diff --git a/README.md b/README.md index f4834a1..50679c0 100644 --- a/README.md +++ b/README.md @@ -3,664 +3,676 @@ HEADER -| [2018](#2018) | [2017](#2017) | [2016](#2016) | [2015](#2015) | [2014](#2014) | [2013](#2013) | 2012 | 2011 | 2010 | 2009 | 2008 | [![Tweet](https://img.shields.io/twitter/url/http/shields.io.svg?style=social)](https://twitter.com/intent/tweet?text=Papers%20with%20code.%20Sorted%20by%20stars.%20Updated%20weekly.%20&url=https://github.com/zziz/pwc&via=fvzaur&hashtags=machinelearning,paper,code,github) | [Suggestions](https://github.com/zziz/pwc/issues/1) | +| [2020](#2020) | [2019](#2019) | [2018](#2018) | [2017](#2017) | [2016](#2016) | [2015](#2015) | [2014](#2014) | [2013](#2013) | 2012 | 2011 | 2010 | 2009 | 2008 | [![Tweet](https://img.shields.io/twitter/url/http/shields.io.svg?style=social)](https://twitter.com/intent/tweet?text=Papers%20with%20code.%20Sorted%20by%20stars.%20Updated%20weekly.%20&url=https://github.com/zziz/pwc&via=fvzaur&hashtags=machinelearning,paper,code,github) | [Suggestions](https://github.com/zziz/pwc/issues/1) | |:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:| This work is in continuous progress and update. We are adding new PWC everyday! Tweet me [@fvzaur](https://twitter.com/fvzaur) Use [this](https://github.com/zziz/pwc/issues/11) thread to request us your favorite conference to be added to our watchlist and to PWC list. -#### Weekly updated pushed! +#### Weekly updated pushed! + +## 2020 +| Title | Conf | Code | Stars | +|:--------|:--------:|:--------:|:--------:| +| [Restricting the Flow: Information Bottlenecks for Attribution](https://arxiv.org/pdf/2001.00396v1.pdf) | [code](https://github.com/attribution-bottleneck/attribution-bottleneck-pytorch) | ICLR | 20 +| [Inferring Commuting Routes and Transportation Modes from Call Detail Records](https://1drv.ms/b/s!Ap6B8pGCJqB6hogwlsUKNaJJRkCJlg?e=m4GFWp) | [code](https://github.com/joelpires/CDRsDataAnalysis) | TRA2020 | 0 | + +## 2019 +| Title | Conf | Code | Stars | +|:--------|:--------:|:--------:|:--------:| +| [Very Long Natural Scenery Image Prediction by Outpainting](https://arxiv.org/pdf/1912.12688v1.pdf) | [code](https://github.com/attribution-bottleneck/attribution-bottleneck-pytorch) | ICCV | 22 | +| [How the Quality of Call Detail Records Influences the Detection of Commuting Trips](https://link.springer.com/chapter/10.1007/978-3-030-30241-2_54) | [code](https://github.com/joelpires/CDRsDataAnalysis) | EPIA2019 | 0 | ## 2018 | Title | Conf | Code | Stars | |:--------|:--------:|:--------:|:--------:| -| [Video-to-Video Synthesis](https://arxiv.org/abs/1808.06601) | NIPS | [code](https://github.com/NVIDIA/vid2vid) | 5578 | -| [Deep Image Prior](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ulyanov_Deep_Image_Prior_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/DmitryUlyanov/deep-image-prior) | 3736 | -| [StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_StarGAN_Unified_Generative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yunjey/StarGAN) | 3405 | -| [Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network](http://openaccess.thecvf.com/content_ECCV_2018/html/Yao_Feng_Joint_3D_Face_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YadiraF/PRNet) | 2434 | -| [Learning to See in the Dark](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Learning_to_See_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/cchen156/Learning-to-See-in-the-Dark) | 2326 | -| [Glow: Generative Flow with Invertible 1x1 Convolutions](http://arxiv.org/abs/1807.03039v2) | NIPS | [code](https://github.com/openai/glow) | 2088 | -| [Squeeze-and-Excitation Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hujie-frank/SENet) | 1477 | -| [Efficient Neural Architecture Search via Parameters Sharing](http://proceedings.mlr.press/v80/pham18a.html) | ICML | [code](https://github.com/carpedm20/ENAS-pytorch) | 1382 | -| [Multimodal Unsupervised Image-to-image Translation](http://openaccess.thecvf.com/content_ECCV_2018/html/Xun_Huang_Multimodal_Unsupervised_Image-to-image_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NVlabs/MUNIT) | 1296 | -| [Non-Local Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Non-Local_Neural_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/video-nonlocal-net) | 992 | -| [Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hara_Can_Spatiotemporal_3D_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kenshohara/3D-ResNets-PyTorch) | 924 | -| [Single-Shot Refinement Neural Network for Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Single-Shot_Refinement_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sfzhang15/RefineDet) | 875 | -| [Image Generation From Scene Graphs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Johnson_Image_Generation_From_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/google/sg2im) | 851 | -| [GANimation: Anatomically-aware Facial Animation from a Single Image](http://openaccess.thecvf.com/content_ECCV_2018/html/Albert_Pumarola_Anatomically_Coherent_Facial_ECCV_2018_paper.html) | ECCV | [code](https://github.com/albertpumarola/GANimation) | 772 | -| [Simple Baselines for Human Pose Estimation and Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Bin_Xiao_Simple_Baselines_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Microsoft/human-pose-estimation.pytorch) | 752 | -| [Visualizing the Loss Landscape of Neural Nets](http://arxiv.org/abs/1712.09913v2) | NIPS | [code](https://github.com/tomgoldstein/loss-landscape) | 724 | -| [Detect-and-Track: Efficient Pose Estimation in Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Girdhar_Detect-and-Track_Efficient_Pose_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/DetectAndTrack) | 650 | -| [Relation Networks for Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Relation_Networks_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/msracver/Relation-Networks-for-Object-Detection) | 635 | -| [Generative Image Inpainting With Contextual Attention](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Generative_Image_Inpainting_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JiahuiYu/generative_inpainting) | 609 | -| [PointCNN](http://arxiv.org/abs/1801.07791v3) | NIPS | [code](https://github.com/yangyanli/PointCNN) | 607 | -| [Look at Boundary: A Boundary-Aware Face Alignment Algorithm](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Look_at_Boundary_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wywu/LAB) | 575 | -| [Pelee: A Real-Time Object Detection System on Mobile Devices](nan) | NIPS | [code](https://github.com/Robert-JunWang/Pelee) | 548 | -| [Distractor-aware Siamese Networks for Visual Object Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Zhu_Distractor-aware_Siamese_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/foolwood/DaSiamRPN) | 545 | -| [Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples](http://proceedings.mlr.press/v80/athalye18a.html) | ICML | [code](https://github.com/anishathalye/obfuscated-gradients) | 535 | -| [Which Training Methods for GANs do actually Converge?](http://proceedings.mlr.press/v80/mescheder18a.html) | ICML | [code](https://github.com/LMescheder/GAN_stability) | 520 | -| [End-to-End Recovery of Human Shape and Pose](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kanazawa_End-to-End_Recovery_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/akanazawa/hmr) | 502 | -| [Taskonomy: Disentangling Task Transfer Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zamir_Taskonomy_Disentangling_Task_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/StanfordVL/taskonomy) | 502 | -| [Cascaded Pyramid Network for Multi-Person Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Cascaded_Pyramid_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chenyilun95/tf-cpn) | 497 | -| [Neural 3D Mesh Renderer](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kato_Neural_3D_Mesh_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hiroharu-kato/neural_renderer) | 489 | -| [Zero-Shot Recognition via Semantic Embeddings and Knowledge Graphs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Zero-Shot_Recognition_via_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JudyYe/zero-shot-gcn) | 489 | -| [In-Place Activated BatchNorm for Memory-Optimized Training of DNNs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bulo_In-Place_Activated_BatchNorm_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mapillary/inplace_abn) | 485 | -| [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_The_Unreasonable_Effectiveness_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/richzhang/PerceptualSimilarity) | 447 | -| [Frustum PointNets for 3D Object Detection From RGB-D Data](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Frustum_PointNets_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/charlesq34/frustum-pointnets) | 434 | -| [The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Berman_The_LovaSz-Softmax_Loss_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/bermanmaxim/LovaszSoftmax) | 416 | -| [ICNet for Real-Time Semantic Segmentation on High-Resolution Images](http://openaccess.thecvf.com/content_ECCV_2018/html/Hengshuang_Zhao_ICNet_for_Real-Time_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hszhao/ICNet) | 415 | -| [PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_PWC-Net_CNNs_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/NVlabs/PWC-Net) | 398 | -| [Efficient Interactive Annotation of Segmentation Datasets With Polygon-RNN++](http://openaccess.thecvf.com/content_cvpr_2018/papers/Acuna_Efficient_Interactive_Annotation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/fidler-lab/polyrnn-pp-pytorch) | 397 | -| [Gibson Env: Real-World Perception for Embodied Agents](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xia_Gibson_Env_Real-World_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/StanfordVL/GibsonEnv) | 385 | -| [Acquisition of Localization Confidence for Accurate Object Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Borui_Jiang_Acquisition_of_Localization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/vacancy/PreciseRoIPooling) | 384 | -| [Noise2Noise: Learning Image Restoration without Clean Data](http://proceedings.mlr.press/v80/lehtinen18a.html) | ICML | [code](https://github.com/yu4u/noise2noise) | 370 | -| [GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_GeoNet_Geometric_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yzcjtr/GeoNet) | 359 | -| [GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yin_GeoNet_Unsupervised_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yzcjtr/GeoNet) | 359 | -| [A Style-Aware Content Loss for Real-time HD Style Transfer](http://openaccess.thecvf.com/content_ECCV_2018/html/Artsiom_Sanakoyeu_A_Style-aware_Content_ECCV_2018_paper.html) | ECCV | [code](https://github.com/CompVis/adaptive-style-transfer) | 349 | -| [Soccer on Your Tabletop](http://openaccess.thecvf.com/content_cvpr_2018/papers/Rematas_Soccer_on_Your_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/krematas/soccerontable) | 338 | -| [Pyramid Stereo Matching Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chang_Pyramid_Stereo_Matching_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JiaRenChang/PSMNet) | 335 | -| [Neural Baby Talk](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lu_Neural_Baby_Talk_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiasenlu/NeuralBabyTalk) | 332 | -| [License Plate Detection and Recognition in Unconstrained Scenarios](http://openaccess.thecvf.com/content_ECCV_2018/html/Sergio_Silva_License_Plate_Detection_ECCV_2018_paper.html) | ECCV | [code](https://github.com/sergiomsilva/alpr-unconstrained) | 326 | -| [Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors](http://openaccess.thecvf.com/content_cvpr_2018/papers/Dong_Supervision-by-Registration_An_Unsupervised_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/supervision-by-registration) | 326 | -| [Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images](http://openaccess.thecvf.com/content_ECCV_2018/html/Nanyang_Wang_Pixel2Mesh_Generating_3D_ECCV_2018_paper.html) | ECCV | [code](https://github.com/nywang16/Pixel2Mesh) | 323 | -| [Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mascharka_Transparency_by_Design_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/davidmascharka/tbd-nets) | 317 | -| [Fast End-to-End Trainable Guided Filter](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Fast_End-to-End_Trainable_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wuhuikai/DeepGuidedFilter) | 312 | -| [Deep Clustering for Unsupervised Learning of Visual Features](http://openaccess.thecvf.com/content_ECCV_2018/html/Mathilde_Caron_Deep_Clustering_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/facebookresearch/deepcluster) | 302 | -| [Deep Photo Enhancer: Unpaired Learning for Image Enhancement From Photographs With GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Deep_Photo_Enhancer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/nothinglo/Deep-Photo-Enhancer) | 294 | -| [Neural Relational Inference for Interacting Systems](http://proceedings.mlr.press/v80/kipf18a.html) | ICML | [code](https://github.com/ethanfetaya/NRI) | 289 | -| [Adversarially Regularized Autoencoders](http://proceedings.mlr.press/v80/zhao18b.html) | ICML | [code](https://github.com/jakezhaojb/ARAE) | 282 | -| [Learning to Adapt Structured Output Space for Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tsai_Learning_to_Adapt_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wasidennis/AdaptSegNet) | 280 | -| [Convolutional Neural Networks With Alternately Updated Clique](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Convolutional_Neural_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/iboing/CliqueNet) | 272 | -| [Learning to Segment Every Thing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Learning_to_Segment_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ronghanghu/seg_every_thing) | 269 | -| [Supervising Unsupervised Learning](http://arxiv.org/abs/1709.05262v2) | NIPS | [code](https://github.com/quinnliu/machineLearning) | 262 | -| [LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hui_LiteFlowNet_A_Lightweight_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/twhui/LiteFlowNet) | 261 | -| [Bilinear Attention Networks](http://arxiv.org/abs/1805.07932v1) | NIPS | [code](https://github.com/jnhwkim/ban-vqa) | 258 | -| [ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Sachin_Mehta_ESPNet_Efficient_Spatial_ECCV_2018_paper.html) | ECCV | [code](https://github.com/sacmehta/ESPNet) | 254 | -| [An intriguing failing of convolutional neural networks and the CoordConv solution](https://arxiv.org/abs/1807.03247) | NIPS | [code](https://github.com/mkocabas/CoordConv-pytorch) | 249 | -| [End-to-End Learning of Motion Representation for Video Understanding](http://openaccess.thecvf.com/content_cvpr_2018/papers/Fan_End-to-End_Learning_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/LijieFan/tvnet) | 238 | -| [Image Super-Resolution Using Very Deep Residual Channel Attention Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Yulun_Zhang_Image_Super-Resolution_Using_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yulunzhang/RCAN) | 234 | -| [Iterative Visual Reasoning Beyond Convolutions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Iterative_Visual_Reasoning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/endernewton/iter-reason) | 228 | -| [Semi-Parametric Image Synthesis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Semi-Parametric_Image_Synthesis_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xjqicuhk/SIMS) | 226 | -| [Compressed Video Action Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Compressed_Video_Action_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chaoyuaw/pytorch-coviar) | 225 | -| [Style Aggregated Network for Facial Landmark Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Dong_Style_Aggregated_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/D-X-Y/SAN) | 223 | -| [Pose-Robust Face Recognition via Deep Residual Equivariant Mapping](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Pose-Robust_Face_Recognition_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/penincillin/DREAM) | 220 | -| [Multi-Content GAN for Few-Shot Font Style Transfer](http://openaccess.thecvf.com/content_cvpr_2018/papers/Azadi_Multi-Content_GAN_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/azadis/MC-GAN) | 218 | -| [GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models](http://proceedings.mlr.press/v80/you18a.html) | ICML | [code](https://github.com/JiaxuanYou/graph-generation) | 214 | -| [Referring Relationships](http://openaccess.thecvf.com/content_cvpr_2018/papers/Krishna_Referring_Relationships_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/StanfordVL/ReferringRelationships) | 210 | -| [MoCoGAN: Decomposing Motion and Content for Video Generation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulyakov_MoCoGAN_Decomposing_Motion_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sergeytulyakov/mocogan) | 205 | -| [Latent Alignment and Variational Attention](http://arxiv.org/abs/1807.03756v1) | NIPS | [code](https://github.com/harvardnlp/var-attn) | 204 | -| [LayoutNet: Reconstructing the 3D Room Layout From a Single RGB Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zou_LayoutNet_Reconstructing_the_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zouchuhang/LayoutNet) | 202 | -| [Large-Scale Point Cloud Semantic Segmentation With Superpoint Graphs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Landrieu_Large-Scale_Point_Cloud_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/loicland/superpoint_graph) | 197 | -| [An End-to-End TextSpotter With Explicit Alignment and Attention](http://openaccess.thecvf.com/content_cvpr_2018/papers/He_An_End-to-End_TextSpotter_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tonghe90/textspotter) | 195 | -| [DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kupyn_DeblurGAN_Blind_Motion_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/RaphaelMeudec/deblur-gan) | 189 | -| [SPLATNet: Sparse Lattice Networks for Point Cloud Processing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Su_SPLATNet_Sparse_Lattice_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/NVlabs/splatnet) | 188 | -| [Attentive Generative Adversarial Network for Raindrop Removal From a Single Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qian_Attentive_Generative_Adversarial_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rui1996/DeRaindrop) | 186 | -| [Single View Stereo Matching](http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_Single_View_Stereo_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lawy623/SVS) | 182 | -| [MegaDepth: Learning Single-View Depth Prediction From Internet Photos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_MegaDepth_Learning_Single-View_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lixx2938/MegaDepth) | 181 | -| [ECO: Efficient Convolutional Network for Online Video Understanding](http://openaccess.thecvf.com/content_ECCV_2018/html/Mohammadreza_Zolfaghari_ECO_Efficient_Convolutional_ECCV_2018_paper.html) | ECCV | [code](https://github.com/mzolfaghari/ECO-efficient-video-understanding) | 180 | -| [Unsupervised Feature Learning via Non-Parametric Instance Discrimination](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Unsupervised_Feature_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhirongw/lemniscate.pytorch) | 180 | -| [ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_ST-GAN_Spatial_Transformer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chenhsuanlin/spatial-transformer-GAN) | 179 | -| [Video Based Reconstruction of 3D People Models](http://openaccess.thecvf.com/content_cvpr_2018/papers/Alldieck_Video_Based_Reconstruction_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/thmoa/videoavatars) | 179 | -| [Social GAN: Socially Acceptable Trajectories With Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gupta_Social_GAN_Socially_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/agrimgupta92/sgan) | 178 | -| [Learning Category-Specific Mesh Reconstruction from Image Collections](http://openaccess.thecvf.com/content_ECCV_2018/html/Angjoo_Kanazawa_Learning_Category-Specific_Mesh_ECCV_2018_paper.html) | ECCV | [code](https://github.com/akanazawa/cmr) | 176 | -| [Realistic Evaluation of Deep Semi-Supervised Learning Algorithms](http://arxiv.org/abs/1804.09170v2) | NIPS | [code](https://github.com/brain-research/realistic-ssl-evaluation) | 175 | -| [BSN: Boundary Sensitive Network for Temporal Action Proposal Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Tianwei_Lin_BSN_Boundary_Sensitive_ECCV_2018_paper.html) | ECCV | [code](https://github.com/wzmsltw/BSN-boundary-sensitive-network) | 175 | -| [Group Normalization](http://openaccess.thecvf.com/content_ECCV_2018/html/Yuxin_Wu_Group_Normalization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/shaohua0116/Group-Normalization-Tensorflow) | 175 | -| [Real-Time Seamless Single Shot 6D Object Pose Prediction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tekin_Real-Time_Seamless_Single_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Microsoft/singleshotpose) | 174 | -| [MVSNet: Depth Inference for Unstructured Multi-view Stereo](http://openaccess.thecvf.com/content_ECCV_2018/html/Yao_Yao_MVSNet_Depth_Inference_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YoYo000/MVSNet) | 174 | -| [Neural Motifs: Scene Graph Parsing With Global Context](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zellers_Neural_Motifs_Scene_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rowanz/neural-motifs) | 171 | -| [Learning a Single Convolutional Super-Resolution Network for Multiple Degradations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Learning_a_Single_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/cszn/SRMD) | 169 | -| [Optimizing Video Object Detection via a Scale-Time Lattice](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Optimizing_Video_Object_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hellock/scale-time-lattice) | 168 | -| [MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network](http://openaccess.thecvf.com/content_ECCV_2018/html/Muhammed_Kocabas_MultiPoseNet_Fast_Multi-Person_ECCV_2018_paper.html) | ECCV | [code](https://github.com/salihkaragoz/pose-residual-network-pytorch) | 167 | -| [Unsupervised Cross-Dataset Person Re-Identification by Transfer Learning of Spatial-Temporal Patterns](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lv_Unsupervised_Cross-Dataset_Person_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ahangchen/TFusion) | 166 | -| [Weakly Supervised Instance Segmentation Using Class Peak Response](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Weakly_Supervised_Instance_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ZhouYanzhao/PRM) | 166 | -| [PlaneNet: Piece-Wise Planar Reconstruction From a Single RGB Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_PlaneNet_Piece-Wise_Planar_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/art-programmer/PlaneNet) | 164 | -| [Residual Dense Network for Image Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Residual_Dense_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yulunzhang/RDN) | 163 | -| [Embodied Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Das_Embodied_Question_Answering_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/EmbodiedQA) | 162 | -| [Evolved Policy Gradients](http://arxiv.org/abs/1802.04821v2) | NIPS | [code](https://github.com/openai/EPG) | 160 | -| [Camera Style Adaptation for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhong_Camera_Style_Adaptation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhunzhong07/CamStyle) | 159 | -| [Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer](http://openaccess.thecvf.com/content_cvpr_2018/papers/Fang_Weakly_and_Semi_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/MVIG-SJTU/WSHP) | 159 | -| [Scale-Recurrent Network for Deep Image Deblurring](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tao_Scale-Recurrent_Network_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiangsutx/SRN-Deblur) | 159 | -| [Unsupervised Learning of Monocular Depth Estimation and Visual Odometry With Deep Feature Reconstruction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhan_Unsupervised_Learning_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Huangying-Zhan/Depth-VO-Feat) | 158 | -| [Relational recurrent neural networks](https://arxiv.org/abs/1806.01822) | NIPS | [code](https://github.com/L0SG/relational-rnn-pytorch) | 157 | -| [Densely Connected Pyramid Dehazing Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Densely_Connected_Pyramid_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hezhangsprinter/DCPDN) | 155 | -| [Image Inpainting for Irregular Holes Using Partial Convolutions](http://openaccess.thecvf.com/content_ECCV_2018/html/Guilin_Liu_Image_Inpainting_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/naoto0804/pytorch-inpainting-with-partial-conv) | 153 | -| [SO-Net: Self-Organizing Network for Point Cloud Analysis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_SO-Net_Self-Organizing_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lijx10/SO-Net) | 152 | -| [Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_Pix3D_Dataset_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xingyuansun/pix3d) | 152 | -| [ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_ShuffleNet_An_Extremely_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/camel007/Caffe-ShuffleNet) | 152 | -| [DenseASPP for Semantic Segmentation in Street Scenes](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_DenseASPP_for_Semantic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/DeepMotionAIResearch/DenseASPP) | 151 | -| [Facelet-Bank for Fast Portrait Manipulation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Facelet-Bank_for_Fast_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yingcong/Facelet_Bank) | 150 | -| [Self-Imitation Learning](http://proceedings.mlr.press/v80/oh18b.html) | ICML | [code](https://github.com/junhyukoh/self-imitation-learning) | 145 | -| [Graph R-CNN for Scene Graph Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Jianwei_Yang_Graph_R-CNN_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/jwyang/graph-rcnn.pytorch) | 144 | -| [A Closer Look at Spatiotemporal Convolutions for Action Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tran_A_Closer_Look_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/irhumshafkat/R2Plus1D-PyTorch) | 143 | -| [Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Inoue_Cross-Domain_Weakly-Supervised_Object_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/naoto0804/cross-domain-detection) | 143 | -| [Quantized Densely Connected U-Nets for Efficient Landmark Localization](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhiqiang_Tang_Quantized_Densely_Connected_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zhiqiangdon/CU-Net) | 143 | -| [Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining](http://openaccess.thecvf.com/content_ECCV_2018/html/Xia_Li_Recurrent_Squeeze-and-Excitation_Context_ECCV_2018_paper.html) | ECCV | [code](https://github.com/XiaLiPKU/RESCAN) | 142 | -| [Two-Stream Convolutional Networks for Dynamic Texture Synthesis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tesfaldet_Two-Stream_Convolutional_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ryersonvisionlab/two-stream-dyntex-synth) | 141 | -| [Integral Human Pose Regression](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiao_Sun_Integral_Human_Pose_ECCV_2018_paper.html) | ECCV | [code](https://github.com/JimmySuen/integral-human-pose) | 141 | -| [Adaptive Affinity Fields for Semantic Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Jyh-Jing_Hwang_Adaptive_Affinity_Field_ECCV_2018_paper.html) | ECCV | [code](https://github.com/twke18/Adaptive_Affinity_Fields) | 141 | -| [LSTM Pose Machines](http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_LSTM_Pose_Machines_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lawy623/LSTM_Pose_Machines) | 141 | -| [Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Structure_Inference_Net_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/choasup/SIN) | 140 | -| [Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Recovering_Realistic_Texture_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xinntao/CVPR18-SFTGAN) | 139 | -| [Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Deng_Image-Image_Domain_Adaptation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Simon4Yan/Learning-via-Translation) | 137 | -| [Learning to Compare: Relation Network for Few-Shot Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sung_Learning_to_Compare_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lzrobots/LearningToCompare_ZSL) | 135 | -| [CosFace: Large Margin Cosine Loss for Deep Face Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_CosFace_Large_Margin_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yule-li/CosFace) | 135 | -| [Deep Depth Completion of a Single RGB-D Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Deep_Depth_Completion_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yindaz/DeepCompletionRelease) | 134 | -| [Deep Back-Projection Networks for Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2018/papers/Haris_Deep_Back-Projection_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alterzero/DBPN-Pytorch) | 132 | -| [Context Embedding Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kim_Context_Embedding_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/thunlp/CANE) | 131 | -| [Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kendall_Multi-Task_Learning_Using_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alexgkendall/multitaskvision) | 131 | -| [Perturbative Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Juefei-Xu_Perturbative_Neural_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/juefeix/pnn.pytorch) | 130 | -| [Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis](http://proceedings.mlr.press/v80/wang18h.html) | ICML | [code](https://github.com/syang1993/gst-tacotron) | 129 | -| [Fast and Accurate Online Video Object Segmentation via Tracking Parts](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cheng_Fast_and_Accurate_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JingchunCheng/FAVOS) | 129 | -| [Nonlinear 3D Face Morphable Model](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tran_Nonlinear_3D_Face_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tranluan/Nonlinear_Face_3DMM) | 128 | -| [BodyNet: Volumetric Inference of 3D Human Body Shapes](http://openaccess.thecvf.com/content_ECCV_2018/html/Gul_Varol_BodyNet_Volumetric_Inference_ECCV_2018_paper.html) | ECCV | [code](https://github.com/gulvarol/bodynet) | 126 | -| [3D-CODED: 3D Correspondences by Deep Deformation](http://openaccess.thecvf.com/content_ECCV_2018/html/Thibault_Groueix_Shape_correspondences_from_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ThibaultGROUEIX/3D-CODED) | 125 | -| [DeepMVS: Learning Multi-View Stereopsis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_DeepMVS_Learning_Multi-View_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/phuang17/DeepMVS) | 125 | -| [Hierarchical Imitation and Reinforcement Learning](http://proceedings.mlr.press/v80/le18a.html) | ICML | [code](https://github.com/hoangminhle/hierarchical_IL_RL) | 124 | -| [Domain Adaptive Faster R-CNN for Object Detection in the Wild](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Domain_Adaptive_Faster_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yuhuayc/da-faster-rcnn) | 123 | -| [L4: Practical loss-based stepsize adaptation for deep learning](http://arxiv.org/abs/1802.05074v4) | NIPS | [code](https://github.com/martius-lab/l4-optimizer) | 123 | -| [A Generative Adversarial Approach for Zero-Shot Learning From Noisy Texts](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhu_A_Generative_Adversarial_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/EthanZhu90/ZSL_GAN_CVPR18) | 122 | -| [Recurrent Relational Networks](http://arxiv.org/abs/1711.08028v2) | NIPS | [code](https://github.com/rasmusbergpalm/recurrent-relational-networks) | 121 | -| [Gated Path Planning Networks](http://proceedings.mlr.press/v80/lee18c.html) | ICML | [code](https://github.com/lileee/gated-path-planning-networks) | 121 | -| [PSANet: Point-wise Spatial Attention Network for Scene Parsing](http://openaccess.thecvf.com/content_ECCV_2018/html/Hengshuang_Zhao_PSANet_Point-wise_Spatial_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hszhao/PSANet) | 121 | -| [Rethinking Feature Distribution for Loss Functions in Image Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wan_Rethinking_Feature_Distribution_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/WeitaoVan/L-GM-loss) | 120 | -| [Density-Aware Single Image De-Raining Using a Multi-Stream Dense Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Density-Aware_Single_Image_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hezhangsprinter/DID-MDN) | 118 | -| [FOTS: Fast Oriented Text Spotting With a Unified Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_FOTS_Fast_Oriented_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiangxiluning/FOTS.PyTorch) | 118 | -| [ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes](http://openaccess.thecvf.com/content_ECCV_2018/html/Taihong_Xiao_ELEGANT_Exchanging_Latent_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Prinsphield/ELEGANT) | 117 | -| [PU-Net: Point Cloud Upsampling Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_PU-Net_Point_Cloud_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yulequan/PU-Net) | 117 | -| [PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mallya_PackNet_Adding_Multiple_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/arunmallya/packnet) | 117 | -| [Long-term Tracking in the Wild: a Benchmark](http://openaccess.thecvf.com/content_ECCV_2018/html/Efstratios_Gavves_Long-term_Tracking_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/oxuva/long-term-tracking-benchmark) | 116 | -| [Factoring Shape, Pose, and Layout From the 2D Image of a 3D Scene](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulsiani_Factoring_Shape_Pose_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/shubhtuls/factored3d) | 114 | -| [Repulsion Loss: Detecting Pedestrians in a Crowd](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Repulsion_Loss_Detecting_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/bailvwangzi/repulsion_loss_ssd) | 113 | -| [Unsupervised Attention-guided Image-to-Image Translation](https://arxiv.org/abs/1806.02311) | NIPS | [code](https://github.com/AlamiMejjati/Unsupervised-Attention-guided-Image-to-Image-Translation) | 110 | -| [Attention-based Deep Multiple Instance Learning](http://proceedings.mlr.press/v80/ilse18a.html) | ICML | [code](https://github.com/AMLab-Amsterdam/AttentionDeepMIL) | 109 | -| [Learning Blind Video Temporal Consistency](http://openaccess.thecvf.com/content_ECCV_2018/html/Wei-Sheng_Lai_Real-Time_Blind_Video_ECCV_2018_paper.html) | ECCV | [code](https://github.com/phoenix104104/fast_blind_video_consistency) | 109 | -| [Noisy Natural Gradient as Variational Inference](http://proceedings.mlr.press/v80/zhang18l.html) | ICML | [code](https://github.com/wlwkgus/NoisyNaturalGradient) | 108 | -| [End-to-End Weakly-Supervised Semantic Alignment](http://openaccess.thecvf.com/content_cvpr_2018/papers/Rocco_End-to-End_Weakly-Supervised_Semantic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ignacio-rocco/weakalign) | 106 | -| [Decoupled Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Decoupled_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wy1iu/DCNets) | 105 | -| [LiDAR-Video Driving Dataset: Learning Driving Policies Effectively](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_LiDAR-Video_Driving_Dataset_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/driving-behavior/DBNet) | 104 | -| [MAttNet: Modular Attention Network for Referring Expression Comprehension](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_MAttNet_Modular_Attention_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lichengunc/MAttNet) | 104 | -| [LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Dongqing_Zhang_Optimized_Quantization_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Microsoft/LQ-Nets) | 103 | -| [FSRNet: End-to-End Learning Face Super-Resolution With Facial Priors](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_FSRNet_End-to-End_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tyshiwo/FSRNet) | 100 | -| [Deep Mutual Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Deep_Mutual_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/YingZhangDUT/Deep-Mutual-Learning) | 100 | -| [Macro-Micro Adversarial Network for Human Parsing](http://openaccess.thecvf.com/content_ECCV_2018/html/Yawei_Luo_Macro-Micro_Adversarial_Network_ECCV_2018_paper.html) | ECCV | [code](https://github.com/RoyalVane/MMAN) | 98 | -| [ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans](http://openaccess.thecvf.com/content_cvpr_2018/papers/Dai_ScanComplete_Large-Scale_Scene_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/angeladai/ScanComplete) | 97 | -| [Learning Depth From Monocular Videos Using Direct Methods](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_Depth_From_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/MightyChaos/LKVOLearner) | 97 | -| [VITON: An Image-Based Virtual Try-On Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Han_VITON_An_Image-Based_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xthan/VITON) | 95 | -| [Cascade R-CNN: Delving Into High Quality Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cai_Cascade_R-CNN_Delving_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/guoruoqian/cascade-rcnn_Pytorch) | 93 | -| [Learning Human-Object Interactions by Graph Parsing Neural Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Siyuan_Qi_Learning_Human-Object_Interactions_ECCV_2018_paper.html) | ECCV | [code](https://github.com/SiyuanQi/gpnn) | 93 | -| [Future Frame Prediction for Anomaly Detection – A New Baseline](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Future_Frame_Prediction_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/StevenLiuWen/ano_pred_cvpr2018) | 92 | -| [Multi-view to Novel view: Synthesizing novel views with Self-Learned Confidence](http://openaccess.thecvf.com/content_ECCV_2018/html/Shao-Hua_Sun_Multi-view_to_Novel_ECCV_2018_paper.html) | ECCV | [code](https://github.com/shaohua0116/Multiview2Novelview) | 92 | -| [Tell Me Where to Look: Guided Attention Inference Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Tell_Me_Where_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alokwhitewolf/Guided-Attention-Inference-Network) | 91 | -| [Neural Kinematic Networks for Unsupervised Motion Retargetting](http://openaccess.thecvf.com/content_cvpr_2018/papers/Villegas_Neural_Kinematic_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rubenvillegas/cvpr2018nkn) | 90 | -| [Learning SO(3) Equivariant Representations with Spherical CNNs](http://openaccess.thecvf.com/content_ECCV_2018/html/Carlos_Esteves_Learning_SO3_Equivariant_ECCV_2018_paper.html) | ECCV | [code](https://github.com/daniilidis-group/spherical-cnn) | 89 | -| [One-Shot Unsupervised Cross Domain Translation](http://arxiv.org/abs/1806.06029v1) | NIPS | [code](https://github.com/sagiebenaim/OneShotTranslation) | 89 | -| [Synthesizing Images of Humans in Unseen Poses](http://openaccess.thecvf.com/content_cvpr_2018/papers/Balakrishnan_Synthesizing_Images_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/balakg/posewarp-cvpr2018) | 88 | -| [Depth-aware CNN for RGB-D Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Weiyue_Wang_Depth-aware_CNN_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/laughtervv/DepthAwareCNN) | 88 | -| [Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights](http://openaccess.thecvf.com/content_ECCV_2018/html/Arun_Mallya_Piggyback_Adapting_a_ECCV_2018_paper.html) | ECCV | [code](https://github.com/arunmallya/piggyback) | 88 | -| [Knowledge Aided Consistency for Weakly Supervised Phrase Grounding](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Knowledge_Aided_Consistency_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kanchen-usc/KAC-Net) | 87 | -| [CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_CSRNet_Dilated_Convolutional_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/leeyeehoo/CSRNet-pytorch) | 87 | -| [Neural Arithmetic Logic Units](http://arxiv.org/abs/1808.00508v1) | NIPS | [code](https://github.com/llSourcell/Neural_Arithmetic_Logic_Units) | 87 | -| [A PID Controller Approach for Stochastic Optimization of Deep Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/An_A_PID_Controller_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tensorboy/PIDOptimizer) | 87 | -| [VITAL: VIsual Tracking via Adversarial Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_VITAL_VIsual_Tracking_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ybsong00/Vital_release) | 86 | -| [Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Spatial-Temporal_Regularized_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lifeng9472/STRCF) | 86 | -| [Recurrent Pixel Embedding for Instance Grouping](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kong_Recurrent_Pixel_Embedding_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/aimerykong/Recurrent-Pixel-Embedding-for-Instance-Grouping) | 85 | -| [SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_SGPN_Similarity_Group_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/laughtervv/SGPN) | 84 | -| [Multi-Scale Location-Aware Kernel Representation for Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Multi-Scale_Location-Aware_Kernel_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Hwang64/MLKP) | 84 | -| [Repeatability Is Not Enough: Learning Affine Regions via Discriminability](http://openaccess.thecvf.com/content_ECCV_2018/html/Dmytro_Mishkin_Repeatability_Is_Not_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ducha-aiki/affnet) | 84 | -| [“Zero-Shot” Super-Resolution Using Deep Internal Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shocher_Zero-Shot_Super-Resolution_Using_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/assafshocher/ZSSR) | 84 | -| [DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency](http://openaccess.thecvf.com/content_ECCV_2018/html/Yuliang_Zou_DF-Net_Unsupervised_Joint_ECCV_2018_paper.html) | ECCV | [code](https://github.com/vt-vl-lab/DF-Net) | 82 | -| [Multi-View Consistency as Supervisory Signal for Learning Shape and Pose Prediction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulsiani_Multi-View_Consistency_as_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/shubhtuls/mvcSnP) | 80 | -| [Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Yikang_LI_Factorizable_Net_An_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yikang-li/FactorizableNet) | 78 | -| [Generalizing A Person Retrieval Model Hetero- and Homogeneously](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhun_Zhong_Generalizing_A_Person_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zhunzhong07/HHL) | 78 | -| [Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Crafting_a_Toolchain_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yuke93/RL-Restore) | 77 | -| [Pairwise Confusion for Fine-Grained Visual Classification](http://openaccess.thecvf.com/content_ECCV_2018/html/Abhimanyu_Dubey_Improving_Fine-Grained_Visual_ECCV_2018_paper.html) | ECCV | [code](https://github.com/abhimanyudubey/confusion) | 77 | -| [Learning to Reweight Examples for Robust Deep Learning](http://proceedings.mlr.press/v80/ren18a.html) | ICML | [code](https://github.com/danieltan07/learning-to-reweight-examples) | 76 | -| [Improving Generalization via Scalable Neighborhood Component Analysis](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhirong_Wu_Improving_Embedding_Generalization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Microsoft/snca.pytorch) | 76 | -| [SparseMAP: Differentiable Sparse Structured Inference](http://proceedings.mlr.press/v80/niculae18a.html) | ICML | [code](https://github.com/vene/sparsemap) | 75 | -| [PDE-Net: Learning PDEs from Data](http://proceedings.mlr.press/v80/long18a.html) | ICML | [code](https://github.com/ZichaoLong/PDE-Net) | 75 | -| [Pose-Normalized Image Generation for Person Re-identification](http://openaccess.thecvf.com/content_ECCV_2018/html/Xuelin_Qian_Pose-Normalized_Image_Generation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/naiq/PN_GAN) | 75 | -| [Disentangled Person Image Generation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ma_Disentangled_Person_Image_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/charliememory/Disentangled-Person-Image-Generation) | 75 | -| [Learning to Navigate for Fine-grained Classification](http://openaccess.thecvf.com/content_ECCV_2018/html/Ze_Yang_Learning_to_Navigate_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yangze0930/NTS-Net) | 74 | -| [Superpixel Sampling Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Varun_Jampani_Superpixel_Sampling_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NVlabs/ssn_superpixels) | 74 | -| [Shift-Net: Image Inpainting via Deep Feature Rearrangement](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhaoyi_Yan_Shift-Net_Image_Inpainting_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Zhaoyi-Yan/Shift-Net_pytorch) | 74 | -| [3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Angela_Dai_3DMV_Joint_3D-Multi-View_ECCV_2018_paper.html) | ECCV | [code](https://github.com/angeladai/3DMV) | 74 | -| [Ordinal Depth Supervision for 3D Human Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Pavlakos_Ordinal_Depth_Supervision_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/geopavlakos/ordinal-pose3d) | 74 | -| [Path-Level Network Transformation for Efficient Architecture Search](http://proceedings.mlr.press/v80/cai18a.html) | ICML | [code](https://github.com/han-cai/PathLevel-EAS) | 73 | -| [Diverse Image-to-Image Translation via Disentangled Representations](http://openaccess.thecvf.com/content_ECCV_2018/html/Hsin-Ying_Lee_Diverse_Image-to-Image_Translation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/taki0112/DRIT-Tensorflow) | 72 | -| [Visual Feature Attribution Using Wasserstein GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Baumgartner_Visual_Feature_Attribution_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/orobix/Visual-Feature-Attribution-Using-Wasserstein-GANs-Pytorch) | 72 | -| [Real-World Anomaly Detection in Surveillance Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sultani_Real-World_Anomaly_Detection_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/WaqasSultani/AnomalyDetectionCVPR2018) | 72 | -| [Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Self-Supervised_Adversarial_Hashing_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lelan-li/SSAH) | 72 | -| [Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image](http://openaccess.thecvf.com/content_ECCV_2018/html/Siyuan_Huang_Monocular_Scene_Parsing_ECCV_2018_paper.html) | ECCV | [code](https://github.com/thusiyuan/holistic_scene_parsing) | 72 | -| [Learning to Find Good Correspondences](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yi_Learning_to_Find_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/vcg-uvic/learned-correspondence-release) | 72 | -| [Learning Less Is More - 6D Camera Localization via 3D Surface Regression](http://openaccess.thecvf.com/content_cvpr_2018/papers/Brachmann_Learning_Less_Is_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/vislearn/LessMore) | 72 | -| [Object Level Visual Reasoning in Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Fabien_Baradel_Object_Level_Visual_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fabienbaradel/object_level_visual_reasoning) | 71 | -| [Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Weakly-Supervised_Semantic_Segmentation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/speedinghzl/DSRG) | 71 | -| [Avatar-Net: Multi-Scale Zero-Shot Style Transfer by Feature Decoration](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sheng_Avatar-Net_Multi-Scale_Zero-Shot_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/LucasSheng/avatar-net) | 71 | -| [Fast and Accurate Single Image Super-Resolution via Information Distillation Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hui_Fast_and_Accurate_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Zheng222/IDN-Caffe) | 71 | -| [Regularizing RNNs for Caption Generation by Reconstructing the Past With the Present](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Regularizing_RNNs_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chenxinpeng/ARNet) | 70 | -| [Multi-Shot Pedestrian Re-Identification via Sequential Decision Making](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Multi-Shot_Pedestrian_Re-Identification_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/TuSimple/rl-multishot-reid) | 70 | -| [PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Uy_PointNetVLAD_Deep_Point_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mikacuy/pointnetvlad) | 69 | -| [Progressive Neural Architecture Search](http://openaccess.thecvf.com/content_ECCV_2018/html/Chenxi_Liu_Progressive_Neural_Architecture_ECCV_2018_paper.html) | ECCV | [code](https://github.com/titu1994/progressive-neural-architecture-search) | 68 | -| [Generative Neural Machine Translation](http://arxiv.org/abs/1806.05138v1) | NIPS | [code](https://github.com/ZhenYangIACAS/NMT_GAN) | 68 | -| [Learning Latent Super-Events to Detect Multiple Activities in Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Piergiovanni_Learning_Latent_Super-Events_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/piergiaj/super-events-cvpr18) | 67 | -| [Generate to Adapt: Aligning Domains Using Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Generate_to_Adapt_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yogeshbalaji/Generate_To_Adapt) | 67 | -| [Adversarial Feature Augmentation for Unsupervised Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Volpi_Adversarial_Feature_Augmentation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ricvolpi/adversarial-feature-augmentation) | 67 | -| [Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_Attentions_Residual_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/foolwood/RASNet) | 67 | -| [Pointwise Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hua_Pointwise_Convolutional_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/scenenn/pointwise) | 67 | -| [Optimizing the Latent Space of Generative Networks](http://proceedings.mlr.press/v80/bojanowski18a.html) | ICML | [code](https://github.com/tneumann/minimal_glo) | 66 | -| [Part-Aligned Bilinear Representations for Person Re-Identification](http://openaccess.thecvf.com/content_ECCV_2018/html/Yumin_Suh_Part-Aligned_Bilinear_Representations_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yuminsuh/part_bilinear_reid) | 64 | -| [Geometry-Aware Learning of Maps for Camera Localization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Brahmbhatt_Geometry-Aware_Learning_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/samarth-robo/MapNet) | 63 | -| [Fighting Fake News: Image Splice Detection via Learned Self-Consistency](http://openaccess.thecvf.com/content_ECCV_2018/html/Jacob_Huh_Fighting_Fake_News_ECCV_2018_paper.html) | ECCV | [code](https://github.com/minyoungg/selfconsistency) | 62 | -| [Isolating Sources of Disentanglement in Variational Autoencoders](http://arxiv.org/abs/1802.04942v2) | NIPS | [code](https://github.com/rtqichen/beta-tcvae) | 62 | -| [Neural Program Synthesis from Diverse Demonstration Videos](http://proceedings.mlr.press/v80/sun18a.html) | ICML | [code](https://github.com/shaohua0116/demo2program) | 62 | -| [Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhaoyang_Lv_Learning_Rigidity_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NVlabs/learningrigidity) | 61 | -| [Rotation-Sensitive Regression for Oriented Scene Text Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liao_Rotation-Sensitive_Regression_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/MhLiao/RRD) | 61 | -| [Human Semantic Parsing for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kalayeh_Human_Semantic_Parsing_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/emrahbasaran/SPReID) | 61 | -| [Unsupervised Discovery of Object Landmarks as Structural Representations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Unsupervised_Discovery_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/YutingZhang/lmdis-rep) | 61 | -| [IQA: Visual Question Answering in Interactive Environments](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gordon_IQA_Visual_Question_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/danielgordon10/thor-iqa-cvpr-2018) | 60 | -| [Hierarchical Long-term Video Prediction without Supervision](http://proceedings.mlr.press/v80/wichers18a.html) | ICML | [code](https://github.com/brain-research/long-term-video-prediction-without-supervision) | 60 | -| [Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency](http://openaccess.thecvf.com/content_ECCV_2018/html/Xingyi_Zhou_Unsupervised_Domain_Adaptation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/xingyizhou/3DKeypoints-DA) | 60 | -| [Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Exploit_the_Unknown_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Yu-Wu/Exploit-Unknown-Gradually) | 59 | -| [Neural Style Transfer via Meta Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Neural_Style_Transfer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/FalongShen/styletransfer) | 59 | -| [Frame-Recurrent Video Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sajjadi_Frame-Recurrent_Video_Super-Resolution_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/msmsajjadi/FRVSR) | 58 | -| [PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction](http://openaccess.thecvf.com/content_ECCV_2018/html/Yifei_Shi_PlaneMatch_Patch_Coplanarity_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yifeishi/PlaneMatch) | 57 | -| [CBAM: Convolutional Block Attention Module](http://openaccess.thecvf.com/content_ECCV_2018/html/Sanghyun_Woo_Convolutional_Block_Attention_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Youngkl0726/Convolutional-Block-Attention-Module) | 57 | -| [Decorrelated Batch Normalization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Decorrelated_Batch_Normalization_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/umich-vl/DecorrelatedBN) | 57 | -| [Learning Conditioned Graph Structures for Interpretable Visual Question Answering](nan) | NIPS | [code](https://github.com/aimbrain/vqa-project) | 57 | -| [Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition](http://openaccess.thecvf.com/content_ECCV_2018/html/Chaojian_Yu_Hierarchical_Bilinear_Pooling_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ChaojianYu/Hierarchical-Bilinear-Pooling) | 57 | -| [Leveraging Unlabeled Data for Crowd Counting by Learning to Rank](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Leveraging_Unlabeled_Data_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xialeiliu/CrowdCountingCVPR18) | 56 | -| [Deep Marching Cubes: Learning Explicit Surface Representations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liao_Deep_Marching_Cubes_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yiyiliao/deep_marching_cubes) | 56 | -| [Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Learning_From_Synthetic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/swamiviv/LSD-seg) | 56 | -| [LF-Net: Learning Local Features from Images](https://arxiv.org/abs/1805.09662) | NIPS | [code](https://github.com/vcg-uvic/lf-net-release) | 55 | -| [Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model](http://openaccess.thecvf.com/content_ECCV_2018/html/Baris_Gecer_Semi-supervised_Adversarial_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/barisgecer/facegan) | 55 | -| [Discriminability Objective for Training Descriptive Captions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_Discriminability_Objective_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ruotianluo/DiscCaptioning) | 54 | -| [BlockDrop: Dynamic Inference Paths in Residual Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_BlockDrop_Dynamic_Inference_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Tushar-N/blockdrop) | 54 | -| [Conditional Probability Models for Deep Image Compression](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mentzer_Conditional_Probability_Models_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/fab-jul/imgcomp-cvpr) | 54 | -| [Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Peng_Jointly_Optimize_Data_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhiqiangdon/pose-adv-aug) | 54 | -| [Learning towards Minimum Hyperspherical Energy](http://arxiv.org/abs/1805.09298v4) | NIPS | [code](https://github.com/wy1iu/MHE) | 54 | -| [DeepVS: A Deep Learning Based Video Saliency Prediction Approach](http://openaccess.thecvf.com/content_ECCV_2018/html/Lai_Jiang_DeepVS_A_Deep_ECCV_2018_paper.html) | ECCV | [code](https://github.com/remega/OMCNN_2CLSTM) | 53 | -| [Learning Efficient Single-stage Pedestrian Detectors by Asymptotic Localization Fitting](http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html) | ECCV | [code](https://github.com/liuwei16/ALFNet) | 52 | -| [Learning Pixel-Level Semantic Affinity With Image-Level Supervision for Weakly Supervised Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ahn_Learning_Pixel-Level_Semantic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiwoon-ahn/psa) | 52 | -| [Wasserstein Introspective Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_Wasserstein_Introspective_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kjunelee/WINN) | 51 | -| [SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_SketchyGAN_Towards_Diverse_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wchen342/SketchyGAN) | 51 | -| [Self-produced Guidance for Weakly-supervised Object Localization](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaolin_Zhang_Self-produced_Guidance_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/xiaomengyc/SPG) | 51 | -| [Measuring abstract reasoning in neural networks](http://proceedings.mlr.press/v80/santoro18a.html) | ICML | [code](https://github.com/deepmind/abstract-reasoning-matrices) | 51 | -| [A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation](https://arxiv.org/abs/1809.01361) | NIPS | [code](https://github.com/XenderLiu/UFDN) | 51 | -| [RayNet: Learning Volumetric 3D Reconstruction With Ray Potentials](http://openaccess.thecvf.com/content_cvpr_2018/papers/Paschalidou_RayNet_Learning_Volumetric_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/paschalidoud/raynet) | 51 | -| [Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Hyojin_Bahng_Coloring_with_Words_ECCV_2018_paper.html) | ECCV | [code](https://github.com/awesome-davian/Text2Colors) | 50 | -| [Efficient end-to-end learning for quantizable representations](http://proceedings.mlr.press/v80/jeong18a.html) | ICML | [code](https://github.com/maestrojeong/Deep-Hash-Table-ICML18) | 50 | -| [Visual Question Generation as Dual Task of Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Visual_Question_Generation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yikang-li/iQAN) | 50 | -| [Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam](http://proceedings.mlr.press/v80/khan18a.html) | ICML | [code](https://github.com/emtiyaz/vadam) | 49 | -| [Surface Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kostrikov_Surface_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiangzhongshi/SurfaceNetworks) | 48 | -| [Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions](http://proceedings.mlr.press/v80/wu18h.html) | ICML | [code](https://github.com/Sandbox3aster/Deep-K-Means-pytorch) | 48 | -| [Stacked Cross Attention for Image-Text Matching](http://openaccess.thecvf.com/content_ECCV_2018/html/Kuang-Huei_Lee_Stacked_Cross_Attention_ECCV_2018_paper.html) | ECCV | [code](https://github.com/kuanghuei/SCAN) | 48 | -| [Actor and Observer: Joint Modeling of First and Third-Person Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sigurdsson_Actor_and_Observer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/gsig/actor-observer) | 48 | -| [Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Jiang_Super_SloMo_High_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/TheFairBear/Super-SlowMo) | 47 | -| [Learning-based Video Motion Magnification](http://openaccess.thecvf.com/content_ECCV_2018/html/Tae-Hyun_Oh_Learning-based_Video_Motion_ECCV_2018_paper.html) | ECCV | [code](https://github.com/12dmodel/deep_motion_mag) | 47 | -| [Pose Partition Networks for Multi-Person Pose Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Xuecheng_Nie_Pose_Partition_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NieXC/pytorch-ppn) | 47 | -| [Neural Autoregressive Flows](http://proceedings.mlr.press/v80/huang18d.html) | ICML | [code](https://github.com/CW-Huang/NAF) | 47 | -| [Weakly- and Semi-Supervised Panoptic Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Anurag_Arnab_Weakly-_and_Semi-Supervised_ECCV_2018_paper.html) | ECCV | [code](https://github.com/qizhuli/Weakly-Supervised-Panoptic-Segmentation) | 46 | -| [Video Re-localization](http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_Feng_Video_Re-localization_via_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fengyang0317/video_reloc) | 46 | -| [Real-time 'Actor-Critic' Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Boyu_Chen_Real-time_Actor-Critic_Tracking_ECCV_2018_paper.html) | ECCV | [code](https://github.com/bychen515/ACT) | 46 | -| [Black-box Adversarial Attacks with Limited Queries and Information](http://proceedings.mlr.press/v80/ilyas18a.html) | ICML | [code](https://github.com/labsix/limited-blackbox-attacks) | 46 | -| [Hyperbolic Entailment Cones for Learning Hierarchical Embeddings](http://proceedings.mlr.press/v80/ganea18a.html) | ICML | [code](https://github.com/dalab/hyperbolic_cones) | 46 | -| [Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Structured_Attention_Guided_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/danxuhk/StructuredAttentionDepthEstimation) | 46 | -| [Differentiable Compositional Kernel Learning for Gaussian Processes](http://proceedings.mlr.press/v80/sun18e.html) | ICML | [code](https://github.com/ssydasheng/Neural-Kernel-Network) | 45 | -| [Visualizing and Understanding Atari Agents](http://proceedings.mlr.press/v80/greydanus18a.html) | ICML | [code](https://github.com/greydanus/visualize_atari) | 45 | -| [Image Manipulation with Perceptual Discriminators](http://openaccess.thecvf.com/content_ECCV_2018/html/Diana_Sungatullina_Image_Manipulation_with_ECCV_2018_paper.html) | ECCV | [code](https://github.com/egorzakharov/PerceptualGAN) | 45 | -| [Learning Intrinsic Image Decomposition From Watching the World](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Intrinsic_Image_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lixx2938/unsupervised-learning-intrinsic-images) | 45 | -| [Overcoming Catastrophic Forgetting with Hard Attention to the Task](http://proceedings.mlr.press/v80/serra18a.html) | ICML | [code](https://github.com/joansj/hat) | 44 | -| [Learning Pose Specific Representations by Predicting Different Views](http://openaccess.thecvf.com/content_cvpr_2018/papers/Poier_Learning_Pose_Specific_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/poier/PreView) | 44 | -| [Zero-Shot Object Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Ankan_Bansal_Zero-Shot_Object_Detection_ECCV_2018_paper.html) | ECCV | [code](https://github.com/salman-h-khan/ZSD_Release) | 43 | -| [Mean Field Multi-Agent Reinforcement Learning](http://proceedings.mlr.press/v80/yang18d.html) | ICML | [code](https://github.com/mlii/mfrl) | 43 | -| [Partial Adversarial Domain Adaptation](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhangjie_Cao_Partial_Adversarial_Domain_ECCV_2018_paper.html) | ECCV | [code](https://github.com/thuml/PADA) | 43 | -| [Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Xuecheng_Nie_Mutual_Learning_to_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NieXC/pytorch-mula) | 43 | -| [Robust Classification With Convolutional Prototype Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Robust_Classification_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/YangHM/Convolutional-Prototype-Learning) | 43 | -| [SimplE Embedding for Link Prediction in Knowledge Graphs](http://arxiv.org/abs/1802.04868v1) | NIPS | [code](https://github.com/Mehran-k/SimplE) | 42 | -| [PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning](http://proceedings.mlr.press/v80/wang18b.html) | ICML | [code](https://github.com/Yunbo426/predrnn-pp) | 42 | -| [Learning to Blend Photos](http://openaccess.thecvf.com/content_ECCV_2018/html/Wei-Chih_Hung_Learning_to_Blend_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hfslyc/LearnToBlend) | 42 | -| [Mask-Guided Contrastive Attention Model for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_Mask-Guided_Contrastive_Attention_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/developfeng/MGCAM) | 41 | -| [Link Prediction Based on Graph Neural Networks](http://arxiv.org/abs/1802.09691v2) | NIPS | [code](https://github.com/muhanzhang/SEAL) | 41 | -| [Generalisation in humans and deep neural networks](http://arxiv.org/abs/1808.08750v1) | NIPS | [code](https://github.com/rgeirhos/generalisation-humans-DNNs) | 41 | -| [Towards Binary-Valued Gates for Robust LSTM Training](http://proceedings.mlr.press/v80/li18c.html) | ICML | [code](https://github.com/zhuohan123/g2-lstm) | 41 | -| [Multi-scale Residual Network for Image Super-Resolution](http://openaccess.thecvf.com/content_ECCV_2018/html/Juncheng_Li_Multi-scale_Residual_Network_ECCV_2018_paper.html) | ECCV | [code](https://github.com/MIVRC/MSRN-PyTorch) | 41 | -| [Fully Motion-Aware Network for Video Object Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Shiyao_Wang_Fully_Motion-Aware_Network_ECCV_2018_paper.html) | ECCV | [code](https://github.com/wangshy31/MANet_for_Video_Object_Detection) | 41 | -| [Interpretable Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Interpretable_Convolutional_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/seongjunyun/CNN-with-Dual-Local-and-Global-Attention) | 40 | -| [Generative Adversarial Perturbations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Poursaeed_Generative_Adversarial_Perturbations_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/OmidPoursaeed/Generative_Adversarial_Perturbations) | 40 | -| [The Sound of Pixels](http://openaccess.thecvf.com/content_ECCV_2018/html/Hang_Zhao_The_Sound_of_ECCV_2018_paper.html) | ECCV | [code](https://github.com/roudimit/MUSIC_dataset) | 40 | -| [Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Towards_Faster_Training_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiangtaoxie/fast-MPN-COV) | 40 | -| [Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance](http://openaccess.thecvf.com/content_ECCV_2018/html/Ramprasaath_Ramasamy_Selvaraju_Choose_Your_Neuron_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ramprs/neuron-importance-zsl) | 40 | -| [Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation](https://arxiv.org/abs/1802.09987) | NIPS | [code](https://github.com/EdwardSmith1884/Multi-View-Silhouette-and-Depth-Decomposition-for-High-Resolution-3D-Object-Representation) | 40 | -| [Learning Warped Guidance for Blind Face Restoration](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaoming_Li_Learning_Warped_Guidance_ECCV_2018_paper.html) | ECCV | [code](https://github.com/csxmli2016/GFRNet) | 39 | -| [Adversarial Complementary Learning for Weakly Supervised Object Localization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Adversarial_Complementary_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xiaomengyc/ACoL) | 39 | -| [Learning Semantic Representations for Unsupervised Domain Adaptation](http://proceedings.mlr.press/v80/xie18c.html) | ICML | [code](https://github.com/Mid-Push/Moving-Semantic-Transfer-Network) | 39 | -| [Neural Architecture Search with Bayesian Optimisation and Optimal Transport](https://arxiv.org/abs/1802.07191) | NIPS | [code](https://github.com/kirthevasank/nasbot) | 39 | -| [Mutual Information Neural Estimation](http://proceedings.mlr.press/v80/belghazi18a.html) | ICML | [code](https://github.com/MasanoriYamada/Mine_pytorch) | 39 | -| [NetGAN: Generating Graphs via Random Walks](http://proceedings.mlr.press/v80/bojchevski18a.html) | ICML | [code](https://github.com/danielzuegner/netgan) | 39 | -| [Learning to Evaluate Image Captioning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cui_Learning_to_Evaluate_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/richardaecn/cvpr18-caption-eval) | 38 | -| [Hyperbolic Neural Networks](http://arxiv.org/abs/1805.09112v2) | NIPS | [code](https://github.com/dalab/hyperbolic_nn) | 37 | -| [Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Helge_Rhodin_Unsupervised_Geometry-Aware_Representation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hrhodin/UnsupervisedGeometryAwareRepresentationLearning) | 37 | -| [Adversarially Learned One-Class Classifier for Novelty Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sabokrou_Adversarially_Learned_One-Class_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/khalooei/ALOCC-CVPR2018) | 37 | -| [Disentangling by Factorising](http://proceedings.mlr.press/v80/kim18b.html) | ICML | [code](https://github.com/1Konny/FactorVAE) | 37 | -| [Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples](http://proceedings.mlr.press/v80/weiss18a.html) | ICML | [code](https://github.com/tech-srl/lstar_extraction) | 37 | -| [Tangent Convolutions for Dense Prediction in 3D](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tatarchenko_Tangent_Convolutions_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tatarchm/tangent_conv) | 37 | -| [Few-Shot Image Recognition by Predicting Parameters From Activations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qiao_Few-Shot_Image_Recognition_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/joe-siyuan-qiao/FewShot-CVPR) | 37 | -| [Real-Time Monocular Depth Estimation Using Synthetic Data With Domain Adaptation via Image Style Transfer](http://openaccess.thecvf.com/content_cvpr_2018/papers/Atapour-Abarghouei_Real-Time_Monocular_Depth_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/atapour/monocularDepth-Inference) | 37 | -| [Generalizing to Unseen Domains via Adversarial Data Augmentation](http://arxiv.org/abs/1805.12018v1) | NIPS | [code](https://github.com/ricvolpi/generalize-unseen-domains) | 36 | -| [SeGAN: Segmenting and Generating the Invisible](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_SeGAN_Segmenting_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ehsanik/SeGAN) | 36 | -| [Graphical Generative Adversarial Networks](http://arxiv.org/abs/1804.03429v1) | NIPS | [code](https://github.com/zhenxuan00/graphical-gan) | 36 | -| [PieAPP: Perceptual Image-Error Assessment Through Pairwise Preference](http://openaccess.thecvf.com/content_cvpr_2018/papers/Prashnani_PieAPP_Perceptual_Image-Error_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/prashnani/PerceptualImageError) | 36 | -| [Gated Fusion Network for Single Image Dehazing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ren_Gated_Fusion_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rwenqi/GFN-dehazing) | 35 | -| [Neural Code Comprehension: A Learnable Representation of Code Semantics](http://arxiv.org/abs/1806.07336v2) | NIPS | [code](https://github.com/spcl/ncc) | 35 | -| [Eye In-Painting With Exemplar Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Dolhansky_Eye_In-Painting_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhangqianhui/Exemplar-GAN-Eye-Inpainting-Tensorflow) | 35 | -| [Deep One-Class Classification](http://proceedings.mlr.press/v80/ruff18a.html) | ICML | [code](https://github.com/lukasruff/Deep-SVDD) | 34 | -| [Deep Regression Tracking with Shrinkage Loss](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiankai_Lu_Deep_Regression_Tracking_ECCV_2018_paper.html) | ECCV | [code](https://github.com/chaoma99/DSLT) | 34 | -| [Deflecting Adversarial Attacks With Pixel Deflection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Prakash_Deflecting_Adversarial_Attacks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/iamaaditya/pixel-deflection) | 34 | -| [Learning Visual Question Answering by Bootstrapping Hard Attention](http://openaccess.thecvf.com/content_ECCV_2018/html/Mateusz_Malinowski_Learning_Visual_Question_ECCV_2018_paper.html) | ECCV | [code](https://github.com/gnouhp/PyTorch-AdaHAN) | 33 | -| [Human-Centric Indoor Scene Synthesis Using Stochastic Grammar](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Human-Centric_Indoor_Scene_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/SiyuanQi/human-centric-scene-synthesis) | 33 | -| [Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Nguyen_Improved_Fusion_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/cvlab-tohoku/Dense-CoAttention-Network) | 33 | -| [CleanNet: Transfer Learning for Scalable Image Classifier Training With Label Noise](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_CleanNet_Transfer_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kuanghuei/clean-net) | 33 | -| [Speaker-Follower Models for Vision-and-Language Navigation](https://arxiv.org/abs/1806.02724) | NIPS | [code](https://github.com/ronghanghu/speaker_follower) | 33 | -| [Improving Shape Deformation in Unsupervised Image-to-Image Translation](http://openaccess.thecvf.com/content_ECCV_2018/html/Aaron_Gokaslan_Improving_Shape_Deformation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/brownvc/ganimorph) | 33 | -| [Learning Single-View 3D Reconstruction with Limited Pose Supervision](http://openaccess.thecvf.com/content_ECCV_2018/html/Guandao_Yang_A_Unified_Framework_ECCV_2018_paper.html) | ECCV | [code](https://github.com/stevenygd/3d-recon) | 33 | -| [3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data](https://arxiv.org/abs/1807.02547) | NIPS | [code](https://github.com/mariogeiger/se3cnn) | 33 | -| [Adversarial Logit Pairing](http://arxiv.org/abs/1803.06373v1) | NIPS | [code](https://github.com/labsix/adversarial-logit-pairing-analysis) | 32 | -| [Attention in Convolutional LSTM for Gesture Recognition](https://nips.cc/Conferences/2018/Schedule?showEvent=11207) | NIPS | [code](https://github.com/GuangmingZhu/AttentionConvLSTM) | 32 | -| [Graph-Cut RANSAC](http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/danini/graph-cut-ransac) | 32 | -| [Neural Guided Constraint Logic Programming for Program Synthesis](http://arxiv.org/abs/1809.02840v2) | NIPS | [code](https://github.com/xuexue/neuralkanren) | 32 | -| [Learning Dynamic Memory Networks for Object Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Tianyu_Yang_Learning_Dynamic_Memory_ECCV_2018_paper.html) | ECCV | [code](https://github.com/skyoung/MemTrack) | 32 | -| [GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints](http://openaccess.thecvf.com/content_ECCV_2018/html/Zixin_Luo_Learning_Local_Descriptors_ECCV_2018_paper.html) | ECCV | [code](https://github.com/lzx551402/geodesc) | 32 | -| [A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks](nan) | NIPS | [code](https://github.com/pokaxpoka/deep_Mahalanobis_detector) | 32 | -| [Flow-Grounded Spatial-Temporal Video Prediction from Still Images](http://openaccess.thecvf.com/content_ECCV_2018/html/Yijun_Li_Flow-Grounded_Spatial-Temporal_Video_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Yijunmaverick/FlowGrounded-VideoPrediction) | 32 | -| [Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Lei_Zhu_Bi-directional_Feature_Pyramid_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zijundeng/BDRAR) | 32 | -| [On the Robustness of Semantic Segmentation Models to Adversarial Attacks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Arnab_On_the_Robustness_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hmph/adversarial-attacks) | 31 | -| [Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cui_Large_Scale_Fine-Grained_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/richardaecn/cvpr18-inaturalist-transfer) | 31 | -| [SketchyScene: Richly-Annotated Scene Sketches](http://openaccess.thecvf.com/content_ECCV_2018/html/Changqing_Zou_SketchyScene_Richly-Annotated_Scene_ECCV_2018_paper.html) | ECCV | [code](https://github.com/SketchyScene/SketchyScene) | 31 | -| [Deep Randomized Ensembles for Metric Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Hong_Xuan_Randomized_Ensemble_Embeddings_ECCV_2018_paper.html) | ECCV | [code](https://github.com/littleredxh/DREML) | 30 | -| [Deep High Dynamic Range Imaging with Large Foreground Motions](http://openaccess.thecvf.com/content_ECCV_2018/html/Shangzhe_Wu_Deep_High_Dynamic_ECCV_2018_paper.html) | ECCV | [code](https://github.com/elliottwu/DeepHDR) | 30 | -| [Revisiting Video Saliency: A Large-Scale Benchmark and a New Model](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Revisiting_Video_Saliency_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wenguanwang/DHF1K) | 30 | -| [Blazingly Fast Video Object Segmentation With Pixel-Wise Metric Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Blazingly_Fast_Video_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yuhuayc/fast-vos) | 30 | -| [Deep Model-Based 6D Pose Refinement in RGB](http://openaccess.thecvf.com/content_ECCV_2018/html/Fabian_Manhardt_Deep_Model-Based_6D_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fabi92/eccv18-rgb_pose_refinement) | 30 | -| [TOM-Net: Learning Transparent Object Matting From a Single Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_TOM-Net_Learning_Transparent_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/guanyingc/TOM-Net) | 30 | -| [Quaternion Convolutional Neural Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Xuanyu_Zhu_Quaternion_Convolutional_Neural_ECCV_2018_paper.html) | ECCV | [code](https://github.com/TParcollet/Quaternion-Convolutional-Neural-Networks-for-End-to-End-Automatic-Speech-Recognition) | 30 | -| [Densely Connected Attention Propagation for Reading Comprehension](https://nips.cc/Conferences/2018/Schedule?showEvent=11481) | NIPS | [code](https://github.com/vanzytay/NIPS2018_DECAPROP) | 30 | -| [A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising](http://openaccess.thecvf.com/content_ECCV_2018/html/XU_JUN_A_Trilateral_Weighted_ECCV_2018_paper.html) | ECCV | [code](https://github.com/csjunxu/TWSC-ECCV2018) | 30 | -| [Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings](http://proceedings.mlr.press/v80/co-reyes18a.html) | ICML | [code](https://github.com/wyndwarrior/Sectar) | 29 | -| [Video Rain Streak Removal by Multiscale Convolutional Sparse Coding](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Video_Rain_Streak_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/MinghanLi/MS-CSC-Rain-Streak-Removal) | 29 | -| [Recurrent Scene Parsing With Perspective Understanding in the Loop](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kong_Recurrent_Scene_Parsing_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/aimerykong/Recurrent-Scene-Parsing-with-Perspective-Understanding-in-the-loop) | 29 | -| [Single Shot Scene Text Retrieval](http://openaccess.thecvf.com/content_ECCV_2018/html/Lluis_Gomez_Single_Shot_Scene_ECCV_2018_paper.html) | ECCV | [code](https://github.com/lluisgomez/single-shot-str) | 29 | -| [Toward Characteristic-Preserving Image-based Virtual Try-On Network](http://openaccess.thecvf.com/content_ECCV_2018/html/Bochao_Wang_Toward_Characteristic-Preserving_Image-based_ECCV_2018_paper.html) | ECCV | [code](https://github.com/sergeywong/cp-vton) | 29 | -| [Explainable Neural Computation via Stack Neural Module Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Ronghang_Hu_Explainable_Neural_Computation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ronghanghu/snmn) | 29 | -| [Exploring Disentangled Feature Representation Beyond Face Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Exploring_Disentangled_Feature_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sciencefans/D2AE-Face-Generator) | 29 | -| [Controllable Video Generation With Sparse Trajectories](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hao_Controllable_Video_Generation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zekunhao1995/ControllableVideoGen) | 28 | -| [Layer-structured 3D Scene Inference via View Synthesis](http://openaccess.thecvf.com/content_ECCV_2018/html/Shubham_Tulsiani_Layer-structured_3D_Scene_ECCV_2018_paper.html) | ECCV | [code](https://github.com/google/layered-scene-inference) | 28 | -| [Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Liang-Chieh_Chen_Encoder-Decoder_with_Atrous_ECCV_2018_paper.html) | ECCV | [code](https://github.com/qixuxiang/deeplabv3plus) | 28 | -| [PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_PiCANet_Learning_Pixel-Wise_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Ugness/PiCANet-Implementation) | 28 | -| [Learning Rich Features for Image Manipulation Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Learning_Rich_Features_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/LarryJiang134/Image_manipulation_detection) | 27 | -| [Fast Video Object Segmentation by Reference-Guided Mask Propagation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Oh_Fast_Video_Object_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/seoungwugoh/RGMP) | 27 | -| [3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration](http://openaccess.thecvf.com/content_ECCV_2018/html/Zi_Jian_Yew_3DFeat-Net_Weakly_Supervised_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yewzijian/3DFeatNet) | 27 | -| [Who Let the Dogs Out? Modeling Dog Behavior From Visual Data](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_Who_Let_the_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ehsanik/dogTorch) | 27 | -| [EC-Net: an Edge-aware Point set Consolidation Network](http://openaccess.thecvf.com/content_ECCV_2018/html/Lequan_Yu_EC-Net_an_Edge-aware_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yulequan/EC-Net) | 27 | -| [Interpretable Intuitive Physics Model](http://openaccess.thecvf.com/content_ECCV_2018/html/Tian_Ye_Interpretable_Intuitive_Physics_ECCV_2018_paper.html) | ECCV | [code](https://github.com/tianye95/interpretable-intuitive-physics-model) | 27 | -| [Learning a Discriminative Feature Network for Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Learning_a_Discriminative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lxtGH/dfn_seg) | 26 | -| [Partial Transfer Learning With Selective Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Partial_Transfer_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/thuml/SAN) | 26 | -| [Cross-Modal Deep Variational Hand Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Spurr_Cross-Modal_Deep_Variational_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/spurra/vae-hands-3d) | 26 | -| [Between-Class Learning for Image Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tokozume_Between-Class_Learning_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mil-tokyo/bc_learning_image) | 26 | -| [AON: Towards Arbitrarily-Oriented Text Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cheng_AON_Towards_Arbitrarily-Oriented_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/huizhang0110/AON) | 26 | -| [Conditional Image-to-Image Translation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Conditional_Image-to-Image_Translation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/znxlwm/pytorch-Conditional-image-to-image-translation) | 25 | -| [Learning Convolutional Networks for Content-Weighted Image Compression](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Convolutional_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/limuhit/ImageCompression) | 25 | -| [Diversity Regularized Spatiotemporal Attention for Video-Based Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Diversity_Regularized_Spatiotemporal_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ShuangLI59/Diversity-Regularized-Spatiotemporal-Attention) | 25 | -| [Dynamic Multimodal Instance Segmentation Guided by Natural Language Queries](http://openaccess.thecvf.com/content_ECCV_2018/html/Edgar_Margffoy-Tuay_Dynamic_Multimodal_Instance_ECCV_2018_paper.html) | ECCV | [code](https://github.com/BCV-Uniandes/query-objseg) | 25 | -| [CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Batsos_CBMV_A_Coalesced_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kbatsos/CBMV) | 25 | -| [Deep Texture Manifold for Ground Terrain Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xue_Deep_Texture_Manifold_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiaxue1993/Deep-Encoding-Pooling-Network-DEP-) | 25 | -| [Audio-Visual Event Localization in Unconstrained Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Yapeng_Tian_Audio-Visual_Event_Localization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YapengTian/AVE-ECCV18) | 25 | -| [First Order Generative Adversarial Networks](http://proceedings.mlr.press/v80/seward18a.html) | ICML | [code](https://github.com/zalandoresearch/first_order_gan) | 25 | -| [Visual Coreference Resolution in Visual Dialog using Neural Module Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Satwik_Kottur_Visual_Coreference_Resolution_ECCV_2018_paper.html) | ECCV | [code](https://github.com/facebookresearch/corefnmn) | 25 | -| [SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Faraone_SYQ_Learning_Symmetric_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/julianfaraone/SYQ) | 24 | -| [Deep Reinforcement Learning of Marked Temporal Point Processes](http://arxiv.org/abs/1805.09360v1) | NIPS | [code](https://github.com/Networks-Learning/tpprl) | 24 | -| [Explicit Inductive Bias for Transfer Learning with Convolutional Networks](http://proceedings.mlr.press/v80/li18a.html) | ICML | [code](https://github.com/holyseven/TransferLearningClassification) | 24 | -| [LEGO: Learning Edge With Geometry All at Once by Watching Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_LEGO_Learning_Edge_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhenheny/LEGO) | 24 | -| [Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes](http://openaccess.thecvf.com/content_ECCV_2018/html/Fangneng_Zhan_Verisimilar_Image_Synthesis_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fnzhan/Verisimilar-Image-Synthesis-for-Accurate-Detection-and-Recognition-of-Texts-in-Scenes) | 24 | -| [Multi-Agent Diverse Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ghosh_Multi-Agent_Diverse_Generative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/arnabgho/MADGAN) | 23 | -| [Face Aging With Identity-Preserved Conditional Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Face_Aging_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/dawei6875797/Face-Aging-with-Identity-Preserved-Conditional-Generative-Adversarial-Networks) | 23 | -| [Learning to Separate Object Sounds by Watching Unlabeled Video](http://openaccess.thecvf.com/content_ECCV_2018/html/Ruohan_Gao_Learning_to_Separate_ECCV_2018_paper.html) | ECCV | [code](https://github.com/rhgao/separating-object-sounds) | 23 | -| [Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search](http://proceedings.mlr.press/v80/suganuma18a.html) | ICML | [code](https://github.com/sg-nm/Evolutionary-Autoencoders) | 23 | -| [To Trust Or Not To Trust A Classifier](http://arxiv.org/abs/1805.11783v1) | NIPS | [code](https://github.com/google/TrustScore) | 23 | -| [Im2Flow: Motion Hallucination From Static Images for Action Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gao_Im2Flow_Motion_Hallucination_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rhgao/Im2Flow) | 22 | -| [ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_ISTA-Net_Interpretable_Optimization-Inspired_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jianzhangcs/ISTA-Net) | 22 | -| [Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Hallucinated-IQA_No-Reference_Image_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kwanyeelin/HIQA) | 22 | -| [Anonymous Walk Embeddings](http://proceedings.mlr.press/v80/ivanov18a.html) | ICML | [code](https://github.com/nd7141/AWE) | 22 | -| [Learning to Multitask](http://arxiv.org/abs/1805.07541v1) | NIPS | [code](https://github.com/jfutoma/MGP-RNN) | 22 | -| [CondenseNet: An Efficient DenseNet Using Learned Group Convolutions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_CondenseNet_An_Efficient_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/markdtw/condensenet-tensorflow) | 22 | -| [HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_HashGAN_Deep_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/thuml/HashGAN) | 22 | -| [Hierarchical Relational Networks for Group Activity Recognition and Retrieval](http://openaccess.thecvf.com/content_ECCV_2018/html/Mostafa_Ibrahim_Hierarchical_Relational_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/mostafa-saad/hierarchical-relational-network) | 22 | -| [Collaborative and Adversarial Network for Unsupervised Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Collaborative_and_Adversarial_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mahfuj9346449/iCAN) | 22 | -| [Geometry-Aware Scene Text Detection With Instance Transformation Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Geometry-Aware_Scene_Text_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zlmzju/itn) | 22 | -| [Learning to Promote Saliency Detectors](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zeng_Learning_to_Promote_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zengxianyu/lps) | 21 | -| [CSGNet: Neural Shape Parser for Constructive Solid Geometry](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sharma_CSGNet_Neural_Shape_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Hippogriff/CSGNet) | 21 | -| [Local Spectral Graph Convolution for Point Set Feature Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Chu_Wang_Local_Spectral_Graph_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fate3439/LocalSpecGCN) | 21 | -| [HiDDeN: Hiding Data with Deep Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Jiren_Zhu_HiDDeN_Hiding_Data_ECCV_2018_paper.html) | ECCV | [code](https://github.com/jirenz/HiDDeN) | 21 | -| [GraphBit: Bitwise Interaction Mining via Deep Reinforcement Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Duan_GraphBit_Bitwise_Interaction_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/duanyq14/GraphBit) | 20 | -| [Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Stacked_Conditional_Generative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/DeepInsight-PCALab/ST-CGAN) | 20 | -| [Fully-Convolutional Point Networks for Large-Scale Point Clouds](http://openaccess.thecvf.com/content_ECCV_2018/html/Dario_Rethage_Fully-Convolutional_Point_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/drethage/fully-convolutional-point-network) | 20 | -| [Learning Superpixels With Segmentation-Aware Affinity Loss](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tu_Learning_Superpixels_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wctu/SEAL) | 20 | -| [Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Zero-Shot_Visual_Recognition_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zjuchenlong/sp-aen.cvpr18) | 20 | -| [Crowd Counting With Deep Negative Correlation Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shi_Crowd_Counting_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/shizenglin/Deep-NCL) | 20 | -| [Dimensionality-Driven Learning with Noisy Labels](http://proceedings.mlr.press/v80/ma18d.html) | ICML | [code](https://github.com/xingjunm/dimensionality-driven-learning) | 20 | -| [Objects that Sound](http://openaccess.thecvf.com/content_ECCV_2018/html/Relja_Arandjelovic_Objects_that_Sound_ECCV_2018_paper.html) | ECCV | [code](https://github.com/rohitrango/objects-that-sound) | 20 | -| [Deep Expander Networks: Efficient Deep Networks from Graph Theory](http://openaccess.thecvf.com/content_ECCV_2018/html/Ameya_Prabhu_Deep_Expander_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/DrImpossible/Deep-Expander-Networks) | 19 | -| [Low-Shot Learning With Large-Scale Diffusion](http://openaccess.thecvf.com/content_cvpr_2018/papers/Douze_Low-Shot_Learning_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/low-shot-with-diffusion) | 19 | -| [Low-Shot Learning With Imprinted Weights](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Low-Shot_Learning_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/YU1ut/imprinted-weights) | 19 | -| [Cross-Domain Self-Supervised Multi-Task Feature Learning Using Synthetic Imagery](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ren_Cross-Domain_Self-Supervised_Multi-Task_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jason718/game-feature-learning) | 19 | -| [Learning Descriptor Networks for 3D Shape Synthesis and Analysis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xie_Learning_Descriptor_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jianwen-xie/3DDescriptorNet) | 19 | -| [Disentangling Factors of Variation with Cycle-Consistent Variational Auto-Encoders](http://openaccess.thecvf.com/content_ECCV_2018/html/Ananya_Harsh_Jha_Disentangling_Factors_of_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ananyahjha93/cycle-consistent-vae) | 19 | -| [CTAP: Complementary Temporal Action Proposal Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Jiyang_Gao_CTAP_Complementary_Temporal_ECCV_2018_paper.html) | ECCV | [code](https://github.com/jiyanggao/CTAP) | 18 | -| [DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors](http://arxiv.org/abs/1805.07445v3) | NIPS | [code](https://github.com/dojoteef/dvae) | 18 | -| [Conditional Image-Text Embedding Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Bryan_Plummer_Conditional_Image-Text_Embedding_ECCV_2018_paper.html) | ECCV | [code](https://github.com/BryanPlummer/cite) | 18 | -| [EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth From Light Field Images](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shin_EPINET_A_Fully-Convolutional_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chshin10/epinet) | 18 | -| [Glimpse Clouds: Human Activity Recognition From Unstructured Feature Points](http://openaccess.thecvf.com/content_cvpr_2018/papers/Baradel_Glimpse_Clouds_Human_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/fabienbaradel/glimpse_clouds) | 18 | -| [Bayesian Optimization of Combinatorial Structures](http://proceedings.mlr.press/v80/baptista18a.html) | ICML | [code](https://github.com/baptistar/BOCS) | 18 | -| [FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Verma_FeaStNet_Feature-Steered_Graph_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/nitika-verma/FeaStNet) | 18 | -| [Learning Type-Aware Embeddings for Fashion Compatibility](http://openaccess.thecvf.com/content_ECCV_2018/html/Mariya_Vasileva_Learning_Type-Aware_Embeddings_ECCV_2018_paper.html) | ECCV | [code](https://github.com/mvasil/fashion-compatibility) | 17 | -| [Sliced Wasserstein Distance for Learning Gaussian Mixture Models](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kolouri_Sliced_Wasserstein_Distance_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/skolouri/swgmm) | 17 | -| [Revisiting Deep Intrinsic Image Decompositions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Fan_Revisiting_Deep_Intrinsic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/fqnchina/IntrinsicImage) | 17 | -| [A Spectral Approach to Gradient Estimation for Implicit Distributions](http://proceedings.mlr.press/v80/shi18a.html) | ICML | [code](https://github.com/thjashin/spectral-stein-grad) | 17 | -| [Hierarchical Novelty Detection for Visual Object Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_Hierarchical_Novelty_Detection_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kibok90/cvpr2018-hnd) | 17 | -| [Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies](http://openaccess.thecvf.com/content_cvpr_2018/papers/Joo_Total_Capture_A_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Myzhencai/Total-Capture) | 17 | -| [Learning Generative ConvNets via Multi-Grid Modeling and Sampling](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gao_Learning_Generative_ConvNets_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ruiqigao/Multigrid_learning) | 17 | -| [Learning 3D Shape Completion From Laser Scan Data With Weak Supervision](http://openaccess.thecvf.com/content_cvpr_2018/papers/Stutz_Learning_3D_Shape_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/davidstutz/cvpr2018-shape-completion) | 17 | -| [Triplet Loss in Siamese Network for Object Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Xingping_Dong_Triplet_Loss_with_ECCV_2018_paper.html) | ECCV | [code](https://github.com/shenjianbing/TripletTracking) | 17 | -| [Adversarial Attack on Graph Structured Data](http://proceedings.mlr.press/v80/dai18b.html) | ICML | [code](https://github.com/Hanjun-Dai/graph_adversarial_attack) | 17 | -| [Arbitrary Style Transfer With Deep Feature Reshuffle](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gu_Arbitrary_Style_Transfer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/msracver/Style-Feature-Reshuffle) | 17 | -| [Visual Question Reasoning on General Dependency Tree](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Visual_Question_Reasoning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/bezorro/ACMN-Pytorch) | 17 | -| [Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition](http://openaccess.thecvf.com/content_ECCV_2018/html/Huang_Predicting_Gaze_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hyf015/egocentric-gaze-prediction) | 16 | -| [Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks](https://arxiv.org/abs/1802.04034) | NIPS | [code](https://github.com/ytsmiling/lmt) | 16 | -| [Coded Sparse Matrix Multiplication](http://proceedings.mlr.press/v80/wang18e.html) | ICML | [code](https://github.com/ksopyla/CudaDotProd) | 16 | -| [Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ding_Weakly-Supervised_Action_Segmentation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Zephyr-D/TCFPN-ISBA) | 16 | -| [Recovering 3D Planes from a Single Image via Convolutional Neural Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Fengting_Yang_Recovering_3D_Planes_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fuy34/planerecover) | 16 | -| [SegStereo: Exploiting Semantic Information for Disparity Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Guorun_Yang_SegStereo_Exploiting_Semantic_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yangguorun/SegStereo) | 16 | -| [Functional Gradient Boosting based on Residual Network Perception](http://proceedings.mlr.press/v80/nitanda18a.html) | ICML | [code](https://github.com/anitan0925/ResFGB) | 16 | -| [NAG: Network for Adversary Generation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mopuri_NAG_Network_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/val-iisc/nag) | 16 | -| [Generative Probabilistic Novelty Detection with Adversarial Autoencoders](http://arxiv.org/abs/1807.02588v1) | NIPS | [code](https://github.com/podgorskiy/GPND) | 16 | -| [Hashing as Tie-Aware Learning to Rank](http://openaccess.thecvf.com/content_cvpr_2018/papers/He_Hashing_as_Tie-Aware_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kunhe/TALR) | 15 | -| [Pose Proposal Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Sekii_Pose_Proposal_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/salihkaragoz/MultiPerson-pose-estimation) | 15 | -| [Convolutional Sequence to Sequence Model for Human Dynamics](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Convolutional_Sequence_to_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chaneyddtt/Convolutional-Sequence-to-Sequence-Model-for-Human-Dynamics) | 15 | -| [Joint Pose and Expression Modeling for Facial Expression Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Joint_Pose_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/FFZhang1231/Facial-expression-recognition) | 15 | -| [Grounding Referring Expressions in Images by Variational Context](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Grounding_Referring_Expressions_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yuleiniu/vc) | 15 | -| [Rethinking the Form of Latent States in Image Captioning](http://openaccess.thecvf.com/content_ECCV_2018/html/Bo_Dai_Rethinking_the_Form_ECCV_2018_paper.html) | ECCV | [code](https://github.com/doubledaibo/2dcaption_eccv2018) | 15 | -| [Open Set Domain Adaptation by Backpropagation](http://openaccess.thecvf.com/content_ECCV_2018/html/Kuniaki_Saito_Adversarial_Open_Set_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YU1ut/openset-DA) | 15 | -| [Neural Sign Language Translation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Camgoz_Neural_Sign_Language_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/neccam/nslt) | 15 | -| [SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters](http://openaccess.thecvf.com/content_ECCV_2018/html/Yifan_Xu_SpiderCNN_Deep_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/xyf513/SpiderCNN) | 15 | -| [Efficient Neural Audio Synthesis](http://proceedings.mlr.press/v80/kalchbrenner18a.html) | ICML | [code](https://github.com/fedden/TensorFlow-Efficient-Neural-Audio-Synthesis) | 15 | -| [Deep Learning Under Privileged Information Using Heteroscedastic Dropout](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lambert_Deep_Learning_Under_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/johnwlambert/dlupi-heteroscedastic-dropout) | 14 | -| [Image Transformer](http://proceedings.mlr.press/v80/parmar18a.html) | ICML | [code](https://github.com/ssingal05/ImageTransformer) | 14 | -| [Learning to Understand Image Blur](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Learning_to_Understand_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Lotuslisa/Understand_Image_Blur) | 14 | -| [Learning and Using the Arrow of Time](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wei_Learning_and_Using_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/donglaiw/AoT_TCAM) | 14 | -| [Action Sets: Weakly Supervised Action Segmentation Without Ordering Constraints](http://openaccess.thecvf.com/content_cvpr_2018/papers/Richard_Action_Sets_Weakly_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alexanderrichard/action-sets) | 14 | -| [Learning to Forecast and Refine Residual Motion for Image-to-Video Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Long_Zhao_Learning_to_Forecast_ECCV_2018_paper.html) | ECCV | [code](https://github.com/garyzhao/FRGAN) | 14 | -| [Multi-Scale Weighted Nuclear Norm Image Restoration](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yair_Multi-Scale_Weighted_Nuclear_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/noamyairTC/MSWNNM) | 14 | -| [Synthesizing Robust Adversarial Examples](http://proceedings.mlr.press/v80/athalye18b.html) | ICML | [code](https://github.com/prabhant/synthesizing-robust-adversarial-examples) | 13 | -| [Fine-Grained Visual Categorization using Meta-Learning Optimization with Sample Selection of Auxiliary Data](http://openaccess.thecvf.com/content_ECCV_2018/html/Yabin_Zhang_Fine-Grained_Visual_Categorization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YabinZhang1994/MetaFGNet) | 13 | -| [Assessing Generative Models via Precision and Recall](http://arxiv.org/abs/1806.00035v1) | NIPS | [code](https://github.com/msmsajjadi/precision-recall-distributions) | 13 | -| [Deep Diffeomorphic Transformer Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Detlefsen_Deep_Diffeomorphic_Transformer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/SkafteNicki/ddtn) | 13 | -| [Learning by Asking Questions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Misra_Learning_by_Asking_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yanghoonkim/question_generation) | 13 | -| [Towards Human-Machine Cooperation: Self-Supervised Sample Mining for Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Towards_Human-Machine_Cooperation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yanxp/SSM) | 13 | -| [Variational Autoencoders for Deforming 3D Mesh Models](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tan_Variational_Autoencoders_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/aldehydecho/Mesh-VAE) | 13 | -| [Min-Entropy Latent Model for Weakly Supervised Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wan_Min-Entropy_Latent_Model_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Winfrand/MELM) | 13 | -| [Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Anderson_Bottom-Up_and_Top-Down_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Wentong-DST/up-down-captioner) | 13 | -| [Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace](http://proceedings.mlr.press/v80/lee18a.html) | ICML | [code](https://github.com/yoonholee/MT-net) | 13 | -| [Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_a_Discriminative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hubeihubei/DFL-CNN-pytorch) | 13 | -| [Finding Influential Training Samples for Gradient Boosted Decision Trees](http://proceedings.mlr.press/v80/sharchilev18a.html) | ICML | [code](https://github.com/bsharchilev/influence_boosting) | 13 | -| [Gesture Recognition: Focus on the Hands](http://openaccess.thecvf.com/content_cvpr_2018/papers/Narayana_Gesture_Recognition_Focus_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/beckabec/HandDetection) | 12 | -| [Cross-View Image Synthesis Using Conditional GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Regmi_Cross-View_Image_Synthesis_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kregmi/cross-view-image-synthesis) | 12 | -| [Joint Optimization Framework for Learning With Noisy Labels](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tanaka_Joint_Optimization_Framework_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/DaikiTanaka-UT/JointOptimization) | 12 | -| [Future Person Localization in First-Person Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yagi_Future_Person_Localization_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/takumayagi/fpl) | 12 | -| [AutoLoc: Weakly-supervised Temporal Action Localization in Untrimmed Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Shou_AutoLoc_Weakly-supervised_Temporal_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zhengshou/AutoLoc) | 12 | -| [Learning Transferable Architectures for Scalable Image Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zoph_Learning_Transferable_Architectures_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/aussetg/nasnet.pytorch) | 12 | -| [Clipped Action Policy Gradient](http://proceedings.mlr.press/v80/fujita18a.html) | ICML | [code](https://github.com/pfnet-research/capg) | 12 | -| [Mix and Match Networks: Encoder-Decoder Alignment for Zero-Pair Image Translation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Mix_and_Match_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yaxingwang/Mix-and-match-networks) | 12 | -| [Decouple Learning for Parameterized Image Operators](http://openaccess.thecvf.com/content_ECCV_2018/html/Qingnan_Fan_Learning_to_Learn_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fqnchina/DecoupleLearning) | 12 | -| [Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction](http://proceedings.mlr.press/v80/qi18a.html) | ICML | [code](https://github.com/SiyuanQi/generalized-earley-parser) | 12 | -| [Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models](https://arxiv.org/abs/1808.04768) | NIPS | [code](https://github.com/neitzal/adaptive-skip-intervals) | 12 | -| [AMNet: Memorability Estimation With Attention](http://openaccess.thecvf.com/content_cvpr_2018/papers/Fajtl_AMNet_Memorability_Estimation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ok1zjf/AMNet) | 12 | -| [Adversarial Time-to-Event Modeling](http://proceedings.mlr.press/v80/chapfuwa18a.html) | ICML | [code](https://github.com/paidamoyo/adversarial_time_to_event) | 12 | -| [Reversible Recurrent Neural Networks](nan) | NIPS | [code](https://github.com/gan3sh500/revrnn) | 12 | -| [Human Pose Estimation With Parsing Induced Learner](http://openaccess.thecvf.com/content_cvpr_2018/papers/Nie_Human_Pose_Estimation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/NieXC/pytorch-pil) | 11 | -| [ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking](http://openaccess.thecvf.com/content_ECCV_2018/html/Oliver_Groth_ShapeStacks_Learning_Vision-Based_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ogroth/shapestacks) | 11 | -| [A Joint Sequence Fusion Model for Video Question Answering and Retrieval](http://openaccess.thecvf.com/content_ECCV_2018/html/Youngjae_Yu_A_Joint_Sequence_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yj-yu/lsmdc) | 11 | -| [Learning Face Age Progression: A Pyramid Architecture of GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Learning_Face_Age_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ajithvallabai/Pyramid-Architecture-of-GANs) | 11 | -| [Robust Physical-World Attacks on Deep Learning Visual Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Eykholt_Robust_Physical-World_Attacks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/evtimovi/robust_physical_perturbations) | 11 | -| [High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach](http://proceedings.mlr.press/v80/pearce18a.html) | ICML | [code](https://github.com/TeaPearce/Deep_Learning_Prediction_Intervals) | 11 | -| [Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory](http://proceedings.mlr.press/v80/amit18a.html) | ICML | [code](https://github.com/ron-amit/meta-learning-adjusting-priors) | 11 | -| [Multimodal Explanations: Justifying Decisions and Pointing to the Evidence](http://openaccess.thecvf.com/content_cvpr_2018/papers/Park_Multimodal_Explanations_Justifying_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Seth-Park/MultimodalExplanations) | 11 | -| [Accelerating Natural Gradient with Higher-Order Invariance](http://proceedings.mlr.press/v80/song18a.html) | ICML | [code](https://github.com/ermongroup/higher_order_invariance) | 11 | -| [Hierarchical Multi-Label Classification Networks](http://proceedings.mlr.press/v80/wehrmann18a.html) | ICML | [code](https://github.com/omoju/receiptdID) | 11 | -| [Convolutional Image Captioning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Aneja_Convolutional_Image_Captioning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/eladhoffer/captionGeneration.torch) | 11 | -| [Boosting Domain Adaptation by Discovering Latent Domains](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mancini_Boosting_Domain_Adaptation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mancinimassimiliano/latent_domains_DA) | 11 | -| [Logo Synthesis and Manipulation With Clustered Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sage_Logo_Synthesis_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alex-sage/logo-gen) | 10 | -| [PacGAN: The power of two samples in generative adversarial networks](http://arxiv.org/abs/1712.04086v2) | NIPS | [code](https://github.com/fjxmlzn/PacGAN) | 10 | -| [Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Long_Attention_Clusters_Purely_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/pomonam/AttentionCluster) | 10 | -| [End-to-End Incremental Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Francisco_M._Castro_End-to-End_Incremental_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fmcp/EndToEndIncrementalLearning) | 10 | -| [Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lyu_Multi-Oriented_Scene_Text_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JK-Rao/Corner_Segmentation_TextDetection) | 10 | -| [On GANs and GMMs](http://arxiv.org/abs/1805.12462v1) | NIPS | [code](https://github.com/eitanrich/gans-n-gmms) | 10 | -| [Salient Object Detection Driven by Fixation Prediction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Salient_Object_Detection_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wenguanwang/ASNet) | 9 | -| [Semantic Video Segmentation by Gated Recurrent Flow Propagation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Nilsson_Semantic_Video_Segmentation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/D-Nilsson/GRFP) | 9 | -| [Constraint-Aware Deep Neural Network Compression](http://openaccess.thecvf.com/content_ECCV_2018/html/Changan_Chen_Constraints_Matter_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ChanganVR/ConstraintAwareCompression) | 9 | -| [Statistically-motivated Second-order Pooling](http://openaccess.thecvf.com/content_ECCV_2018/html/Kaicheng_Yu_Statistically-motivated_Second-order_Pooling_ECCV_2018_paper.html) | ECCV | [code](https://github.com/kcyu2014/smsop) | 9 | -| [Excitation Backprop for RNNs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bargal_Excitation_Backprop_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sbargal/Caffe-ExcitationBP-RNNs) | 9 | -| [Analyzing Uncertainty in Neural Machine Translation](http://proceedings.mlr.press/v80/ott18a.html) | ICML | [code](https://github.com/facebookresearch/analyzing-uncertainty-nmt) | 9 | -| [Learning Dynamics of Linear Denoising Autoencoders](http://proceedings.mlr.press/v80/pretorius18a.html) | ICML | [code](https://github.com/arnupretorius/lindaedynamics_icml2018) | 9 | -| [Saliency Detection in 360° Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Ziheng_Zhang_Saliency_Detection_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/xuyanyu-shh/Saliency-detection-in-360-video) | 9 | -| [Density Adaptive Point Set Registration](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lawin_Density_Adaptive_Point_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/felja633/DARE) | 9 | -| [Decoupled Parallel Backpropagation with Convergence Guarantee](http://proceedings.mlr.press/v80/huo18a.html) | ICML | [code](https://github.com/slowbull/DDG) | 9 | -| [Classification from Pairwise Similarity and Unlabeled Data](http://proceedings.mlr.press/v80/bao18a.html) | ICML | [code](https://github.com/levelfour/SU_Classification) | 9 | -| [oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis](http://proceedings.mlr.press/v80/ainsworth18a.html) | ICML | [code](https://github.com/samuela/oi-vae) | 9 | -| [Modeling Sparse Deviations for Compressed Sensing using Generative Models](http://proceedings.mlr.press/v80/dhar18a.html) | ICML | [code](https://github.com/ermongroup/sparse_gen) | 9 | -| [Pixels, Voxels, and Views: A Study of Shape Representations for Single View 3D Object Shape Prediction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shin_Pixels_Voxels_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/daeyun/object-shapes-cvpr18) | 9 | -| [Towards Open-Set Identity Preserving Face Synthesis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bao_Towards_Open-Set_Identity_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chloeguoqing/Towards-Open-Set-Identity-Preserving-Face-Synthesis) | 9 | -| [Five-Point Fundamental Matrix Estimation for Uncalibrated Cameras](http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Five-Point_Fundamental_Matrix_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/danini/five-point-fundamental) | 8 | -| [BourGAN: Generative Networks with Metric Embeddings](https://arxiv.org/abs/1805.07674) | NIPS | [code](https://github.com/a554b554/BourGAN) | 8 | -| [Fast Information-theoretic Bayesian Optimisation](http://proceedings.mlr.press/v80/ru18a.html) | ICML | [code](https://github.com/rubinxin/FITBO) | 8 | -| [Deep Variational Reinforcement Learning for POMDPs](http://proceedings.mlr.press/v80/igl18a.html) | ICML | [code](https://github.com/oxwhirl/Deep-Variational-Reinforcement-Learning) | 8 | -| [Specular-to-Diffuse Translation for Multi-View Reconstruction](http://openaccess.thecvf.com/content_ECCV_2018/html/Shihao_Wu_Specular-to-Diffuse_Translation_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/wsh312/S2Dnet) | 8 | -| [Dynamic Conditional Networks for Few-Shot Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Fang_Zhao_Dynamic_Conditional_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ZhaoJ9014/Dynamic-Conditional-Networks-for-Few-Shot-Learning.pytorch) | 8 | -| [Learning Facial Action Units From Web Images With Scalable Weakly Supervised Clustering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhao_Learning_Facial_Action_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zkl20061823/WSC) | 8 | -| [High-Resolution Image Synthesis and Semantic Manipulation With Conditional GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_High-Resolution_Image_Synthesis_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chenxli/High-Resolution-Image-Synthesis-and-Semantic-Manipulation-with-Conditional-GANsl-) | 8 | -| [Deep Defense: Training DNNs with Improved Adversarial Robustness](http://arxiv.org/abs/1803.00404v2) | NIPS | [code](https://github.com/ZiangYan/deepdefense.pytorch) | 8 | -| [Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations](http://proceedings.mlr.press/v80/chen18g.html) | ICML | [code](https://github.com/chentingpc/kdcode-lm) | 8 | -| [Light Structure from Pin Motion: Simple and Accurate Point Light Calibration for Physics-based Modeling](http://openaccess.thecvf.com/content_ECCV_2018/html/Hiroaki_Santo_Light_Structure_from_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hiroaki-santo/light-structure-from-pin-motion) | 7 | -| [Non-metric Similarity Graphs for Maximum Inner Product Search](nan) | NIPS | [code](https://github.com/stanis-morozov/ip-nsw) | 7 | -| [Towards Realistic Predictors](http://openaccess.thecvf.com/content_ECCV_2018/html/Pei_Wang_Towards_Realistic_Predictors_ECCV_2018_paper.html) | ECCV | [code](https://github.com/peiwang062/towards-realistic-predictors) | 7 | -| [Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation](nan) | NIPS | [code](https://github.com/rwenqi/NBD-GLRA) | 7 | -| [Don’t Just Assume Look and Answer: Overcoming Priors for Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Agrawal_Dont_Just_Assume_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/AishwaryaAgrawal/GVQA) | 7 | -| [Learning Dual Convolutional Neural Networks for Low-Level Vision](http://openaccess.thecvf.com/content_cvpr_2018/papers/Pan_Learning_Dual_Convolutional_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/galad-loth/DualCNN-TF) | 7 | -| [The Mirage of Action-Dependent Baselines in Reinforcement Learning](http://proceedings.mlr.press/v80/tucker18a.html) | ICML | [code](https://github.com/brain-research/mirage-rl) | 7 | -| [DVQA: Understanding Data Visualizations via Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kafle_DVQA_Understanding_Data_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kushalkafle/DVQA_dataset) | 7 | -| [A Two-Step Disentanglement Method](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hadad_A_Two-Step_Disentanglement_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/naamahadad/A-Two-Step-Disentanglement-Method) | 7 | -| [Detecting and Correcting for Label Shift with Black Box Predictors](http://proceedings.mlr.press/v80/lipton18a.html) | ICML | [code](https://github.com/zackchase/label-shift) | 7 | -| [Conditional Prior Networks for Optical Flow](http://openaccess.thecvf.com/content_ECCV_2018/html/Yanchao_Yang_Conditional_Prior_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YanchaoYang/Conditional-Prior-Networks) | 7 | -| [Generative Adversarial Learning Towards Fast Weakly Supervised Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Generative_Adversarial_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/shenyunhang/GAL-fWSD) | 7 | -| [Adversarial Learning with Local Coordinate Coding](http://proceedings.mlr.press/v80/cao18a.html) | ICML | [code](https://github.com/guoyongcs/LCCGAN) | 7 | -| [Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kuen_Stochastic_Downsampling_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xternalz/SDPoint) | 7 | -| [AttnGAN: Fine-Grained Text to Image Generation With Attentional Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_AttnGAN_Fine-Grained_Text_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Wentong-DST/attn-gan) | 7 | -| [Learning to Explain: An Information-Theoretic Perspective on Model Interpretation](http://proceedings.mlr.press/v80/chen18j.html) | ICML | [code](https://github.com/nickvosk/acl2015-dataset-learning-to-explain-entity-relationships) | 7 | -| [Banach Wasserstein GAN](http://arxiv.org/abs/1806.06621v1) | NIPS | [code](https://github.com/adler-j/bwgan) | 7 | -| [Gradually Updated Neural Networks for Large-Scale Image Recognition](http://proceedings.mlr.press/v80/qiao18b.html) | ICML | [code](https://github.com/joe-siyuan-qiao/GUNN) | 7 | -| [Learning Steady-States of Iterative Algorithms over Graphs](http://proceedings.mlr.press/v80/dai18a.html) | ICML | [code](https://github.com/Hanjun-Dai/steady_state_embedding) | 7 | -| [Progressive Attention Guided Recurrent Network for Salient Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Progressive_Attention_Guided_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhangxiaoning666/PAGR) | 7 | -| [Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains](http://openaccess.thecvf.com/content_cvpr_2018/papers/Pang_Zoom_and_Learn_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Artifineuro/zole) | 6 | -| [Unsupervised holistic image generation from key local patches](http://openaccess.thecvf.com/content_ECCV_2018/html/Donghoon_Lee_Unsupervised_holistic_image_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hellbell/KeyPatchGan) | 6 | -| [Inner Space Preserving Generative Pose Machine](http://openaccess.thecvf.com/content_ECCV_2018/html/Shuangjun_Liu_Inner_Space_Preserving_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ostadabbas/isp-gpm) | 6 | -| [Bilevel Programming for Hyperparameter Optimization and Meta-Learning](http://proceedings.mlr.press/v80/franceschi18a.html) | ICML | [code](https://github.com/prolearner/hyper-representation) | 6 | -| [Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_Optical_Flow_Guided_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kitsune999/Optical-Flow-Guided-Feature) | 6 | -| [Breaking the Activation Function Bottleneck through Adaptive Parameterization](https://arxiv.org/abs/1805.08574) | NIPS | [code](https://github.com/flennerhag/alstm) | 6 | -| [Ultra Large-Scale Feature Selection using Count-Sketches](http://proceedings.mlr.press/v80/aghazadeh18a.html) | ICML | [code](https://github.com/rdspring1/MISSION) | 6 | -| [Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Dynamic_Scene_Deblurring_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhjwustc/cvpr18_rnn_deblur_matcaffe) | 6 | -| [Orthogonally Decoupled Variational Gaussian Processes](http://arxiv.org/abs/1809.08820v1) | NIPS | [code](https://github.com/hughsalimbeni/orth_decoupled_var_gps) | 6 | -| [Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design](http://proceedings.mlr.press/v80/lyu18a.html) | ICML | [code](https://github.com/Alaya-in-Matrix/MACE) | 6 | -| [A Modulation Module for Multi-task Learning with Applications in Image Retrieval](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiangyun_Zhao_A_Modulation_Module_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Zhaoxiangyun/Multi-Task-Modulation-Module) | 6 | -| [A Memory Network Approach for Story-Based Temporal Summarization of 360° Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_A_Memory_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sangho-vision/PFMN) | 6 | -| [Towards Effective Low-Bitwidth Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhuang_Towards_Effective_Low-Bitwidth_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/nowgood/QuantizeCNNModel) | 5 | -| [Disentangling Factors of Variation by Mixing Them](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Disentangling_Factors_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/HuQyang/Disentangling-Factors-of-Variation-by-Mixing-Them) | 5 | -| [Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web Prior](http://openaccess.thecvf.com/content_ECCV_2018/html/Sijia_Cai_Weakly-supervised_Video_Summarization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/cssjcai/vesd) | 5 | -| [Learning Longer-term Dependencies in RNNs with Auxiliary Losses](http://proceedings.mlr.press/v80/trinh18a.html) | ICML | [code](https://github.com/belepi93/rnn-auxiliary-loss) | 5 | -| [Contour Knowledge Transfer for Salient Object Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Xin_Li_Contour_Knowledge_Transfer_ECCV_2018_paper.html) | ECCV | [code](https://github.com/lixin666/C2SNet) | 5 | -| [HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Thomas_Robert_HybridNet_Classification_and_ECCV_2018_paper.html) | ECCV | [code](https://github.com/dakshitagrawal97/HybridNet) | 5 | -| [Sidekick Policy Learning for Active Visual Exploration](http://openaccess.thecvf.com/content_ECCV_2018/html/Santhosh_Kumar_Ramakrishnan_Sidekick_Policy_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/srama2512/sidekicks) | 5 | -| [Learning to Localize Sound Source in Visual Scenes](http://openaccess.thecvf.com/content_cvpr_2018/papers/Senocak_Learning_to_Localize_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ardasnck/learning_to_localize_sound) | 5 | -| [Neural Architecture Optimization](http://arxiv.org/abs/1808.07233v3) | NIPS | [code](https://github.com/dicarlolab/archconvnets) | 5 | -| [COLA: Decentralized Linear Learning](nan) | NIPS | [code](https://github.com/epfml/cola) | 5 | -| [Diverse and Coherent Paragraph Generation from Images](http://openaccess.thecvf.com/content_ECCV_2018/html/Moitreya_Chatterjee_Diverse_and_Coherent_ECCV_2018_paper.html) | ECCV | [code](https://github.com/metro-smiles/CapG_RevG_Code) | 5 | -| [DRACO: Byzantine-resilient Distributed Training via Redundant Gradients](http://proceedings.mlr.press/v80/chen18l.html) | ICML | [code](https://github.com/hwang595/Draco) | 5 | -| [Inter and Intra Topic Structure Learning with Word Embeddings](http://proceedings.mlr.press/v80/zhao18a.html) | ICML | [code](https://github.com/ethanhezhao/WEDTM) | 5 | -| [Estimating the Success of Unsupervised Image to Image Translation](http://openaccess.thecvf.com/content_ECCV_2018/html/Lior_Wolf_Estimating_the_Success_ECCV_2018_paper.html) | ECCV | [code](https://github.com/sagiebenaim/gan_bound) | 5 | -| [Dynamic-Structured Semantic Propagation Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liang_Dynamic-Structured_Semantic_Propagation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/limberc/DSSPN) | 5 | -| [The Description Length of Deep Learning models](https://arxiv.org/abs/1802.07044) | NIPS | [code](https://github.com/leonardblier/descriptionlengthdeeplearning) | 5 | -| [Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving](http://openaccess.thecvf.com/content_ECCV_2018/html/Peiliang_LI_Stereo_Vision-based_Semantic_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zhanghanduo/stereo_semantic_mapping) | 5 | -| [Blind Justice: Fairness with Encrypted Sensitive Attributes](http://proceedings.mlr.press/v80/kilbertus18a.html) | ICML | [code](https://github.com/nikikilbertus/blind-justice) | 5 | -| [Transfer Learning via Learning to Transfer](http://proceedings.mlr.press/v80/wei18a.html) | ICML | [code](https://github.com/QuebecAI/webcam-transfer-learning-v1) | 5 | -| [Deepcode: Feedback Codes via Deep Learning](http://arxiv.org/abs/1807.00801v1) | NIPS | [code](https://github.com/hyejikim1/Deepcode) | 4 | -| [Configurable Markov Decision Processes](http://proceedings.mlr.press/v80/metelli18a.html) | ICML | [code](https://github.com/albertometelli/Configurable-Markov-Decision-Processes-ICML-2018) | 4 | -| [A Framework for Evaluating 6-DOF Object Trackers](http://openaccess.thecvf.com/content_ECCV_2018/html/Mathieu_Garon_A_Framework_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/lvsn/6DOF_tracking_evaluation) | 4 | -| [Differentially Private Database Release via Kernel Mean Embeddings](http://proceedings.mlr.press/v80/balog18a.html) | ICML | [code](https://github.com/matejbalog/RKHS-private-database) | 4 | -| [Recognizing Human Actions as the Evolution of Pose Estimation Maps](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Recognizing_Human_Actions_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/nkliuyifang/Skeleton-based-Human-Action-Recognition) | 4 | -| [Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images](http://openaccess.thecvf.com/content_cvpr_2018/papers/Orekondy_Connecting_Pixels_to_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tribhuvanesh/visual_redactions) | 4 | -| [DeLS-3D: Deep Localization and Segmentation With a 3D Semantic Map](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_DeLS-3D_Deep_Localization_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/pengwangucla/DeLS-3D) | 4 | -| [Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification](http://openaccess.thecvf.com/content_ECCV_2018/html/Eric_Muller-Budack_Geolocation_Estimation_of_ECCV_2018_paper.html) | ECCV | [code](https://github.com/TIBHannover/GeoEstimation) | 4 | -| [Tracking Emerges by Colorizing Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Carl_Vondrick_Self-supervised_Tracking_by_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Oh-Yoojin/Tracking-Emerges-by-Colorizing-Videos) | 4 | -| [Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes](http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_He_Diverse_Conditional_Image_ECCV_2018_paper.html) | ECCV | [code](https://github.com/SSAW14/Image_Generation_with_Latent_Code) | 4 | -| [Inference Suboptimality in Variational Autoencoders](http://proceedings.mlr.press/v80/cremer18a.html) | ICML | [code](https://github.com/lxuechen/inference-suboptimality) | 4 | -| [Black Box FDR](http://proceedings.mlr.press/v80/tansey18a.html) | ICML | [code](https://github.com/tansey/bb-fdr) | 4 | -| [Feedback-Prop: Convolutional Neural Network Inference Under Partial Evidence](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Feedback-Prop_Convolutional_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/uvavision/feedbackprop) | 4 | -| [Quadrature-based features for kernel approximation](http://arxiv.org/abs/1802.03832v3) | NIPS | [code](https://github.com/quffka/quffka) | 4 | -| [Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Yingjie_Yao_Joint_Representation_and_ECCV_2018_paper.html) | ECCV | [code](https://github.com/tourmaline612/RTINet) | 4 | -| [Transferable Adversarial Perturbations](http://openaccess.thecvf.com/content_ECCV_2018/html/Bruce_Hou_Transferable_Adversarial_Perturbations_ECCV_2018_paper.html) | ECCV | [code](https://github.com/vinayprabhu/Gainsboro-box-attacks-) | 4 | -| [Single Image Water Hazard Detection using FCN with Reflection Attention Units](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaofeng_Han_Single_Image_Water_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Cow911/SingleImageWaterHazardDetectionWithRAU) | 4 | -| [Multimodal Generative Models for Scalable Weakly-Supervised Learning](http://arxiv.org/abs/1802.05335v2) | NIPS | [code](https://github.com/mhw32/multimodal-vae-public) | 4 | -| [Importance Weighted Transfer of Samples in Reinforcement Learning](http://proceedings.mlr.press/v80/tirinzoni18a.html) | ICML | [code](https://github.com/AndreaTirinzoni/iw-transfer-rl) | 3 | -| [Feature Generating Networks for Zero-Shot Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xian_Feature_Generating_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/akku1506/Feature-Generating-Networks-for-ZSL) | 3 | -| [DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding](http://proceedings.mlr.press/v80/moreau18a.html) | ICML | [code](https://github.com/tomMoral/Dicod) | 3 | -| [CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces](nan) | NIPS | [code](https://github.com/maple-research-lab/CapProNet) | 3 | -| [Bidirectional Retrieval Made Simple](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wehrmann_Bidirectional_Retrieval_Made_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jwehrmann/chain-vse) | 3 | -| [Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages](nan) | NIPS | [code](https://github.com/forest-snow/mtanchor_demo) | 3 | -| [A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liang_A_Hybrid_l1-l0_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/csjunxu/L1L0_TM-CVPR2018) | 3 | -| [Spatially-Adaptive Filter Units for Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tabernik_Spatially-Adaptive_Filter_Units_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/skokec/DAU-ConvNet) | 3 | -| [Learning to Branch](http://proceedings.mlr.press/v80/balcan18a.html) | ICML | [code](https://github.com/StoneyJackson/github-workflow-activity) | 3 | -| [Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives](nan) | NIPS | [code](https://github.com/IBM/Contrastive-Explanation-Method) | 3 | -| [Lifelong Learning via Progressive Distillation and Retrospection](http://openaccess.thecvf.com/content_ECCV_2018/html/Saihui_Hou_Progressive_Lifelong_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hshustc/ECCV18_Lifelong_Learning) | 3 | -| [CLEAR: Cumulative LEARning for One-Shot One-Class Image Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kozerawski_CLEAR_Cumulative_LEARning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JKozerawski/CLEAR-osoc) | 3 | -| [Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care](http://proceedings.mlr.press/v80/schwab18a.html) | ICML | [code](https://github.com/d909b/DSMT-Nets) | 3 | -| [Learning Answer Embeddings for Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Learning_Answer_Embeddings_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hexiang-hu/answer_embedding) | 3 | -| [Information Constraints on Auto-Encoding Variational Bayes](http://arxiv.org/abs/1805.08672v2) | NIPS | [code](https://github.com/romain-lopez/HCV) | 3 | -| [Parallel Bayesian Network Structure Learning](http://proceedings.mlr.press/v80/gao18b.html) | ICML | [code](https://github.com/bign8/PyStruct) | 3 | -| [Ring Loss: Convex Feature Normalization for Face Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zheng_Ring_Loss_Convex_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/vsatyakumar/Ring-Loss-Keras) | 3 | -| [Teaching Categories to Human Learners With Visual Explanations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Aodha_Teaching_Categories_to_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/macaodha/explain_teach) | 3 | -| [Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization](http://proceedings.mlr.press/v80/zhang18g.html) | ICML | [code](https://github.com/zhangjiong724/spectral-RNN) | 3 | -| [Deep Burst Denoising](http://openaccess.thecvf.com/content_ECCV_2018/html/Clement_Godard_Deep_Burst_Denoising_ECCV_2018_paper.html) | ECCV | [code](https://github.com/mrharicot/deep_burst_denoising) | 3 | -| [Convergent Tree Backup and Retrace with Function Approximation](http://proceedings.mlr.press/v80/touati18a.html) | ICML | [code](https://github.com/ahmed-touati/convergent-off-policy) | 3 | -| [Gaze Prediction in Dynamic 360° Immersive Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Gaze_Prediction_in_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xuyanyu-shh/VR-EyeTracking) | 3 | -| [Statistical Recurrent Models on Manifold valued Data](http://arxiv.org/abs/1805.11204v1) | NIPS | [code](https://github.com/zhenxingjian/SPD-SRU) | 3 | -| [End-to-End Flow Correlation Tracking With Spatial-Temporal Attention](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhu_End-to-End_Flow_Correlation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhengzhugithub/FlowTrack) | 3 | +| [Video-to-Video Synthesis](https://arxiv.org/abs/1808.06601) | NIPS | [code](https://github.com/NVIDIA/vid2vid) | 5578 | +| [Deep Image Prior](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ulyanov_Deep_Image_Prior_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/DmitryUlyanov/deep-image-prior) | 3736 | +| [StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_StarGAN_Unified_Generative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yunjey/StarGAN) | 3405 | +| [Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network](http://openaccess.thecvf.com/content_ECCV_2018/html/Yao_Feng_Joint_3D_Face_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YadiraF/PRNet) | 2434 | +| [Learning to See in the Dark](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Learning_to_See_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/cchen156/Learning-to-See-in-the-Dark) | 2326 | +| [Glow: Generative Flow with Invertible 1x1 Convolutions](http://arxiv.org/abs/1807.03039v2) | NIPS | [code](https://github.com/openai/glow) | 2088 | +| [Squeeze-and-Excitation Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hujie-frank/SENet) | 1477 | +| [Efficient Neural Architecture Search via Parameters Sharing](http://proceedings.mlr.press/v80/pham18a.html) | ICML | [code](https://github.com/carpedm20/ENAS-pytorch) | 1382 | +| [Multimodal Unsupervised Image-to-image Translation](http://openaccess.thecvf.com/content_ECCV_2018/html/Xun_Huang_Multimodal_Unsupervised_Image-to-image_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NVlabs/MUNIT) | 1296 | +| [Non-Local Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Non-Local_Neural_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/video-nonlocal-net) | 992 | +| [Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hara_Can_Spatiotemporal_3D_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kenshohara/3D-ResNets-PyTorch) | 924 | +| [Single-Shot Refinement Neural Network for Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Single-Shot_Refinement_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sfzhang15/RefineDet) | 875 | +| [Image Generation From Scene Graphs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Johnson_Image_Generation_From_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/google/sg2im) | 851 | +| [GANimation: Anatomically-aware Facial Animation from a Single Image](http://openaccess.thecvf.com/content_ECCV_2018/html/Albert_Pumarola_Anatomically_Coherent_Facial_ECCV_2018_paper.html) | ECCV | [code](https://github.com/albertpumarola/GANimation) | 772 | +| [Simple Baselines for Human Pose Estimation and Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Bin_Xiao_Simple_Baselines_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Microsoft/human-pose-estimation.pytorch) | 752 | +| [Visualizing the Loss Landscape of Neural Nets](http://arxiv.org/abs/1712.09913v2) | NIPS | [code](https://github.com/tomgoldstein/loss-landscape) | 724 | +| [Detect-and-Track: Efficient Pose Estimation in Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Girdhar_Detect-and-Track_Efficient_Pose_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/DetectAndTrack) | 650 | +| [Relation Networks for Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Relation_Networks_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/msracver/Relation-Networks-for-Object-Detection) | 635 | +| [Generative Image Inpainting With Contextual Attention](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Generative_Image_Inpainting_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JiahuiYu/generative_inpainting) | 609 | +| [PointCNN](http://arxiv.org/abs/1801.07791v3) | NIPS | [code](https://github.com/yangyanli/PointCNN) | 607 | +| [Look at Boundary: A Boundary-Aware Face Alignment Algorithm](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Look_at_Boundary_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wywu/LAB) | 575 | +| [Pelee: A Real-Time Object Detection System on Mobile Devices](nan) | NIPS | [code](https://github.com/Robert-JunWang/Pelee) | 548 | +| [Distractor-aware Siamese Networks for Visual Object Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Zhu_Distractor-aware_Siamese_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/foolwood/DaSiamRPN) | 545 | +| [Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples](http://proceedings.mlr.press/v80/athalye18a.html) | ICML | [code](https://github.com/anishathalye/obfuscated-gradients) | 535 | +| [Which Training Methods for GANs do actually Converge?](http://proceedings.mlr.press/v80/mescheder18a.html) | ICML | [code](https://github.com/LMescheder/GAN_stability) | 520 | +| [End-to-End Recovery of Human Shape and Pose](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kanazawa_End-to-End_Recovery_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/akanazawa/hmr) | 502 | +| [Taskonomy: Disentangling Task Transfer Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zamir_Taskonomy_Disentangling_Task_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/StanfordVL/taskonomy) | 502 | +| [Cascaded Pyramid Network for Multi-Person Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Cascaded_Pyramid_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chenyilun95/tf-cpn) | 497 | +| [Neural 3D Mesh Renderer](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kato_Neural_3D_Mesh_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hiroharu-kato/neural_renderer) | 489 | +| [Zero-Shot Recognition via Semantic Embeddings and Knowledge Graphs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Zero-Shot_Recognition_via_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JudyYe/zero-shot-gcn) | 489 | +| [In-Place Activated BatchNorm for Memory-Optimized Training of DNNs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bulo_In-Place_Activated_BatchNorm_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mapillary/inplace_abn) | 485 | +| [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_The_Unreasonable_Effectiveness_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/richzhang/PerceptualSimilarity) | 447 | +| [Frustum PointNets for 3D Object Detection From RGB-D Data](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Frustum_PointNets_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/charlesq34/frustum-pointnets) | 434 | +| [The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Berman_The_LovaSz-Softmax_Loss_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/bermanmaxim/LovaszSoftmax) | 416 | +| [ICNet for Real-Time Semantic Segmentation on High-Resolution Images](http://openaccess.thecvf.com/content_ECCV_2018/html/Hengshuang_Zhao_ICNet_for_Real-Time_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hszhao/ICNet) | 415 | +| [PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_PWC-Net_CNNs_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/NVlabs/PWC-Net) | 398 | +| [Efficient Interactive Annotation of Segmentation Datasets With Polygon-RNN++](http://openaccess.thecvf.com/content_cvpr_2018/papers/Acuna_Efficient_Interactive_Annotation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/fidler-lab/polyrnn-pp-pytorch) | 397 | +| [Gibson Env: Real-World Perception for Embodied Agents](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xia_Gibson_Env_Real-World_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/StanfordVL/GibsonEnv) | 385 | +| [Acquisition of Localization Confidence for Accurate Object Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Borui_Jiang_Acquisition_of_Localization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/vacancy/PreciseRoIPooling) | 384 | +| [Noise2Noise: Learning Image Restoration without Clean Data](http://proceedings.mlr.press/v80/lehtinen18a.html) | ICML | [code](https://github.com/yu4u/noise2noise) | 370 | +| [GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_GeoNet_Geometric_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yzcjtr/GeoNet) | 359 | +| [GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yin_GeoNet_Unsupervised_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yzcjtr/GeoNet) | 359 | +| [A Style-Aware Content Loss for Real-time HD Style Transfer](http://openaccess.thecvf.com/content_ECCV_2018/html/Artsiom_Sanakoyeu_A_Style-aware_Content_ECCV_2018_paper.html) | ECCV | [code](https://github.com/CompVis/adaptive-style-transfer) | 349 | +| [Soccer on Your Tabletop](http://openaccess.thecvf.com/content_cvpr_2018/papers/Rematas_Soccer_on_Your_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/krematas/soccerontable) | 338 | +| [Pyramid Stereo Matching Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chang_Pyramid_Stereo_Matching_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JiaRenChang/PSMNet) | 335 | +| [Neural Baby Talk](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lu_Neural_Baby_Talk_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiasenlu/NeuralBabyTalk) | 332 | +| [License Plate Detection and Recognition in Unconstrained Scenarios](http://openaccess.thecvf.com/content_ECCV_2018/html/Sergio_Silva_License_Plate_Detection_ECCV_2018_paper.html) | ECCV | [code](https://github.com/sergiomsilva/alpr-unconstrained) | 326 | +| [Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors](http://openaccess.thecvf.com/content_cvpr_2018/papers/Dong_Supervision-by-Registration_An_Unsupervised_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/supervision-by-registration) | 326 | +| [Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images](http://openaccess.thecvf.com/content_ECCV_2018/html/Nanyang_Wang_Pixel2Mesh_Generating_3D_ECCV_2018_paper.html) | ECCV | [code](https://github.com/nywang16/Pixel2Mesh) | 323 | +| [Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mascharka_Transparency_by_Design_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/davidmascharka/tbd-nets) | 317 | +| [Fast End-to-End Trainable Guided Filter](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Fast_End-to-End_Trainable_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wuhuikai/DeepGuidedFilter) | 312 | +| [Deep Clustering for Unsupervised Learning of Visual Features](http://openaccess.thecvf.com/content_ECCV_2018/html/Mathilde_Caron_Deep_Clustering_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/facebookresearch/deepcluster) | 302 | +| [Deep Photo Enhancer: Unpaired Learning for Image Enhancement From Photographs With GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Deep_Photo_Enhancer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/nothinglo/Deep-Photo-Enhancer) | 294 | +| [Neural Relational Inference for Interacting Systems](http://proceedings.mlr.press/v80/kipf18a.html) | ICML | [code](https://github.com/ethanfetaya/NRI) | 289 | +| [Adversarially Regularized Autoencoders](http://proceedings.mlr.press/v80/zhao18b.html) | ICML | [code](https://github.com/jakezhaojb/ARAE) | 282 | +| [Learning to Adapt Structured Output Space for Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tsai_Learning_to_Adapt_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wasidennis/AdaptSegNet) | 280 | +| [Convolutional Neural Networks With Alternately Updated Clique](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Convolutional_Neural_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/iboing/CliqueNet) | 272 | +| [Learning to Segment Every Thing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Learning_to_Segment_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ronghanghu/seg_every_thing) | 269 | +| [Supervising Unsupervised Learning](http://arxiv.org/abs/1709.05262v2) | NIPS | [code](https://github.com/quinnliu/machineLearning) | 262 | +| [LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hui_LiteFlowNet_A_Lightweight_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/twhui/LiteFlowNet) | 261 | +| [Bilinear Attention Networks](http://arxiv.org/abs/1805.07932v1) | NIPS | [code](https://github.com/jnhwkim/ban-vqa) | 258 | +| [ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Sachin_Mehta_ESPNet_Efficient_Spatial_ECCV_2018_paper.html) | ECCV | [code](https://github.com/sacmehta/ESPNet) | 254 | +| [An intriguing failing of convolutional neural networks and the CoordConv solution](https://arxiv.org/abs/1807.03247) | NIPS | [code](https://github.com/mkocabas/CoordConv-pytorch) | 249 | +| [End-to-End Learning of Motion Representation for Video Understanding](http://openaccess.thecvf.com/content_cvpr_2018/papers/Fan_End-to-End_Learning_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/LijieFan/tvnet) | 238 | +| [Image Super-Resolution Using Very Deep Residual Channel Attention Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Yulun_Zhang_Image_Super-Resolution_Using_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yulunzhang/RCAN) | 234 | +| [Iterative Visual Reasoning Beyond Convolutions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Iterative_Visual_Reasoning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/endernewton/iter-reason) | 228 | +| [Semi-Parametric Image Synthesis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Semi-Parametric_Image_Synthesis_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xjqicuhk/SIMS) | 226 | +| [Compressed Video Action Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Compressed_Video_Action_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chaoyuaw/pytorch-coviar) | 225 | +| [Style Aggregated Network for Facial Landmark Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Dong_Style_Aggregated_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/D-X-Y/SAN) | 223 | +| [Pose-Robust Face Recognition via Deep Residual Equivariant Mapping](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Pose-Robust_Face_Recognition_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/penincillin/DREAM) | 220 | +| [Multi-Content GAN for Few-Shot Font Style Transfer](http://openaccess.thecvf.com/content_cvpr_2018/papers/Azadi_Multi-Content_GAN_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/azadis/MC-GAN) | 218 | +| [GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models](http://proceedings.mlr.press/v80/you18a.html) | ICML | [code](https://github.com/JiaxuanYou/graph-generation) | 214 | +| [Referring Relationships](http://openaccess.thecvf.com/content_cvpr_2018/papers/Krishna_Referring_Relationships_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/StanfordVL/ReferringRelationships) | 210 | +| [MoCoGAN: Decomposing Motion and Content for Video Generation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulyakov_MoCoGAN_Decomposing_Motion_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sergeytulyakov/mocogan) | 205 | +| [Latent Alignment and Variational Attention](http://arxiv.org/abs/1807.03756v1) | NIPS | [code](https://github.com/harvardnlp/var-attn) | 204 | +| [LayoutNet: Reconstructing the 3D Room Layout From a Single RGB Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zou_LayoutNet_Reconstructing_the_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zouchuhang/LayoutNet) | 202 | +| [Large-Scale Point Cloud Semantic Segmentation With Superpoint Graphs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Landrieu_Large-Scale_Point_Cloud_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/loicland/superpoint_graph) | 197 | +| [An End-to-End TextSpotter With Explicit Alignment and Attention](http://openaccess.thecvf.com/content_cvpr_2018/papers/He_An_End-to-End_TextSpotter_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tonghe90/textspotter) | 195 | +| [DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kupyn_DeblurGAN_Blind_Motion_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/RaphaelMeudec/deblur-gan) | 189 | +| [SPLATNet: Sparse Lattice Networks for Point Cloud Processing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Su_SPLATNet_Sparse_Lattice_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/NVlabs/splatnet) | 188 | +| [Attentive Generative Adversarial Network for Raindrop Removal From a Single Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qian_Attentive_Generative_Adversarial_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rui1996/DeRaindrop) | 186 | +| [Single View Stereo Matching](http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_Single_View_Stereo_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lawy623/SVS) | 182 | +| [MegaDepth: Learning Single-View Depth Prediction From Internet Photos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_MegaDepth_Learning_Single-View_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lixx2938/MegaDepth) | 181 | +| [ECO: Efficient Convolutional Network for Online Video Understanding](http://openaccess.thecvf.com/content_ECCV_2018/html/Mohammadreza_Zolfaghari_ECO_Efficient_Convolutional_ECCV_2018_paper.html) | ECCV | [code](https://github.com/mzolfaghari/ECO-efficient-video-understanding) | 180 | +| [Unsupervised Feature Learning via Non-Parametric Instance Discrimination](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Unsupervised_Feature_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhirongw/lemniscate.pytorch) | 180 | +| [ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_ST-GAN_Spatial_Transformer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chenhsuanlin/spatial-transformer-GAN) | 179 | +| [Video Based Reconstruction of 3D People Models](http://openaccess.thecvf.com/content_cvpr_2018/papers/Alldieck_Video_Based_Reconstruction_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/thmoa/videoavatars) | 179 | +| [Social GAN: Socially Acceptable Trajectories With Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gupta_Social_GAN_Socially_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/agrimgupta92/sgan) | 178 | +| [Learning Category-Specific Mesh Reconstruction from Image Collections](http://openaccess.thecvf.com/content_ECCV_2018/html/Angjoo_Kanazawa_Learning_Category-Specific_Mesh_ECCV_2018_paper.html) | ECCV | [code](https://github.com/akanazawa/cmr) | 176 | +| [Realistic Evaluation of Deep Semi-Supervised Learning Algorithms](http://arxiv.org/abs/1804.09170v2) | NIPS | [code](https://github.com/brain-research/realistic-ssl-evaluation) | 175 | +| [BSN: Boundary Sensitive Network for Temporal Action Proposal Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Tianwei_Lin_BSN_Boundary_Sensitive_ECCV_2018_paper.html) | ECCV | [code](https://github.com/wzmsltw/BSN-boundary-sensitive-network) | 175 | +| [Group Normalization](http://openaccess.thecvf.com/content_ECCV_2018/html/Yuxin_Wu_Group_Normalization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/shaohua0116/Group-Normalization-Tensorflow) | 175 | +| [Real-Time Seamless Single Shot 6D Object Pose Prediction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tekin_Real-Time_Seamless_Single_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Microsoft/singleshotpose) | 174 | +| [MVSNet: Depth Inference for Unstructured Multi-view Stereo](http://openaccess.thecvf.com/content_ECCV_2018/html/Yao_Yao_MVSNet_Depth_Inference_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YoYo000/MVSNet) | 174 | +| [Neural Motifs: Scene Graph Parsing With Global Context](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zellers_Neural_Motifs_Scene_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rowanz/neural-motifs) | 171 | +| [Learning a Single Convolutional Super-Resolution Network for Multiple Degradations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Learning_a_Single_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/cszn/SRMD) | 169 | +| [Optimizing Video Object Detection via a Scale-Time Lattice](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Optimizing_Video_Object_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hellock/scale-time-lattice) | 168 | +| [MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network](http://openaccess.thecvf.com/content_ECCV_2018/html/Muhammed_Kocabas_MultiPoseNet_Fast_Multi-Person_ECCV_2018_paper.html) | ECCV | [code](https://github.com/salihkaragoz/pose-residual-network-pytorch) | 167 | +| [Unsupervised Cross-Dataset Person Re-Identification by Transfer Learning of Spatial-Temporal Patterns](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lv_Unsupervised_Cross-Dataset_Person_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ahangchen/TFusion) | 166 | +| [Weakly Supervised Instance Segmentation Using Class Peak Response](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Weakly_Supervised_Instance_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ZhouYanzhao/PRM) | 166 | +| [PlaneNet: Piece-Wise Planar Reconstruction From a Single RGB Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_PlaneNet_Piece-Wise_Planar_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/art-programmer/PlaneNet) | 164 | +| [Residual Dense Network for Image Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Residual_Dense_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yulunzhang/RDN) | 163 | +| [Embodied Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Das_Embodied_Question_Answering_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/EmbodiedQA) | 162 | +| [Evolved Policy Gradients](http://arxiv.org/abs/1802.04821v2) | NIPS | [code](https://github.com/openai/EPG) | 160 | +| [Camera Style Adaptation for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhong_Camera_Style_Adaptation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhunzhong07/CamStyle) | 159 | +| [Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer](http://openaccess.thecvf.com/content_cvpr_2018/papers/Fang_Weakly_and_Semi_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/MVIG-SJTU/WSHP) | 159 | +| [Scale-Recurrent Network for Deep Image Deblurring](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tao_Scale-Recurrent_Network_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiangsutx/SRN-Deblur) | 159 | +| [Unsupervised Learning of Monocular Depth Estimation and Visual Odometry With Deep Feature Reconstruction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhan_Unsupervised_Learning_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Huangying-Zhan/Depth-VO-Feat) | 158 | +| [Relational recurrent neural networks](https://arxiv.org/abs/1806.01822) | NIPS | [code](https://github.com/L0SG/relational-rnn-pytorch) | 157 | +| [Densely Connected Pyramid Dehazing Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Densely_Connected_Pyramid_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hezhangsprinter/DCPDN) | 155 | +| [Image Inpainting for Irregular Holes Using Partial Convolutions](http://openaccess.thecvf.com/content_ECCV_2018/html/Guilin_Liu_Image_Inpainting_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/naoto0804/pytorch-inpainting-with-partial-conv) | 153 | +| [SO-Net: Self-Organizing Network for Point Cloud Analysis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_SO-Net_Self-Organizing_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lijx10/SO-Net) | 152 | +| [Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_Pix3D_Dataset_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xingyuansun/pix3d) | 152 | +| [ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_ShuffleNet_An_Extremely_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/camel007/Caffe-ShuffleNet) | 152 | +| [DenseASPP for Semantic Segmentation in Street Scenes](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_DenseASPP_for_Semantic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/DeepMotionAIResearch/DenseASPP) | 151 | +| [Facelet-Bank for Fast Portrait Manipulation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Facelet-Bank_for_Fast_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yingcong/Facelet_Bank) | 150 | +| [Self-Imitation Learning](http://proceedings.mlr.press/v80/oh18b.html) | ICML | [code](https://github.com/junhyukoh/self-imitation-learning) | 145 | +| [Graph R-CNN for Scene Graph Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Jianwei_Yang_Graph_R-CNN_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/jwyang/graph-rcnn.pytorch) | 144 | +| [A Closer Look at Spatiotemporal Convolutions for Action Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tran_A_Closer_Look_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/irhumshafkat/R2Plus1D-PyTorch) | 143 | +| [Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Inoue_Cross-Domain_Weakly-Supervised_Object_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/naoto0804/cross-domain-detection) | 143 | +| [Quantized Densely Connected U-Nets for Efficient Landmark Localization](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhiqiang_Tang_Quantized_Densely_Connected_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zhiqiangdon/CU-Net) | 143 | +| [Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining](http://openaccess.thecvf.com/content_ECCV_2018/html/Xia_Li_Recurrent_Squeeze-and-Excitation_Context_ECCV_2018_paper.html) | ECCV | [code](https://github.com/XiaLiPKU/RESCAN) | 142 | +| [Two-Stream Convolutional Networks for Dynamic Texture Synthesis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tesfaldet_Two-Stream_Convolutional_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ryersonvisionlab/two-stream-dyntex-synth) | 141 | +| [Integral Human Pose Regression](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiao_Sun_Integral_Human_Pose_ECCV_2018_paper.html) | ECCV | [code](https://github.com/JimmySuen/integral-human-pose) | 141 | +| [Adaptive Affinity Fields for Semantic Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Jyh-Jing_Hwang_Adaptive_Affinity_Field_ECCV_2018_paper.html) | ECCV | [code](https://github.com/twke18/Adaptive_Affinity_Fields) | 141 | +| [LSTM Pose Machines](http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_LSTM_Pose_Machines_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lawy623/LSTM_Pose_Machines) | 141 | +| [Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Structure_Inference_Net_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/choasup/SIN) | 140 | +| [Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Recovering_Realistic_Texture_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xinntao/CVPR18-SFTGAN) | 139 | +| [Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Deng_Image-Image_Domain_Adaptation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Simon4Yan/Learning-via-Translation) | 137 | +| [Learning to Compare: Relation Network for Few-Shot Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sung_Learning_to_Compare_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lzrobots/LearningToCompare_ZSL) | 135 | +| [CosFace: Large Margin Cosine Loss for Deep Face Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_CosFace_Large_Margin_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yule-li/CosFace) | 135 | +| [Deep Depth Completion of a Single RGB-D Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Deep_Depth_Completion_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yindaz/DeepCompletionRelease) | 134 | +| [Deep Back-Projection Networks for Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2018/papers/Haris_Deep_Back-Projection_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alterzero/DBPN-Pytorch) | 132 | +| [Context Embedding Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kim_Context_Embedding_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/thunlp/CANE) | 131 | +| [Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kendall_Multi-Task_Learning_Using_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alexgkendall/multitaskvision) | 131 | +| [Perturbative Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Juefei-Xu_Perturbative_Neural_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/juefeix/pnn.pytorch) | 130 | +| [Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis](http://proceedings.mlr.press/v80/wang18h.html) | ICML | [code](https://github.com/syang1993/gst-tacotron) | 129 | +| [Fast and Accurate Online Video Object Segmentation via Tracking Parts](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cheng_Fast_and_Accurate_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JingchunCheng/FAVOS) | 129 | +| [Nonlinear 3D Face Morphable Model](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tran_Nonlinear_3D_Face_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tranluan/Nonlinear_Face_3DMM) | 128 | +| [BodyNet: Volumetric Inference of 3D Human Body Shapes](http://openaccess.thecvf.com/content_ECCV_2018/html/Gul_Varol_BodyNet_Volumetric_Inference_ECCV_2018_paper.html) | ECCV | [code](https://github.com/gulvarol/bodynet) | 126 | +| [3D-CODED: 3D Correspondences by Deep Deformation](http://openaccess.thecvf.com/content_ECCV_2018/html/Thibault_Groueix_Shape_correspondences_from_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ThibaultGROUEIX/3D-CODED) | 125 | +| [DeepMVS: Learning Multi-View Stereopsis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_DeepMVS_Learning_Multi-View_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/phuang17/DeepMVS) | 125 | +| [Hierarchical Imitation and Reinforcement Learning](http://proceedings.mlr.press/v80/le18a.html) | ICML | [code](https://github.com/hoangminhle/hierarchical_IL_RL) | 124 | +| [Domain Adaptive Faster R-CNN for Object Detection in the Wild](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Domain_Adaptive_Faster_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yuhuayc/da-faster-rcnn) | 123 | +| [L4: Practical loss-based stepsize adaptation for deep learning](http://arxiv.org/abs/1802.05074v4) | NIPS | [code](https://github.com/martius-lab/l4-optimizer) | 123 | +| [A Generative Adversarial Approach for Zero-Shot Learning From Noisy Texts](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhu_A_Generative_Adversarial_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/EthanZhu90/ZSL_GAN_CVPR18) | 122 | +| [Recurrent Relational Networks](http://arxiv.org/abs/1711.08028v2) | NIPS | [code](https://github.com/rasmusbergpalm/recurrent-relational-networks) | 121 | +| [Gated Path Planning Networks](http://proceedings.mlr.press/v80/lee18c.html) | ICML | [code](https://github.com/lileee/gated-path-planning-networks) | 121 | +| [PSANet: Point-wise Spatial Attention Network for Scene Parsing](http://openaccess.thecvf.com/content_ECCV_2018/html/Hengshuang_Zhao_PSANet_Point-wise_Spatial_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hszhao/PSANet) | 121 | +| [Rethinking Feature Distribution for Loss Functions in Image Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wan_Rethinking_Feature_Distribution_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/WeitaoVan/L-GM-loss) | 120 | +| [Density-Aware Single Image De-Raining Using a Multi-Stream Dense Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Density-Aware_Single_Image_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hezhangsprinter/DID-MDN) | 118 | +| [FOTS: Fast Oriented Text Spotting With a Unified Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_FOTS_Fast_Oriented_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiangxiluning/FOTS.PyTorch) | 118 | +| [ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes](http://openaccess.thecvf.com/content_ECCV_2018/html/Taihong_Xiao_ELEGANT_Exchanging_Latent_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Prinsphield/ELEGANT) | 117 | +| [PU-Net: Point Cloud Upsampling Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_PU-Net_Point_Cloud_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yulequan/PU-Net) | 117 | +| [PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mallya_PackNet_Adding_Multiple_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/arunmallya/packnet) | 117 | +| [Long-term Tracking in the Wild: a Benchmark](http://openaccess.thecvf.com/content_ECCV_2018/html/Efstratios_Gavves_Long-term_Tracking_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/oxuva/long-term-tracking-benchmark) | 116 | +| [Factoring Shape, Pose, and Layout From the 2D Image of a 3D Scene](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulsiani_Factoring_Shape_Pose_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/shubhtuls/factored3d) | 114 | +| [Repulsion Loss: Detecting Pedestrians in a Crowd](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Repulsion_Loss_Detecting_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/bailvwangzi/repulsion_loss_ssd) | 113 | +| [Unsupervised Attention-guided Image-to-Image Translation](https://arxiv.org/abs/1806.02311) | NIPS | [code](https://github.com/AlamiMejjati/Unsupervised-Attention-guided-Image-to-Image-Translation) | 110 | +| [Attention-based Deep Multiple Instance Learning](http://proceedings.mlr.press/v80/ilse18a.html) | ICML | [code](https://github.com/AMLab-Amsterdam/AttentionDeepMIL) | 109 | +| [Learning Blind Video Temporal Consistency](http://openaccess.thecvf.com/content_ECCV_2018/html/Wei-Sheng_Lai_Real-Time_Blind_Video_ECCV_2018_paper.html) | ECCV | [code](https://github.com/phoenix104104/fast_blind_video_consistency) | 109 | +| [Noisy Natural Gradient as Variational Inference](http://proceedings.mlr.press/v80/zhang18l.html) | ICML | [code](https://github.com/wlwkgus/NoisyNaturalGradient) | 108 | +| [End-to-End Weakly-Supervised Semantic Alignment](http://openaccess.thecvf.com/content_cvpr_2018/papers/Rocco_End-to-End_Weakly-Supervised_Semantic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ignacio-rocco/weakalign) | 106 | +| [Decoupled Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Decoupled_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wy1iu/DCNets) | 105 | +| [LiDAR-Video Driving Dataset: Learning Driving Policies Effectively](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_LiDAR-Video_Driving_Dataset_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/driving-behavior/DBNet) | 104 | +| [MAttNet: Modular Attention Network for Referring Expression Comprehension](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_MAttNet_Modular_Attention_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lichengunc/MAttNet) | 104 | +| [LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Dongqing_Zhang_Optimized_Quantization_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Microsoft/LQ-Nets) | 103 | +| [FSRNet: End-to-End Learning Face Super-Resolution With Facial Priors](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_FSRNet_End-to-End_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tyshiwo/FSRNet) | 100 | +| [Deep Mutual Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Deep_Mutual_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/YingZhangDUT/Deep-Mutual-Learning) | 100 | +| [Macro-Micro Adversarial Network for Human Parsing](http://openaccess.thecvf.com/content_ECCV_2018/html/Yawei_Luo_Macro-Micro_Adversarial_Network_ECCV_2018_paper.html) | ECCV | [code](https://github.com/RoyalVane/MMAN) | 98 | +| [ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans](http://openaccess.thecvf.com/content_cvpr_2018/papers/Dai_ScanComplete_Large-Scale_Scene_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/angeladai/ScanComplete) | 97 | +| [Learning Depth From Monocular Videos Using Direct Methods](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_Depth_From_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/MightyChaos/LKVOLearner) | 97 | +| [VITON: An Image-Based Virtual Try-On Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Han_VITON_An_Image-Based_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xthan/VITON) | 95 | +| [Cascade R-CNN: Delving Into High Quality Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cai_Cascade_R-CNN_Delving_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/guoruoqian/cascade-rcnn_Pytorch) | 93 | +| [Learning Human-Object Interactions by Graph Parsing Neural Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Siyuan_Qi_Learning_Human-Object_Interactions_ECCV_2018_paper.html) | ECCV | [code](https://github.com/SiyuanQi/gpnn) | 93 | +| [Future Frame Prediction for Anomaly Detection – A New Baseline](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Future_Frame_Prediction_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/StevenLiuWen/ano_pred_cvpr2018) | 92 | +| [Multi-view to Novel view: Synthesizing novel views with Self-Learned Confidence](http://openaccess.thecvf.com/content_ECCV_2018/html/Shao-Hua_Sun_Multi-view_to_Novel_ECCV_2018_paper.html) | ECCV | [code](https://github.com/shaohua0116/Multiview2Novelview) | 92 | +| [Tell Me Where to Look: Guided Attention Inference Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Tell_Me_Where_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alokwhitewolf/Guided-Attention-Inference-Network) | 91 | +| [Neural Kinematic Networks for Unsupervised Motion Retargetting](http://openaccess.thecvf.com/content_cvpr_2018/papers/Villegas_Neural_Kinematic_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rubenvillegas/cvpr2018nkn) | 90 | +| [Learning SO(3) Equivariant Representations with Spherical CNNs](http://openaccess.thecvf.com/content_ECCV_2018/html/Carlos_Esteves_Learning_SO3_Equivariant_ECCV_2018_paper.html) | ECCV | [code](https://github.com/daniilidis-group/spherical-cnn) | 89 | +| [One-Shot Unsupervised Cross Domain Translation](http://arxiv.org/abs/1806.06029v1) | NIPS | [code](https://github.com/sagiebenaim/OneShotTranslation) | 89 | +| [Synthesizing Images of Humans in Unseen Poses](http://openaccess.thecvf.com/content_cvpr_2018/papers/Balakrishnan_Synthesizing_Images_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/balakg/posewarp-cvpr2018) | 88 | +| [Depth-aware CNN for RGB-D Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Weiyue_Wang_Depth-aware_CNN_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/laughtervv/DepthAwareCNN) | 88 | +| [Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights](http://openaccess.thecvf.com/content_ECCV_2018/html/Arun_Mallya_Piggyback_Adapting_a_ECCV_2018_paper.html) | ECCV | [code](https://github.com/arunmallya/piggyback) | 88 | +| [Knowledge Aided Consistency for Weakly Supervised Phrase Grounding](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Knowledge_Aided_Consistency_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kanchen-usc/KAC-Net) | 87 | +| [CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_CSRNet_Dilated_Convolutional_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/leeyeehoo/CSRNet-pytorch) | 87 | +| [Neural Arithmetic Logic Units](http://arxiv.org/abs/1808.00508v1) | NIPS | [code](https://github.com/llSourcell/Neural_Arithmetic_Logic_Units) | 87 | +| [A PID Controller Approach for Stochastic Optimization of Deep Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/An_A_PID_Controller_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tensorboy/PIDOptimizer) | 87 | +| [VITAL: VIsual Tracking via Adversarial Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_VITAL_VIsual_Tracking_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ybsong00/Vital_release) | 86 | +| [Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Spatial-Temporal_Regularized_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lifeng9472/STRCF) | 86 | +| [Recurrent Pixel Embedding for Instance Grouping](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kong_Recurrent_Pixel_Embedding_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/aimerykong/Recurrent-Pixel-Embedding-for-Instance-Grouping) | 85 | +| [SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_SGPN_Similarity_Group_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/laughtervv/SGPN) | 84 | +| [Multi-Scale Location-Aware Kernel Representation for Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Multi-Scale_Location-Aware_Kernel_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Hwang64/MLKP) | 84 | +| [Repeatability Is Not Enough: Learning Affine Regions via Discriminability](http://openaccess.thecvf.com/content_ECCV_2018/html/Dmytro_Mishkin_Repeatability_Is_Not_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ducha-aiki/affnet) | 84 | +| [“Zero-Shot” Super-Resolution Using Deep Internal Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shocher_Zero-Shot_Super-Resolution_Using_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/assafshocher/ZSSR) | 84 | +| [DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency](http://openaccess.thecvf.com/content_ECCV_2018/html/Yuliang_Zou_DF-Net_Unsupervised_Joint_ECCV_2018_paper.html) | ECCV | [code](https://github.com/vt-vl-lab/DF-Net) | 82 | +| [Multi-View Consistency as Supervisory Signal for Learning Shape and Pose Prediction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulsiani_Multi-View_Consistency_as_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/shubhtuls/mvcSnP) | 80 | +| [Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Yikang_LI_Factorizable_Net_An_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yikang-li/FactorizableNet) | 78 | +| [Generalizing A Person Retrieval Model Hetero- and Homogeneously](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhun_Zhong_Generalizing_A_Person_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zhunzhong07/HHL) | 78 | +| [Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Crafting_a_Toolchain_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yuke93/RL-Restore) | 77 | +| [Pairwise Confusion for Fine-Grained Visual Classification](http://openaccess.thecvf.com/content_ECCV_2018/html/Abhimanyu_Dubey_Improving_Fine-Grained_Visual_ECCV_2018_paper.html) | ECCV | [code](https://github.com/abhimanyudubey/confusion) | 77 | +| [Learning to Reweight Examples for Robust Deep Learning](http://proceedings.mlr.press/v80/ren18a.html) | ICML | [code](https://github.com/danieltan07/learning-to-reweight-examples) | 76 | +| [Improving Generalization via Scalable Neighborhood Component Analysis](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhirong_Wu_Improving_Embedding_Generalization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Microsoft/snca.pytorch) | 76 | +| [SparseMAP: Differentiable Sparse Structured Inference](http://proceedings.mlr.press/v80/niculae18a.html) | ICML | [code](https://github.com/vene/sparsemap) | 75 | +| [PDE-Net: Learning PDEs from Data](http://proceedings.mlr.press/v80/long18a.html) | ICML | [code](https://github.com/ZichaoLong/PDE-Net) | 75 | +| [Pose-Normalized Image Generation for Person Re-identification](http://openaccess.thecvf.com/content_ECCV_2018/html/Xuelin_Qian_Pose-Normalized_Image_Generation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/naiq/PN_GAN) | 75 | +| [Disentangled Person Image Generation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ma_Disentangled_Person_Image_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/charliememory/Disentangled-Person-Image-Generation) | 75 | +| [Learning to Navigate for Fine-grained Classification](http://openaccess.thecvf.com/content_ECCV_2018/html/Ze_Yang_Learning_to_Navigate_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yangze0930/NTS-Net) | 74 | +| [Superpixel Sampling Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Varun_Jampani_Superpixel_Sampling_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NVlabs/ssn_superpixels) | 74 | +| [Shift-Net: Image Inpainting via Deep Feature Rearrangement](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhaoyi_Yan_Shift-Net_Image_Inpainting_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Zhaoyi-Yan/Shift-Net_pytorch) | 74 | +| [3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Angela_Dai_3DMV_Joint_3D-Multi-View_ECCV_2018_paper.html) | ECCV | [code](https://github.com/angeladai/3DMV) | 74 | +| [Ordinal Depth Supervision for 3D Human Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Pavlakos_Ordinal_Depth_Supervision_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/geopavlakos/ordinal-pose3d) | 74 | +| [Path-Level Network Transformation for Efficient Architecture Search](http://proceedings.mlr.press/v80/cai18a.html) | ICML | [code](https://github.com/han-cai/PathLevel-EAS) | 73 | +| [Diverse Image-to-Image Translation via Disentangled Representations](http://openaccess.thecvf.com/content_ECCV_2018/html/Hsin-Ying_Lee_Diverse_Image-to-Image_Translation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/taki0112/DRIT-Tensorflow) | 72 | +| [Visual Feature Attribution Using Wasserstein GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Baumgartner_Visual_Feature_Attribution_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/orobix/Visual-Feature-Attribution-Using-Wasserstein-GANs-Pytorch) | 72 | +| [Real-World Anomaly Detection in Surveillance Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sultani_Real-World_Anomaly_Detection_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/WaqasSultani/AnomalyDetectionCVPR2018) | 72 | +| [Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Self-Supervised_Adversarial_Hashing_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lelan-li/SSAH) | 72 | +| [Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image](http://openaccess.thecvf.com/content_ECCV_2018/html/Siyuan_Huang_Monocular_Scene_Parsing_ECCV_2018_paper.html) | ECCV | [code](https://github.com/thusiyuan/holistic_scene_parsing) | 72 | +| [Learning to Find Good Correspondences](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yi_Learning_to_Find_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/vcg-uvic/learned-correspondence-release) | 72 | +| [Learning Less Is More - 6D Camera Localization via 3D Surface Regression](http://openaccess.thecvf.com/content_cvpr_2018/papers/Brachmann_Learning_Less_Is_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/vislearn/LessMore) | 72 | +| [Object Level Visual Reasoning in Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Fabien_Baradel_Object_Level_Visual_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fabienbaradel/object_level_visual_reasoning) | 71 | +| [Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Weakly-Supervised_Semantic_Segmentation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/speedinghzl/DSRG) | 71 | +| [Avatar-Net: Multi-Scale Zero-Shot Style Transfer by Feature Decoration](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sheng_Avatar-Net_Multi-Scale_Zero-Shot_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/LucasSheng/avatar-net) | 71 | +| [Fast and Accurate Single Image Super-Resolution via Information Distillation Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hui_Fast_and_Accurate_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Zheng222/IDN-Caffe) | 71 | +| [Regularizing RNNs for Caption Generation by Reconstructing the Past With the Present](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Regularizing_RNNs_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chenxinpeng/ARNet) | 70 | +| [Multi-Shot Pedestrian Re-Identification via Sequential Decision Making](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Multi-Shot_Pedestrian_Re-Identification_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/TuSimple/rl-multishot-reid) | 70 | +| [PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Uy_PointNetVLAD_Deep_Point_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mikacuy/pointnetvlad) | 69 | +| [Progressive Neural Architecture Search](http://openaccess.thecvf.com/content_ECCV_2018/html/Chenxi_Liu_Progressive_Neural_Architecture_ECCV_2018_paper.html) | ECCV | [code](https://github.com/titu1994/progressive-neural-architecture-search) | 68 | +| [Generative Neural Machine Translation](http://arxiv.org/abs/1806.05138v1) | NIPS | [code](https://github.com/ZhenYangIACAS/NMT_GAN) | 68 | +| [Learning Latent Super-Events to Detect Multiple Activities in Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Piergiovanni_Learning_Latent_Super-Events_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/piergiaj/super-events-cvpr18) | 67 | +| [Generate to Adapt: Aligning Domains Using Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Generate_to_Adapt_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yogeshbalaji/Generate_To_Adapt) | 67 | +| [Adversarial Feature Augmentation for Unsupervised Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Volpi_Adversarial_Feature_Augmentation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ricvolpi/adversarial-feature-augmentation) | 67 | +| [Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_Attentions_Residual_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/foolwood/RASNet) | 67 | +| [Pointwise Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hua_Pointwise_Convolutional_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/scenenn/pointwise) | 67 | +| [Optimizing the Latent Space of Generative Networks](http://proceedings.mlr.press/v80/bojanowski18a.html) | ICML | [code](https://github.com/tneumann/minimal_glo) | 66 | +| [Part-Aligned Bilinear Representations for Person Re-Identification](http://openaccess.thecvf.com/content_ECCV_2018/html/Yumin_Suh_Part-Aligned_Bilinear_Representations_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yuminsuh/part_bilinear_reid) | 64 | +| [Geometry-Aware Learning of Maps for Camera Localization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Brahmbhatt_Geometry-Aware_Learning_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/samarth-robo/MapNet) | 63 | +| [Fighting Fake News: Image Splice Detection via Learned Self-Consistency](http://openaccess.thecvf.com/content_ECCV_2018/html/Jacob_Huh_Fighting_Fake_News_ECCV_2018_paper.html) | ECCV | [code](https://github.com/minyoungg/selfconsistency) | 62 | +| [Isolating Sources of Disentanglement in Variational Autoencoders](http://arxiv.org/abs/1802.04942v2) | NIPS | [code](https://github.com/rtqichen/beta-tcvae) | 62 | +| [Neural Program Synthesis from Diverse Demonstration Videos](http://proceedings.mlr.press/v80/sun18a.html) | ICML | [code](https://github.com/shaohua0116/demo2program) | 62 | +| [Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhaoyang_Lv_Learning_Rigidity_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NVlabs/learningrigidity) | 61 | +| [Rotation-Sensitive Regression for Oriented Scene Text Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liao_Rotation-Sensitive_Regression_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/MhLiao/RRD) | 61 | +| [Human Semantic Parsing for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kalayeh_Human_Semantic_Parsing_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/emrahbasaran/SPReID) | 61 | +| [Unsupervised Discovery of Object Landmarks as Structural Representations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Unsupervised_Discovery_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/YutingZhang/lmdis-rep) | 61 | +| [IQA: Visual Question Answering in Interactive Environments](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gordon_IQA_Visual_Question_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/danielgordon10/thor-iqa-cvpr-2018) | 60 | +| [Hierarchical Long-term Video Prediction without Supervision](http://proceedings.mlr.press/v80/wichers18a.html) | ICML | [code](https://github.com/brain-research/long-term-video-prediction-without-supervision) | 60 | +| [Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency](http://openaccess.thecvf.com/content_ECCV_2018/html/Xingyi_Zhou_Unsupervised_Domain_Adaptation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/xingyizhou/3DKeypoints-DA) | 60 | +| [Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Exploit_the_Unknown_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Yu-Wu/Exploit-Unknown-Gradually) | 59 | +| [Neural Style Transfer via Meta Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Neural_Style_Transfer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/FalongShen/styletransfer) | 59 | +| [Frame-Recurrent Video Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sajjadi_Frame-Recurrent_Video_Super-Resolution_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/msmsajjadi/FRVSR) | 58 | +| [PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction](http://openaccess.thecvf.com/content_ECCV_2018/html/Yifei_Shi_PlaneMatch_Patch_Coplanarity_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yifeishi/PlaneMatch) | 57 | +| [CBAM: Convolutional Block Attention Module](http://openaccess.thecvf.com/content_ECCV_2018/html/Sanghyun_Woo_Convolutional_Block_Attention_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Youngkl0726/Convolutional-Block-Attention-Module) | 57 | +| [Decorrelated Batch Normalization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Decorrelated_Batch_Normalization_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/umich-vl/DecorrelatedBN) | 57 | +| [Learning Conditioned Graph Structures for Interpretable Visual Question Answering](nan) | NIPS | [code](https://github.com/aimbrain/vqa-project) | 57 | +| [Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition](http://openaccess.thecvf.com/content_ECCV_2018/html/Chaojian_Yu_Hierarchical_Bilinear_Pooling_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ChaojianYu/Hierarchical-Bilinear-Pooling) | 57 | +| [Leveraging Unlabeled Data for Crowd Counting by Learning to Rank](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Leveraging_Unlabeled_Data_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xialeiliu/CrowdCountingCVPR18) | 56 | +| [Deep Marching Cubes: Learning Explicit Surface Representations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liao_Deep_Marching_Cubes_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yiyiliao/deep_marching_cubes) | 56 | +| [Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Learning_From_Synthetic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/swamiviv/LSD-seg) | 56 | +| [LF-Net: Learning Local Features from Images](https://arxiv.org/abs/1805.09662) | NIPS | [code](https://github.com/vcg-uvic/lf-net-release) | 55 | +| [Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model](http://openaccess.thecvf.com/content_ECCV_2018/html/Baris_Gecer_Semi-supervised_Adversarial_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/barisgecer/facegan) | 55 | +| [Discriminability Objective for Training Descriptive Captions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_Discriminability_Objective_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ruotianluo/DiscCaptioning) | 54 | +| [BlockDrop: Dynamic Inference Paths in Residual Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_BlockDrop_Dynamic_Inference_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Tushar-N/blockdrop) | 54 | +| [Conditional Probability Models for Deep Image Compression](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mentzer_Conditional_Probability_Models_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/fab-jul/imgcomp-cvpr) | 54 | +| [Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Peng_Jointly_Optimize_Data_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhiqiangdon/pose-adv-aug) | 54 | +| [Learning towards Minimum Hyperspherical Energy](http://arxiv.org/abs/1805.09298v4) | NIPS | [code](https://github.com/wy1iu/MHE) | 54 | +| [DeepVS: A Deep Learning Based Video Saliency Prediction Approach](http://openaccess.thecvf.com/content_ECCV_2018/html/Lai_Jiang_DeepVS_A_Deep_ECCV_2018_paper.html) | ECCV | [code](https://github.com/remega/OMCNN_2CLSTM) | 53 | +| [Learning Efficient Single-stage Pedestrian Detectors by Asymptotic Localization Fitting](http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html) | ECCV | [code](https://github.com/liuwei16/ALFNet) | 52 | +| [Learning Pixel-Level Semantic Affinity With Image-Level Supervision for Weakly Supervised Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ahn_Learning_Pixel-Level_Semantic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiwoon-ahn/psa) | 52 | +| [Wasserstein Introspective Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_Wasserstein_Introspective_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kjunelee/WINN) | 51 | +| [SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_SketchyGAN_Towards_Diverse_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wchen342/SketchyGAN) | 51 | +| [Self-produced Guidance for Weakly-supervised Object Localization](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaolin_Zhang_Self-produced_Guidance_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/xiaomengyc/SPG) | 51 | +| [Measuring abstract reasoning in neural networks](http://proceedings.mlr.press/v80/santoro18a.html) | ICML | [code](https://github.com/deepmind/abstract-reasoning-matrices) | 51 | +| [A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation](https://arxiv.org/abs/1809.01361) | NIPS | [code](https://github.com/XenderLiu/UFDN) | 51 | +| [RayNet: Learning Volumetric 3D Reconstruction With Ray Potentials](http://openaccess.thecvf.com/content_cvpr_2018/papers/Paschalidou_RayNet_Learning_Volumetric_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/paschalidoud/raynet) | 51 | +| [Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Hyojin_Bahng_Coloring_with_Words_ECCV_2018_paper.html) | ECCV | [code](https://github.com/awesome-davian/Text2Colors) | 50 | +| [Efficient end-to-end learning for quantizable representations](http://proceedings.mlr.press/v80/jeong18a.html) | ICML | [code](https://github.com/maestrojeong/Deep-Hash-Table-ICML18) | 50 | +| [Visual Question Generation as Dual Task of Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Visual_Question_Generation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yikang-li/iQAN) | 50 | +| [Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam](http://proceedings.mlr.press/v80/khan18a.html) | ICML | [code](https://github.com/emtiyaz/vadam) | 49 | +| [Surface Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kostrikov_Surface_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiangzhongshi/SurfaceNetworks) | 48 | +| [Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions](http://proceedings.mlr.press/v80/wu18h.html) | ICML | [code](https://github.com/Sandbox3aster/Deep-K-Means-pytorch) | 48 | +| [Stacked Cross Attention for Image-Text Matching](http://openaccess.thecvf.com/content_ECCV_2018/html/Kuang-Huei_Lee_Stacked_Cross_Attention_ECCV_2018_paper.html) | ECCV | [code](https://github.com/kuanghuei/SCAN) | 48 | +| [Actor and Observer: Joint Modeling of First and Third-Person Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sigurdsson_Actor_and_Observer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/gsig/actor-observer) | 48 | +| [Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Jiang_Super_SloMo_High_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/TheFairBear/Super-SlowMo) | 47 | +| [Learning-based Video Motion Magnification](http://openaccess.thecvf.com/content_ECCV_2018/html/Tae-Hyun_Oh_Learning-based_Video_Motion_ECCV_2018_paper.html) | ECCV | [code](https://github.com/12dmodel/deep_motion_mag) | 47 | +| [Pose Partition Networks for Multi-Person Pose Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Xuecheng_Nie_Pose_Partition_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NieXC/pytorch-ppn) | 47 | +| [Neural Autoregressive Flows](http://proceedings.mlr.press/v80/huang18d.html) | ICML | [code](https://github.com/CW-Huang/NAF) | 47 | +| [Weakly- and Semi-Supervised Panoptic Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Anurag_Arnab_Weakly-_and_Semi-Supervised_ECCV_2018_paper.html) | ECCV | [code](https://github.com/qizhuli/Weakly-Supervised-Panoptic-Segmentation) | 46 | +| [Video Re-localization](http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_Feng_Video_Re-localization_via_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fengyang0317/video_reloc) | 46 | +| [Real-time 'Actor-Critic' Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Boyu_Chen_Real-time_Actor-Critic_Tracking_ECCV_2018_paper.html) | ECCV | [code](https://github.com/bychen515/ACT) | 46 | +| [Black-box Adversarial Attacks with Limited Queries and Information](http://proceedings.mlr.press/v80/ilyas18a.html) | ICML | [code](https://github.com/labsix/limited-blackbox-attacks) | 46 | +| [Hyperbolic Entailment Cones for Learning Hierarchical Embeddings](http://proceedings.mlr.press/v80/ganea18a.html) | ICML | [code](https://github.com/dalab/hyperbolic_cones) | 46 | +| [Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Structured_Attention_Guided_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/danxuhk/StructuredAttentionDepthEstimation) | 46 | +| [Differentiable Compositional Kernel Learning for Gaussian Processes](http://proceedings.mlr.press/v80/sun18e.html) | ICML | [code](https://github.com/ssydasheng/Neural-Kernel-Network) | 45 | +| [Visualizing and Understanding Atari Agents](http://proceedings.mlr.press/v80/greydanus18a.html) | ICML | [code](https://github.com/greydanus/visualize_atari) | 45 | +| [Image Manipulation with Perceptual Discriminators](http://openaccess.thecvf.com/content_ECCV_2018/html/Diana_Sungatullina_Image_Manipulation_with_ECCV_2018_paper.html) | ECCV | [code](https://github.com/egorzakharov/PerceptualGAN) | 45 | +| [Learning Intrinsic Image Decomposition From Watching the World](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Intrinsic_Image_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lixx2938/unsupervised-learning-intrinsic-images) | 45 | +| [Overcoming Catastrophic Forgetting with Hard Attention to the Task](http://proceedings.mlr.press/v80/serra18a.html) | ICML | [code](https://github.com/joansj/hat) | 44 | +| [Learning Pose Specific Representations by Predicting Different Views](http://openaccess.thecvf.com/content_cvpr_2018/papers/Poier_Learning_Pose_Specific_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/poier/PreView) | 44 | +| [Zero-Shot Object Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Ankan_Bansal_Zero-Shot_Object_Detection_ECCV_2018_paper.html) | ECCV | [code](https://github.com/salman-h-khan/ZSD_Release) | 43 | +| [Mean Field Multi-Agent Reinforcement Learning](http://proceedings.mlr.press/v80/yang18d.html) | ICML | [code](https://github.com/mlii/mfrl) | 43 | +| [Partial Adversarial Domain Adaptation](http://openaccess.thecvf.com/content_ECCV_2018/html/Zhangjie_Cao_Partial_Adversarial_Domain_ECCV_2018_paper.html) | ECCV | [code](https://github.com/thuml/PADA) | 43 | +| [Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Xuecheng_Nie_Mutual_Learning_to_ECCV_2018_paper.html) | ECCV | [code](https://github.com/NieXC/pytorch-mula) | 43 | +| [Robust Classification With Convolutional Prototype Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Robust_Classification_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/YangHM/Convolutional-Prototype-Learning) | 43 | +| [SimplE Embedding for Link Prediction in Knowledge Graphs](http://arxiv.org/abs/1802.04868v1) | NIPS | [code](https://github.com/Mehran-k/SimplE) | 42 | +| [PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning](http://proceedings.mlr.press/v80/wang18b.html) | ICML | [code](https://github.com/Yunbo426/predrnn-pp) | 42 | +| [Learning to Blend Photos](http://openaccess.thecvf.com/content_ECCV_2018/html/Wei-Chih_Hung_Learning_to_Blend_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hfslyc/LearnToBlend) | 42 | +| [Mask-Guided Contrastive Attention Model for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_Mask-Guided_Contrastive_Attention_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/developfeng/MGCAM) | 41 | +| [Link Prediction Based on Graph Neural Networks](http://arxiv.org/abs/1802.09691v2) | NIPS | [code](https://github.com/muhanzhang/SEAL) | 41 | +| [Generalisation in humans and deep neural networks](http://arxiv.org/abs/1808.08750v1) | NIPS | [code](https://github.com/rgeirhos/generalisation-humans-DNNs) | 41 | +| [Towards Binary-Valued Gates for Robust LSTM Training](http://proceedings.mlr.press/v80/li18c.html) | ICML | [code](https://github.com/zhuohan123/g2-lstm) | 41 | +| [Multi-scale Residual Network for Image Super-Resolution](http://openaccess.thecvf.com/content_ECCV_2018/html/Juncheng_Li_Multi-scale_Residual_Network_ECCV_2018_paper.html) | ECCV | [code](https://github.com/MIVRC/MSRN-PyTorch) | 41 | +| [Fully Motion-Aware Network for Video Object Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Shiyao_Wang_Fully_Motion-Aware_Network_ECCV_2018_paper.html) | ECCV | [code](https://github.com/wangshy31/MANet_for_Video_Object_Detection) | 41 | +| [Interpretable Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Interpretable_Convolutional_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/seongjunyun/CNN-with-Dual-Local-and-Global-Attention) | 40 | +| [Generative Adversarial Perturbations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Poursaeed_Generative_Adversarial_Perturbations_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/OmidPoursaeed/Generative_Adversarial_Perturbations) | 40 | +| [The Sound of Pixels](http://openaccess.thecvf.com/content_ECCV_2018/html/Hang_Zhao_The_Sound_of_ECCV_2018_paper.html) | ECCV | [code](https://github.com/roudimit/MUSIC_dataset) | 40 | +| [Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Towards_Faster_Training_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiangtaoxie/fast-MPN-COV) | 40 | +| [Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance](http://openaccess.thecvf.com/content_ECCV_2018/html/Ramprasaath_Ramasamy_Selvaraju_Choose_Your_Neuron_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ramprs/neuron-importance-zsl) | 40 | +| [Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation](https://arxiv.org/abs/1802.09987) | NIPS | [code](https://github.com/EdwardSmith1884/Multi-View-Silhouette-and-Depth-Decomposition-for-High-Resolution-3D-Object-Representation) | 40 | +| [Learning Warped Guidance for Blind Face Restoration](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaoming_Li_Learning_Warped_Guidance_ECCV_2018_paper.html) | ECCV | [code](https://github.com/csxmli2016/GFRNet) | 39 | +| [Adversarial Complementary Learning for Weakly Supervised Object Localization](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Adversarial_Complementary_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xiaomengyc/ACoL) | 39 | +| [Learning Semantic Representations for Unsupervised Domain Adaptation](http://proceedings.mlr.press/v80/xie18c.html) | ICML | [code](https://github.com/Mid-Push/Moving-Semantic-Transfer-Network) | 39 | +| [Neural Architecture Search with Bayesian Optimisation and Optimal Transport](https://arxiv.org/abs/1802.07191) | NIPS | [code](https://github.com/kirthevasank/nasbot) | 39 | +| [Mutual Information Neural Estimation](http://proceedings.mlr.press/v80/belghazi18a.html) | ICML | [code](https://github.com/MasanoriYamada/Mine_pytorch) | 39 | +| [NetGAN: Generating Graphs via Random Walks](http://proceedings.mlr.press/v80/bojchevski18a.html) | ICML | [code](https://github.com/danielzuegner/netgan) | 39 | +| [Learning to Evaluate Image Captioning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cui_Learning_to_Evaluate_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/richardaecn/cvpr18-caption-eval) | 38 | +| [Hyperbolic Neural Networks](http://arxiv.org/abs/1805.09112v2) | NIPS | [code](https://github.com/dalab/hyperbolic_nn) | 37 | +| [Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Helge_Rhodin_Unsupervised_Geometry-Aware_Representation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hrhodin/UnsupervisedGeometryAwareRepresentationLearning) | 37 | +| [Adversarially Learned One-Class Classifier for Novelty Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sabokrou_Adversarially_Learned_One-Class_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/khalooei/ALOCC-CVPR2018) | 37 | +| [Disentangling by Factorising](http://proceedings.mlr.press/v80/kim18b.html) | ICML | [code](https://github.com/1Konny/FactorVAE) | 37 | +| [Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples](http://proceedings.mlr.press/v80/weiss18a.html) | ICML | [code](https://github.com/tech-srl/lstar_extraction) | 37 | +| [Tangent Convolutions for Dense Prediction in 3D](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tatarchenko_Tangent_Convolutions_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tatarchm/tangent_conv) | 37 | +| [Few-Shot Image Recognition by Predicting Parameters From Activations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qiao_Few-Shot_Image_Recognition_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/joe-siyuan-qiao/FewShot-CVPR) | 37 | +| [Real-Time Monocular Depth Estimation Using Synthetic Data With Domain Adaptation via Image Style Transfer](http://openaccess.thecvf.com/content_cvpr_2018/papers/Atapour-Abarghouei_Real-Time_Monocular_Depth_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/atapour/monocularDepth-Inference) | 37 | +| [Generalizing to Unseen Domains via Adversarial Data Augmentation](http://arxiv.org/abs/1805.12018v1) | NIPS | [code](https://github.com/ricvolpi/generalize-unseen-domains) | 36 | +| [SeGAN: Segmenting and Generating the Invisible](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_SeGAN_Segmenting_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ehsanik/SeGAN) | 36 | +| [Graphical Generative Adversarial Networks](http://arxiv.org/abs/1804.03429v1) | NIPS | [code](https://github.com/zhenxuan00/graphical-gan) | 36 | +| [PieAPP: Perceptual Image-Error Assessment Through Pairwise Preference](http://openaccess.thecvf.com/content_cvpr_2018/papers/Prashnani_PieAPP_Perceptual_Image-Error_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/prashnani/PerceptualImageError) | 36 | +| [Gated Fusion Network for Single Image Dehazing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ren_Gated_Fusion_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rwenqi/GFN-dehazing) | 35 | +| [Neural Code Comprehension: A Learnable Representation of Code Semantics](http://arxiv.org/abs/1806.07336v2) | NIPS | [code](https://github.com/spcl/ncc) | 35 | +| [Eye In-Painting With Exemplar Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Dolhansky_Eye_In-Painting_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhangqianhui/Exemplar-GAN-Eye-Inpainting-Tensorflow) | 35 | +| [Deep One-Class Classification](http://proceedings.mlr.press/v80/ruff18a.html) | ICML | [code](https://github.com/lukasruff/Deep-SVDD) | 34 | +| [Deep Regression Tracking with Shrinkage Loss](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiankai_Lu_Deep_Regression_Tracking_ECCV_2018_paper.html) | ECCV | [code](https://github.com/chaoma99/DSLT) | 34 | +| [Deflecting Adversarial Attacks With Pixel Deflection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Prakash_Deflecting_Adversarial_Attacks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/iamaaditya/pixel-deflection) | 34 | +| [Learning Visual Question Answering by Bootstrapping Hard Attention](http://openaccess.thecvf.com/content_ECCV_2018/html/Mateusz_Malinowski_Learning_Visual_Question_ECCV_2018_paper.html) | ECCV | [code](https://github.com/gnouhp/PyTorch-AdaHAN) | 33 | +| [Human-Centric Indoor Scene Synthesis Using Stochastic Grammar](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Human-Centric_Indoor_Scene_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/SiyuanQi/human-centric-scene-synthesis) | 33 | +| [Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Nguyen_Improved_Fusion_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/cvlab-tohoku/Dense-CoAttention-Network) | 33 | +| [CleanNet: Transfer Learning for Scalable Image Classifier Training With Label Noise](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_CleanNet_Transfer_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kuanghuei/clean-net) | 33 | +| [Speaker-Follower Models for Vision-and-Language Navigation](https://arxiv.org/abs/1806.02724) | NIPS | [code](https://github.com/ronghanghu/speaker_follower) | 33 | +| [Improving Shape Deformation in Unsupervised Image-to-Image Translation](http://openaccess.thecvf.com/content_ECCV_2018/html/Aaron_Gokaslan_Improving_Shape_Deformation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/brownvc/ganimorph) | 33 | +| [Learning Single-View 3D Reconstruction with Limited Pose Supervision](http://openaccess.thecvf.com/content_ECCV_2018/html/Guandao_Yang_A_Unified_Framework_ECCV_2018_paper.html) | ECCV | [code](https://github.com/stevenygd/3d-recon) | 33 | +| [3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data](https://arxiv.org/abs/1807.02547) | NIPS | [code](https://github.com/mariogeiger/se3cnn) | 33 | +| [Adversarial Logit Pairing](http://arxiv.org/abs/1803.06373v1) | NIPS | [code](https://github.com/labsix/adversarial-logit-pairing-analysis) | 32 | +| [Attention in Convolutional LSTM for Gesture Recognition](https://nips.cc/Conferences/2018/Schedule?showEvent=11207) | NIPS | [code](https://github.com/GuangmingZhu/AttentionConvLSTM) | 32 | +| [Graph-Cut RANSAC](http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/danini/graph-cut-ransac) | 32 | +| [Neural Guided Constraint Logic Programming for Program Synthesis](http://arxiv.org/abs/1809.02840v2) | NIPS | [code](https://github.com/xuexue/neuralkanren) | 32 | +| [Learning Dynamic Memory Networks for Object Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Tianyu_Yang_Learning_Dynamic_Memory_ECCV_2018_paper.html) | ECCV | [code](https://github.com/skyoung/MemTrack) | 32 | +| [GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints](http://openaccess.thecvf.com/content_ECCV_2018/html/Zixin_Luo_Learning_Local_Descriptors_ECCV_2018_paper.html) | ECCV | [code](https://github.com/lzx551402/geodesc) | 32 | +| [A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks](nan) | NIPS | [code](https://github.com/pokaxpoka/deep_Mahalanobis_detector) | 32 | +| [Flow-Grounded Spatial-Temporal Video Prediction from Still Images](http://openaccess.thecvf.com/content_ECCV_2018/html/Yijun_Li_Flow-Grounded_Spatial-Temporal_Video_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Yijunmaverick/FlowGrounded-VideoPrediction) | 32 | +| [Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Lei_Zhu_Bi-directional_Feature_Pyramid_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zijundeng/BDRAR) | 32 | +| [On the Robustness of Semantic Segmentation Models to Adversarial Attacks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Arnab_On_the_Robustness_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hmph/adversarial-attacks) | 31 | +| [Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cui_Large_Scale_Fine-Grained_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/richardaecn/cvpr18-inaturalist-transfer) | 31 | +| [SketchyScene: Richly-Annotated Scene Sketches](http://openaccess.thecvf.com/content_ECCV_2018/html/Changqing_Zou_SketchyScene_Richly-Annotated_Scene_ECCV_2018_paper.html) | ECCV | [code](https://github.com/SketchyScene/SketchyScene) | 31 | +| [Deep Randomized Ensembles for Metric Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Hong_Xuan_Randomized_Ensemble_Embeddings_ECCV_2018_paper.html) | ECCV | [code](https://github.com/littleredxh/DREML) | 30 | +| [Deep High Dynamic Range Imaging with Large Foreground Motions](http://openaccess.thecvf.com/content_ECCV_2018/html/Shangzhe_Wu_Deep_High_Dynamic_ECCV_2018_paper.html) | ECCV | [code](https://github.com/elliottwu/DeepHDR) | 30 | +| [Revisiting Video Saliency: A Large-Scale Benchmark and a New Model](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Revisiting_Video_Saliency_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wenguanwang/DHF1K) | 30 | +| [Blazingly Fast Video Object Segmentation With Pixel-Wise Metric Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Blazingly_Fast_Video_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yuhuayc/fast-vos) | 30 | +| [Deep Model-Based 6D Pose Refinement in RGB](http://openaccess.thecvf.com/content_ECCV_2018/html/Fabian_Manhardt_Deep_Model-Based_6D_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fabi92/eccv18-rgb_pose_refinement) | 30 | +| [TOM-Net: Learning Transparent Object Matting From a Single Image](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_TOM-Net_Learning_Transparent_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/guanyingc/TOM-Net) | 30 | +| [Quaternion Convolutional Neural Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Xuanyu_Zhu_Quaternion_Convolutional_Neural_ECCV_2018_paper.html) | ECCV | [code](https://github.com/TParcollet/Quaternion-Convolutional-Neural-Networks-for-End-to-End-Automatic-Speech-Recognition) | 30 | +| [Densely Connected Attention Propagation for Reading Comprehension](https://nips.cc/Conferences/2018/Schedule?showEvent=11481) | NIPS | [code](https://github.com/vanzytay/NIPS2018_DECAPROP) | 30 | +| [A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising](http://openaccess.thecvf.com/content_ECCV_2018/html/XU_JUN_A_Trilateral_Weighted_ECCV_2018_paper.html) | ECCV | [code](https://github.com/csjunxu/TWSC-ECCV2018) | 30 | +| [Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings](http://proceedings.mlr.press/v80/co-reyes18a.html) | ICML | [code](https://github.com/wyndwarrior/Sectar) | 29 | +| [Video Rain Streak Removal by Multiscale Convolutional Sparse Coding](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Video_Rain_Streak_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/MinghanLi/MS-CSC-Rain-Streak-Removal) | 29 | +| [Recurrent Scene Parsing With Perspective Understanding in the Loop](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kong_Recurrent_Scene_Parsing_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/aimerykong/Recurrent-Scene-Parsing-with-Perspective-Understanding-in-the-loop) | 29 | +| [Single Shot Scene Text Retrieval](http://openaccess.thecvf.com/content_ECCV_2018/html/Lluis_Gomez_Single_Shot_Scene_ECCV_2018_paper.html) | ECCV | [code](https://github.com/lluisgomez/single-shot-str) | 29 | +| [Toward Characteristic-Preserving Image-based Virtual Try-On Network](http://openaccess.thecvf.com/content_ECCV_2018/html/Bochao_Wang_Toward_Characteristic-Preserving_Image-based_ECCV_2018_paper.html) | ECCV | [code](https://github.com/sergeywong/cp-vton) | 29 | +| [Explainable Neural Computation via Stack Neural Module Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Ronghang_Hu_Explainable_Neural_Computation_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ronghanghu/snmn) | 29 | +| [Exploring Disentangled Feature Representation Beyond Face Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Exploring_Disentangled_Feature_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sciencefans/D2AE-Face-Generator) | 29 | +| [Controllable Video Generation With Sparse Trajectories](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hao_Controllable_Video_Generation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zekunhao1995/ControllableVideoGen) | 28 | +| [Layer-structured 3D Scene Inference via View Synthesis](http://openaccess.thecvf.com/content_ECCV_2018/html/Shubham_Tulsiani_Layer-structured_3D_Scene_ECCV_2018_paper.html) | ECCV | [code](https://github.com/google/layered-scene-inference) | 28 | +| [Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation](http://openaccess.thecvf.com/content_ECCV_2018/html/Liang-Chieh_Chen_Encoder-Decoder_with_Atrous_ECCV_2018_paper.html) | ECCV | [code](https://github.com/qixuxiang/deeplabv3plus) | 28 | +| [PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_PiCANet_Learning_Pixel-Wise_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Ugness/PiCANet-Implementation) | 28 | +| [Learning Rich Features for Image Manipulation Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Learning_Rich_Features_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/LarryJiang134/Image_manipulation_detection) | 27 | +| [Fast Video Object Segmentation by Reference-Guided Mask Propagation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Oh_Fast_Video_Object_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/seoungwugoh/RGMP) | 27 | +| [3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration](http://openaccess.thecvf.com/content_ECCV_2018/html/Zi_Jian_Yew_3DFeat-Net_Weakly_Supervised_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yewzijian/3DFeatNet) | 27 | +| [Who Let the Dogs Out? Modeling Dog Behavior From Visual Data](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_Who_Let_the_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ehsanik/dogTorch) | 27 | +| [EC-Net: an Edge-aware Point set Consolidation Network](http://openaccess.thecvf.com/content_ECCV_2018/html/Lequan_Yu_EC-Net_an_Edge-aware_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yulequan/EC-Net) | 27 | +| [Interpretable Intuitive Physics Model](http://openaccess.thecvf.com/content_ECCV_2018/html/Tian_Ye_Interpretable_Intuitive_Physics_ECCV_2018_paper.html) | ECCV | [code](https://github.com/tianye95/interpretable-intuitive-physics-model) | 27 | +| [Learning a Discriminative Feature Network for Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Learning_a_Discriminative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/lxtGH/dfn_seg) | 26 | +| [Partial Transfer Learning With Selective Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Partial_Transfer_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/thuml/SAN) | 26 | +| [Cross-Modal Deep Variational Hand Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Spurr_Cross-Modal_Deep_Variational_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/spurra/vae-hands-3d) | 26 | +| [Between-Class Learning for Image Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tokozume_Between-Class_Learning_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mil-tokyo/bc_learning_image) | 26 | +| [AON: Towards Arbitrarily-Oriented Text Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cheng_AON_Towards_Arbitrarily-Oriented_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/huizhang0110/AON) | 26 | +| [Conditional Image-to-Image Translation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Conditional_Image-to-Image_Translation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/znxlwm/pytorch-Conditional-image-to-image-translation) | 25 | +| [Learning Convolutional Networks for Content-Weighted Image Compression](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Convolutional_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/limuhit/ImageCompression) | 25 | +| [Diversity Regularized Spatiotemporal Attention for Video-Based Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Diversity_Regularized_Spatiotemporal_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ShuangLI59/Diversity-Regularized-Spatiotemporal-Attention) | 25 | +| [Dynamic Multimodal Instance Segmentation Guided by Natural Language Queries](http://openaccess.thecvf.com/content_ECCV_2018/html/Edgar_Margffoy-Tuay_Dynamic_Multimodal_Instance_ECCV_2018_paper.html) | ECCV | [code](https://github.com/BCV-Uniandes/query-objseg) | 25 | +| [CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Batsos_CBMV_A_Coalesced_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kbatsos/CBMV) | 25 | +| [Deep Texture Manifold for Ground Terrain Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xue_Deep_Texture_Manifold_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jiaxue1993/Deep-Encoding-Pooling-Network-DEP-) | 25 | +| [Audio-Visual Event Localization in Unconstrained Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Yapeng_Tian_Audio-Visual_Event_Localization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YapengTian/AVE-ECCV18) | 25 | +| [First Order Generative Adversarial Networks](http://proceedings.mlr.press/v80/seward18a.html) | ICML | [code](https://github.com/zalandoresearch/first_order_gan) | 25 | +| [Visual Coreference Resolution in Visual Dialog using Neural Module Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Satwik_Kottur_Visual_Coreference_Resolution_ECCV_2018_paper.html) | ECCV | [code](https://github.com/facebookresearch/corefnmn) | 25 | +| [SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Faraone_SYQ_Learning_Symmetric_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/julianfaraone/SYQ) | 24 | +| [Deep Reinforcement Learning of Marked Temporal Point Processes](http://arxiv.org/abs/1805.09360v1) | NIPS | [code](https://github.com/Networks-Learning/tpprl) | 24 | +| [Explicit Inductive Bias for Transfer Learning with Convolutional Networks](http://proceedings.mlr.press/v80/li18a.html) | ICML | [code](https://github.com/holyseven/TransferLearningClassification) | 24 | +| [LEGO: Learning Edge With Geometry All at Once by Watching Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_LEGO_Learning_Edge_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhenheny/LEGO) | 24 | +| [Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes](http://openaccess.thecvf.com/content_ECCV_2018/html/Fangneng_Zhan_Verisimilar_Image_Synthesis_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fnzhan/Verisimilar-Image-Synthesis-for-Accurate-Detection-and-Recognition-of-Texts-in-Scenes) | 24 | +| [Multi-Agent Diverse Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ghosh_Multi-Agent_Diverse_Generative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/arnabgho/MADGAN) | 23 | +| [Face Aging With Identity-Preserved Conditional Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Face_Aging_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/dawei6875797/Face-Aging-with-Identity-Preserved-Conditional-Generative-Adversarial-Networks) | 23 | +| [Learning to Separate Object Sounds by Watching Unlabeled Video](http://openaccess.thecvf.com/content_ECCV_2018/html/Ruohan_Gao_Learning_to_Separate_ECCV_2018_paper.html) | ECCV | [code](https://github.com/rhgao/separating-object-sounds) | 23 | +| [Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search](http://proceedings.mlr.press/v80/suganuma18a.html) | ICML | [code](https://github.com/sg-nm/Evolutionary-Autoencoders) | 23 | +| [To Trust Or Not To Trust A Classifier](http://arxiv.org/abs/1805.11783v1) | NIPS | [code](https://github.com/google/TrustScore) | 23 | +| [Im2Flow: Motion Hallucination From Static Images for Action Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gao_Im2Flow_Motion_Hallucination_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/rhgao/Im2Flow) | 22 | +| [ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_ISTA-Net_Interpretable_Optimization-Inspired_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jianzhangcs/ISTA-Net) | 22 | +| [Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Hallucinated-IQA_No-Reference_Image_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kwanyeelin/HIQA) | 22 | +| [Anonymous Walk Embeddings](http://proceedings.mlr.press/v80/ivanov18a.html) | ICML | [code](https://github.com/nd7141/AWE) | 22 | +| [Learning to Multitask](http://arxiv.org/abs/1805.07541v1) | NIPS | [code](https://github.com/jfutoma/MGP-RNN) | 22 | +| [CondenseNet: An Efficient DenseNet Using Learned Group Convolutions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_CondenseNet_An_Efficient_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/markdtw/condensenet-tensorflow) | 22 | +| [HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_HashGAN_Deep_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/thuml/HashGAN) | 22 | +| [Hierarchical Relational Networks for Group Activity Recognition and Retrieval](http://openaccess.thecvf.com/content_ECCV_2018/html/Mostafa_Ibrahim_Hierarchical_Relational_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/mostafa-saad/hierarchical-relational-network) | 22 | +| [Collaborative and Adversarial Network for Unsupervised Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Collaborative_and_Adversarial_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mahfuj9346449/iCAN) | 22 | +| [Geometry-Aware Scene Text Detection With Instance Transformation Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Geometry-Aware_Scene_Text_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zlmzju/itn) | 22 | +| [Learning to Promote Saliency Detectors](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zeng_Learning_to_Promote_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zengxianyu/lps) | 21 | +| [CSGNet: Neural Shape Parser for Constructive Solid Geometry](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sharma_CSGNet_Neural_Shape_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Hippogriff/CSGNet) | 21 | +| [Local Spectral Graph Convolution for Point Set Feature Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Chu_Wang_Local_Spectral_Graph_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fate3439/LocalSpecGCN) | 21 | +| [HiDDeN: Hiding Data with Deep Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Jiren_Zhu_HiDDeN_Hiding_Data_ECCV_2018_paper.html) | ECCV | [code](https://github.com/jirenz/HiDDeN) | 21 | +| [GraphBit: Bitwise Interaction Mining via Deep Reinforcement Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Duan_GraphBit_Bitwise_Interaction_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/duanyq14/GraphBit) | 20 | +| [Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Stacked_Conditional_Generative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/DeepInsight-PCALab/ST-CGAN) | 20 | +| [Fully-Convolutional Point Networks for Large-Scale Point Clouds](http://openaccess.thecvf.com/content_ECCV_2018/html/Dario_Rethage_Fully-Convolutional_Point_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/drethage/fully-convolutional-point-network) | 20 | +| [Learning Superpixels With Segmentation-Aware Affinity Loss](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tu_Learning_Superpixels_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wctu/SEAL) | 20 | +| [Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Zero-Shot_Visual_Recognition_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zjuchenlong/sp-aen.cvpr18) | 20 | +| [Crowd Counting With Deep Negative Correlation Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shi_Crowd_Counting_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/shizenglin/Deep-NCL) | 20 | +| [Dimensionality-Driven Learning with Noisy Labels](http://proceedings.mlr.press/v80/ma18d.html) | ICML | [code](https://github.com/xingjunm/dimensionality-driven-learning) | 20 | +| [Objects that Sound](http://openaccess.thecvf.com/content_ECCV_2018/html/Relja_Arandjelovic_Objects_that_Sound_ECCV_2018_paper.html) | ECCV | [code](https://github.com/rohitrango/objects-that-sound) | 20 | +| [Deep Expander Networks: Efficient Deep Networks from Graph Theory](http://openaccess.thecvf.com/content_ECCV_2018/html/Ameya_Prabhu_Deep_Expander_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/DrImpossible/Deep-Expander-Networks) | 19 | +| [Low-Shot Learning With Large-Scale Diffusion](http://openaccess.thecvf.com/content_cvpr_2018/papers/Douze_Low-Shot_Learning_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/facebookresearch/low-shot-with-diffusion) | 19 | +| [Low-Shot Learning With Imprinted Weights](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Low-Shot_Learning_With_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/YU1ut/imprinted-weights) | 19 | +| [Cross-Domain Self-Supervised Multi-Task Feature Learning Using Synthetic Imagery](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ren_Cross-Domain_Self-Supervised_Multi-Task_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jason718/game-feature-learning) | 19 | +| [Learning Descriptor Networks for 3D Shape Synthesis and Analysis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xie_Learning_Descriptor_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jianwen-xie/3DDescriptorNet) | 19 | +| [Disentangling Factors of Variation with Cycle-Consistent Variational Auto-Encoders](http://openaccess.thecvf.com/content_ECCV_2018/html/Ananya_Harsh_Jha_Disentangling_Factors_of_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ananyahjha93/cycle-consistent-vae) | 19 | +| [CTAP: Complementary Temporal Action Proposal Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Jiyang_Gao_CTAP_Complementary_Temporal_ECCV_2018_paper.html) | ECCV | [code](https://github.com/jiyanggao/CTAP) | 18 | +| [DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors](http://arxiv.org/abs/1805.07445v3) | NIPS | [code](https://github.com/dojoteef/dvae) | 18 | +| [Conditional Image-Text Embedding Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Bryan_Plummer_Conditional_Image-Text_Embedding_ECCV_2018_paper.html) | ECCV | [code](https://github.com/BryanPlummer/cite) | 18 | +| [EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth From Light Field Images](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shin_EPINET_A_Fully-Convolutional_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chshin10/epinet) | 18 | +| [Glimpse Clouds: Human Activity Recognition From Unstructured Feature Points](http://openaccess.thecvf.com/content_cvpr_2018/papers/Baradel_Glimpse_Clouds_Human_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/fabienbaradel/glimpse_clouds) | 18 | +| [Bayesian Optimization of Combinatorial Structures](http://proceedings.mlr.press/v80/baptista18a.html) | ICML | [code](https://github.com/baptistar/BOCS) | 18 | +| [FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Verma_FeaStNet_Feature-Steered_Graph_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/nitika-verma/FeaStNet) | 18 | +| [Learning Type-Aware Embeddings for Fashion Compatibility](http://openaccess.thecvf.com/content_ECCV_2018/html/Mariya_Vasileva_Learning_Type-Aware_Embeddings_ECCV_2018_paper.html) | ECCV | [code](https://github.com/mvasil/fashion-compatibility) | 17 | +| [Sliced Wasserstein Distance for Learning Gaussian Mixture Models](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kolouri_Sliced_Wasserstein_Distance_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/skolouri/swgmm) | 17 | +| [Revisiting Deep Intrinsic Image Decompositions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Fan_Revisiting_Deep_Intrinsic_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/fqnchina/IntrinsicImage) | 17 | +| [A Spectral Approach to Gradient Estimation for Implicit Distributions](http://proceedings.mlr.press/v80/shi18a.html) | ICML | [code](https://github.com/thjashin/spectral-stein-grad) | 17 | +| [Hierarchical Novelty Detection for Visual Object Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_Hierarchical_Novelty_Detection_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kibok90/cvpr2018-hnd) | 17 | +| [Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies](http://openaccess.thecvf.com/content_cvpr_2018/papers/Joo_Total_Capture_A_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Myzhencai/Total-Capture) | 17 | +| [Learning Generative ConvNets via Multi-Grid Modeling and Sampling](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gao_Learning_Generative_ConvNets_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ruiqigao/Multigrid_learning) | 17 | +| [Learning 3D Shape Completion From Laser Scan Data With Weak Supervision](http://openaccess.thecvf.com/content_cvpr_2018/papers/Stutz_Learning_3D_Shape_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/davidstutz/cvpr2018-shape-completion) | 17 | +| [Triplet Loss in Siamese Network for Object Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Xingping_Dong_Triplet_Loss_with_ECCV_2018_paper.html) | ECCV | [code](https://github.com/shenjianbing/TripletTracking) | 17 | +| [Adversarial Attack on Graph Structured Data](http://proceedings.mlr.press/v80/dai18b.html) | ICML | [code](https://github.com/Hanjun-Dai/graph_adversarial_attack) | 17 | +| [Arbitrary Style Transfer With Deep Feature Reshuffle](http://openaccess.thecvf.com/content_cvpr_2018/papers/Gu_Arbitrary_Style_Transfer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/msracver/Style-Feature-Reshuffle) | 17 | +| [Visual Question Reasoning on General Dependency Tree](http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Visual_Question_Reasoning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/bezorro/ACMN-Pytorch) | 17 | +| [Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition](http://openaccess.thecvf.com/content_ECCV_2018/html/Huang_Predicting_Gaze_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hyf015/egocentric-gaze-prediction) | 16 | +| [Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks](https://arxiv.org/abs/1802.04034) | NIPS | [code](https://github.com/ytsmiling/lmt) | 16 | +| [Coded Sparse Matrix Multiplication](http://proceedings.mlr.press/v80/wang18e.html) | ICML | [code](https://github.com/ksopyla/CudaDotProd) | 16 | +| [Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ding_Weakly-Supervised_Action_Segmentation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Zephyr-D/TCFPN-ISBA) | 16 | +| [Recovering 3D Planes from a Single Image via Convolutional Neural Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Fengting_Yang_Recovering_3D_Planes_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fuy34/planerecover) | 16 | +| [SegStereo: Exploiting Semantic Information for Disparity Estimation](http://openaccess.thecvf.com/content_ECCV_2018/html/Guorun_Yang_SegStereo_Exploiting_Semantic_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yangguorun/SegStereo) | 16 | +| [Functional Gradient Boosting based on Residual Network Perception](http://proceedings.mlr.press/v80/nitanda18a.html) | ICML | [code](https://github.com/anitan0925/ResFGB) | 16 | +| [NAG: Network for Adversary Generation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mopuri_NAG_Network_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/val-iisc/nag) | 16 | +| [Generative Probabilistic Novelty Detection with Adversarial Autoencoders](http://arxiv.org/abs/1807.02588v1) | NIPS | [code](https://github.com/podgorskiy/GPND) | 16 | +| [Hashing as Tie-Aware Learning to Rank](http://openaccess.thecvf.com/content_cvpr_2018/papers/He_Hashing_as_Tie-Aware_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kunhe/TALR) | 15 | +| [Pose Proposal Networks](http://openaccess.thecvf.com/content_ECCV_2018/html/Sekii_Pose_Proposal_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/salihkaragoz/MultiPerson-pose-estimation) | 15 | +| [Convolutional Sequence to Sequence Model for Human Dynamics](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Convolutional_Sequence_to_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chaneyddtt/Convolutional-Sequence-to-Sequence-Model-for-Human-Dynamics) | 15 | +| [Joint Pose and Expression Modeling for Facial Expression Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Joint_Pose_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/FFZhang1231/Facial-expression-recognition) | 15 | +| [Grounding Referring Expressions in Images by Variational Context](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Grounding_Referring_Expressions_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yuleiniu/vc) | 15 | +| [Rethinking the Form of Latent States in Image Captioning](http://openaccess.thecvf.com/content_ECCV_2018/html/Bo_Dai_Rethinking_the_Form_ECCV_2018_paper.html) | ECCV | [code](https://github.com/doubledaibo/2dcaption_eccv2018) | 15 | +| [Open Set Domain Adaptation by Backpropagation](http://openaccess.thecvf.com/content_ECCV_2018/html/Kuniaki_Saito_Adversarial_Open_Set_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YU1ut/openset-DA) | 15 | +| [Neural Sign Language Translation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Camgoz_Neural_Sign_Language_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/neccam/nslt) | 15 | +| [SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters](http://openaccess.thecvf.com/content_ECCV_2018/html/Yifan_Xu_SpiderCNN_Deep_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/xyf513/SpiderCNN) | 15 | +| [Efficient Neural Audio Synthesis](http://proceedings.mlr.press/v80/kalchbrenner18a.html) | ICML | [code](https://github.com/fedden/TensorFlow-Efficient-Neural-Audio-Synthesis) | 15 | +| [Deep Learning Under Privileged Information Using Heteroscedastic Dropout](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lambert_Deep_Learning_Under_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/johnwlambert/dlupi-heteroscedastic-dropout) | 14 | +| [Image Transformer](http://proceedings.mlr.press/v80/parmar18a.html) | ICML | [code](https://github.com/ssingal05/ImageTransformer) | 14 | +| [Learning to Understand Image Blur](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Learning_to_Understand_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Lotuslisa/Understand_Image_Blur) | 14 | +| [Learning and Using the Arrow of Time](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wei_Learning_and_Using_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/donglaiw/AoT_TCAM) | 14 | +| [Action Sets: Weakly Supervised Action Segmentation Without Ordering Constraints](http://openaccess.thecvf.com/content_cvpr_2018/papers/Richard_Action_Sets_Weakly_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alexanderrichard/action-sets) | 14 | +| [Learning to Forecast and Refine Residual Motion for Image-to-Video Generation](http://openaccess.thecvf.com/content_ECCV_2018/html/Long_Zhao_Learning_to_Forecast_ECCV_2018_paper.html) | ECCV | [code](https://github.com/garyzhao/FRGAN) | 14 | +| [Multi-Scale Weighted Nuclear Norm Image Restoration](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yair_Multi-Scale_Weighted_Nuclear_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/noamyairTC/MSWNNM) | 14 | +| [Synthesizing Robust Adversarial Examples](http://proceedings.mlr.press/v80/athalye18b.html) | ICML | [code](https://github.com/prabhant/synthesizing-robust-adversarial-examples) | 13 | +| [Fine-Grained Visual Categorization using Meta-Learning Optimization with Sample Selection of Auxiliary Data](http://openaccess.thecvf.com/content_ECCV_2018/html/Yabin_Zhang_Fine-Grained_Visual_Categorization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YabinZhang1994/MetaFGNet) | 13 | +| [Assessing Generative Models via Precision and Recall](http://arxiv.org/abs/1806.00035v1) | NIPS | [code](https://github.com/msmsajjadi/precision-recall-distributions) | 13 | +| [Deep Diffeomorphic Transformer Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Detlefsen_Deep_Diffeomorphic_Transformer_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/SkafteNicki/ddtn) | 13 | +| [Learning by Asking Questions](http://openaccess.thecvf.com/content_cvpr_2018/papers/Misra_Learning_by_Asking_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yanghoonkim/question_generation) | 13 | +| [Towards Human-Machine Cooperation: Self-Supervised Sample Mining for Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Towards_Human-Machine_Cooperation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yanxp/SSM) | 13 | +| [Variational Autoencoders for Deforming 3D Mesh Models](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tan_Variational_Autoencoders_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/aldehydecho/Mesh-VAE) | 13 | +| [Min-Entropy Latent Model for Weakly Supervised Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wan_Min-Entropy_Latent_Model_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Winfrand/MELM) | 13 | +| [Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Anderson_Bottom-Up_and_Top-Down_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Wentong-DST/up-down-captioner) | 13 | +| [Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace](http://proceedings.mlr.press/v80/lee18a.html) | ICML | [code](https://github.com/yoonholee/MT-net) | 13 | +| [Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_a_Discriminative_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hubeihubei/DFL-CNN-pytorch) | 13 | +| [Finding Influential Training Samples for Gradient Boosted Decision Trees](http://proceedings.mlr.press/v80/sharchilev18a.html) | ICML | [code](https://github.com/bsharchilev/influence_boosting) | 13 | +| [Gesture Recognition: Focus on the Hands](http://openaccess.thecvf.com/content_cvpr_2018/papers/Narayana_Gesture_Recognition_Focus_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/beckabec/HandDetection) | 12 | +| [Cross-View Image Synthesis Using Conditional GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Regmi_Cross-View_Image_Synthesis_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kregmi/cross-view-image-synthesis) | 12 | +| [Joint Optimization Framework for Learning With Noisy Labels](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tanaka_Joint_Optimization_Framework_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/DaikiTanaka-UT/JointOptimization) | 12 | +| [Future Person Localization in First-Person Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yagi_Future_Person_Localization_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/takumayagi/fpl) | 12 | +| [AutoLoc: Weakly-supervised Temporal Action Localization in Untrimmed Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Shou_AutoLoc_Weakly-supervised_Temporal_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zhengshou/AutoLoc) | 12 | +| [Learning Transferable Architectures for Scalable Image Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zoph_Learning_Transferable_Architectures_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/aussetg/nasnet.pytorch) | 12 | +| [Clipped Action Policy Gradient](http://proceedings.mlr.press/v80/fujita18a.html) | ICML | [code](https://github.com/pfnet-research/capg) | 12 | +| [Mix and Match Networks: Encoder-Decoder Alignment for Zero-Pair Image Translation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Mix_and_Match_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/yaxingwang/Mix-and-match-networks) | 12 | +| [Decouple Learning for Parameterized Image Operators](http://openaccess.thecvf.com/content_ECCV_2018/html/Qingnan_Fan_Learning_to_Learn_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fqnchina/DecoupleLearning) | 12 | +| [Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction](http://proceedings.mlr.press/v80/qi18a.html) | ICML | [code](https://github.com/SiyuanQi/generalized-earley-parser) | 12 | +| [Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models](https://arxiv.org/abs/1808.04768) | NIPS | [code](https://github.com/neitzal/adaptive-skip-intervals) | 12 | +| [AMNet: Memorability Estimation With Attention](http://openaccess.thecvf.com/content_cvpr_2018/papers/Fajtl_AMNet_Memorability_Estimation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ok1zjf/AMNet) | 12 | +| [Adversarial Time-to-Event Modeling](http://proceedings.mlr.press/v80/chapfuwa18a.html) | ICML | [code](https://github.com/paidamoyo/adversarial_time_to_event) | 12 | +| [Reversible Recurrent Neural Networks](nan) | NIPS | [code](https://github.com/gan3sh500/revrnn) | 12 | +| [Human Pose Estimation With Parsing Induced Learner](http://openaccess.thecvf.com/content_cvpr_2018/papers/Nie_Human_Pose_Estimation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/NieXC/pytorch-pil) | 11 | +| [ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking](http://openaccess.thecvf.com/content_ECCV_2018/html/Oliver_Groth_ShapeStacks_Learning_Vision-Based_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ogroth/shapestacks) | 11 | +| [A Joint Sequence Fusion Model for Video Question Answering and Retrieval](http://openaccess.thecvf.com/content_ECCV_2018/html/Youngjae_Yu_A_Joint_Sequence_ECCV_2018_paper.html) | ECCV | [code](https://github.com/yj-yu/lsmdc) | 11 | +| [Learning Face Age Progression: A Pyramid Architecture of GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Learning_Face_Age_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ajithvallabai/Pyramid-Architecture-of-GANs) | 11 | +| [Robust Physical-World Attacks on Deep Learning Visual Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Eykholt_Robust_Physical-World_Attacks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/evtimovi/robust_physical_perturbations) | 11 | +| [High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach](http://proceedings.mlr.press/v80/pearce18a.html) | ICML | [code](https://github.com/TeaPearce/Deep_Learning_Prediction_Intervals) | 11 | +| [Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory](http://proceedings.mlr.press/v80/amit18a.html) | ICML | [code](https://github.com/ron-amit/meta-learning-adjusting-priors) | 11 | +| [Multimodal Explanations: Justifying Decisions and Pointing to the Evidence](http://openaccess.thecvf.com/content_cvpr_2018/papers/Park_Multimodal_Explanations_Justifying_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Seth-Park/MultimodalExplanations) | 11 | +| [Accelerating Natural Gradient with Higher-Order Invariance](http://proceedings.mlr.press/v80/song18a.html) | ICML | [code](https://github.com/ermongroup/higher_order_invariance) | 11 | +| [Hierarchical Multi-Label Classification Networks](http://proceedings.mlr.press/v80/wehrmann18a.html) | ICML | [code](https://github.com/omoju/receiptdID) | 11 | +| [Convolutional Image Captioning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Aneja_Convolutional_Image_Captioning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/eladhoffer/captionGeneration.torch) | 11 | +| [Boosting Domain Adaptation by Discovering Latent Domains](http://openaccess.thecvf.com/content_cvpr_2018/papers/Mancini_Boosting_Domain_Adaptation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/mancinimassimiliano/latent_domains_DA) | 11 | +| [Logo Synthesis and Manipulation With Clustered Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sage_Logo_Synthesis_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/alex-sage/logo-gen) | 10 | +| [PacGAN: The power of two samples in generative adversarial networks](http://arxiv.org/abs/1712.04086v2) | NIPS | [code](https://github.com/fjxmlzn/PacGAN) | 10 | +| [Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Long_Attention_Clusters_Purely_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/pomonam/AttentionCluster) | 10 | +| [End-to-End Incremental Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Francisco_M._Castro_End-to-End_Incremental_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/fmcp/EndToEndIncrementalLearning) | 10 | +| [Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lyu_Multi-Oriented_Scene_Text_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JK-Rao/Corner_Segmentation_TextDetection) | 10 | +| [On GANs and GMMs](http://arxiv.org/abs/1805.12462v1) | NIPS | [code](https://github.com/eitanrich/gans-n-gmms) | 10 | +| [Salient Object Detection Driven by Fixation Prediction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Salient_Object_Detection_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/wenguanwang/ASNet) | 9 | +| [Semantic Video Segmentation by Gated Recurrent Flow Propagation](http://openaccess.thecvf.com/content_cvpr_2018/papers/Nilsson_Semantic_Video_Segmentation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/D-Nilsson/GRFP) | 9 | +| [Constraint-Aware Deep Neural Network Compression](http://openaccess.thecvf.com/content_ECCV_2018/html/Changan_Chen_Constraints_Matter_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ChanganVR/ConstraintAwareCompression) | 9 | +| [Statistically-motivated Second-order Pooling](http://openaccess.thecvf.com/content_ECCV_2018/html/Kaicheng_Yu_Statistically-motivated_Second-order_Pooling_ECCV_2018_paper.html) | ECCV | [code](https://github.com/kcyu2014/smsop) | 9 | +| [Excitation Backprop for RNNs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bargal_Excitation_Backprop_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sbargal/Caffe-ExcitationBP-RNNs) | 9 | +| [Analyzing Uncertainty in Neural Machine Translation](http://proceedings.mlr.press/v80/ott18a.html) | ICML | [code](https://github.com/facebookresearch/analyzing-uncertainty-nmt) | 9 | +| [Learning Dynamics of Linear Denoising Autoencoders](http://proceedings.mlr.press/v80/pretorius18a.html) | ICML | [code](https://github.com/arnupretorius/lindaedynamics_icml2018) | 9 | +| [Saliency Detection in 360° Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Ziheng_Zhang_Saliency_Detection_in_ECCV_2018_paper.html) | ECCV | [code](https://github.com/xuyanyu-shh/Saliency-detection-in-360-video) | 9 | +| [Density Adaptive Point Set Registration](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lawin_Density_Adaptive_Point_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/felja633/DARE) | 9 | +| [Decoupled Parallel Backpropagation with Convergence Guarantee](http://proceedings.mlr.press/v80/huo18a.html) | ICML | [code](https://github.com/slowbull/DDG) | 9 | +| [Classification from Pairwise Similarity and Unlabeled Data](http://proceedings.mlr.press/v80/bao18a.html) | ICML | [code](https://github.com/levelfour/SU_Classification) | 9 | +| [oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis](http://proceedings.mlr.press/v80/ainsworth18a.html) | ICML | [code](https://github.com/samuela/oi-vae) | 9 | +| [Modeling Sparse Deviations for Compressed Sensing using Generative Models](http://proceedings.mlr.press/v80/dhar18a.html) | ICML | [code](https://github.com/ermongroup/sparse_gen) | 9 | +| [Pixels, Voxels, and Views: A Study of Shape Representations for Single View 3D Object Shape Prediction](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shin_Pixels_Voxels_and_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/daeyun/object-shapes-cvpr18) | 9 | +| [Towards Open-Set Identity Preserving Face Synthesis](http://openaccess.thecvf.com/content_cvpr_2018/papers/Bao_Towards_Open-Set_Identity_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chloeguoqing/Towards-Open-Set-Identity-Preserving-Face-Synthesis) | 9 | +| [Five-Point Fundamental Matrix Estimation for Uncalibrated Cameras](http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Five-Point_Fundamental_Matrix_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/danini/five-point-fundamental) | 8 | +| [BourGAN: Generative Networks with Metric Embeddings](https://arxiv.org/abs/1805.07674) | NIPS | [code](https://github.com/a554b554/BourGAN) | 8 | +| [Fast Information-theoretic Bayesian Optimisation](http://proceedings.mlr.press/v80/ru18a.html) | ICML | [code](https://github.com/rubinxin/FITBO) | 8 | +| [Deep Variational Reinforcement Learning for POMDPs](http://proceedings.mlr.press/v80/igl18a.html) | ICML | [code](https://github.com/oxwhirl/Deep-Variational-Reinforcement-Learning) | 8 | +| [Specular-to-Diffuse Translation for Multi-View Reconstruction](http://openaccess.thecvf.com/content_ECCV_2018/html/Shihao_Wu_Specular-to-Diffuse_Translation_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/wsh312/S2Dnet) | 8 | +| [Dynamic Conditional Networks for Few-Shot Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Fang_Zhao_Dynamic_Conditional_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ZhaoJ9014/Dynamic-Conditional-Networks-for-Few-Shot-Learning.pytorch) | 8 | +| [Learning Facial Action Units From Web Images With Scalable Weakly Supervised Clustering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhao_Learning_Facial_Action_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zkl20061823/WSC) | 8 | +| [High-Resolution Image Synthesis and Semantic Manipulation With Conditional GANs](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_High-Resolution_Image_Synthesis_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/chenxli/High-Resolution-Image-Synthesis-and-Semantic-Manipulation-with-Conditional-GANsl-) | 8 | +| [Deep Defense: Training DNNs with Improved Adversarial Robustness](http://arxiv.org/abs/1803.00404v2) | NIPS | [code](https://github.com/ZiangYan/deepdefense.pytorch) | 8 | +| [Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations](http://proceedings.mlr.press/v80/chen18g.html) | ICML | [code](https://github.com/chentingpc/kdcode-lm) | 8 | +| [Light Structure from Pin Motion: Simple and Accurate Point Light Calibration for Physics-based Modeling](http://openaccess.thecvf.com/content_ECCV_2018/html/Hiroaki_Santo_Light_Structure_from_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hiroaki-santo/light-structure-from-pin-motion) | 7 | +| [Non-metric Similarity Graphs for Maximum Inner Product Search](nan) | NIPS | [code](https://github.com/stanis-morozov/ip-nsw) | 7 | +| [Towards Realistic Predictors](http://openaccess.thecvf.com/content_ECCV_2018/html/Pei_Wang_Towards_Realistic_Predictors_ECCV_2018_paper.html) | ECCV | [code](https://github.com/peiwang062/towards-realistic-predictors) | 7 | +| [Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation](nan) | NIPS | [code](https://github.com/rwenqi/NBD-GLRA) | 7 | +| [Don’t Just Assume Look and Answer: Overcoming Priors for Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Agrawal_Dont_Just_Assume_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/AishwaryaAgrawal/GVQA) | 7 | +| [Learning Dual Convolutional Neural Networks for Low-Level Vision](http://openaccess.thecvf.com/content_cvpr_2018/papers/Pan_Learning_Dual_Convolutional_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/galad-loth/DualCNN-TF) | 7 | +| [The Mirage of Action-Dependent Baselines in Reinforcement Learning](http://proceedings.mlr.press/v80/tucker18a.html) | ICML | [code](https://github.com/brain-research/mirage-rl) | 7 | +| [DVQA: Understanding Data Visualizations via Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kafle_DVQA_Understanding_Data_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kushalkafle/DVQA_dataset) | 7 | +| [A Two-Step Disentanglement Method](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hadad_A_Two-Step_Disentanglement_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/naamahadad/A-Two-Step-Disentanglement-Method) | 7 | +| [Detecting and Correcting for Label Shift with Black Box Predictors](http://proceedings.mlr.press/v80/lipton18a.html) | ICML | [code](https://github.com/zackchase/label-shift) | 7 | +| [Conditional Prior Networks for Optical Flow](http://openaccess.thecvf.com/content_ECCV_2018/html/Yanchao_Yang_Conditional_Prior_Networks_ECCV_2018_paper.html) | ECCV | [code](https://github.com/YanchaoYang/Conditional-Prior-Networks) | 7 | +| [Generative Adversarial Learning Towards Fast Weakly Supervised Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Generative_Adversarial_Learning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/shenyunhang/GAL-fWSD) | 7 | +| [Adversarial Learning with Local Coordinate Coding](http://proceedings.mlr.press/v80/cao18a.html) | ICML | [code](https://github.com/guoyongcs/LCCGAN) | 7 | +| [Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kuen_Stochastic_Downsampling_for_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xternalz/SDPoint) | 7 | +| [AttnGAN: Fine-Grained Text to Image Generation With Attentional Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_AttnGAN_Fine-Grained_Text_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Wentong-DST/attn-gan) | 7 | +| [Learning to Explain: An Information-Theoretic Perspective on Model Interpretation](http://proceedings.mlr.press/v80/chen18j.html) | ICML | [code](https://github.com/nickvosk/acl2015-dataset-learning-to-explain-entity-relationships) | 7 | +| [Banach Wasserstein GAN](http://arxiv.org/abs/1806.06621v1) | NIPS | [code](https://github.com/adler-j/bwgan) | 7 | +| [Gradually Updated Neural Networks for Large-Scale Image Recognition](http://proceedings.mlr.press/v80/qiao18b.html) | ICML | [code](https://github.com/joe-siyuan-qiao/GUNN) | 7 | +| [Learning Steady-States of Iterative Algorithms over Graphs](http://proceedings.mlr.press/v80/dai18a.html) | ICML | [code](https://github.com/Hanjun-Dai/steady_state_embedding) | 7 | +| [Progressive Attention Guided Recurrent Network for Salient Object Detection](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Progressive_Attention_Guided_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhangxiaoning666/PAGR) | 7 | +| [Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains](http://openaccess.thecvf.com/content_cvpr_2018/papers/Pang_Zoom_and_Learn_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/Artifineuro/zole) | 6 | +| [Unsupervised holistic image generation from key local patches](http://openaccess.thecvf.com/content_ECCV_2018/html/Donghoon_Lee_Unsupervised_holistic_image_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hellbell/KeyPatchGan) | 6 | +| [Inner Space Preserving Generative Pose Machine](http://openaccess.thecvf.com/content_ECCV_2018/html/Shuangjun_Liu_Inner_Space_Preserving_ECCV_2018_paper.html) | ECCV | [code](https://github.com/ostadabbas/isp-gpm) | 6 | +| [Bilevel Programming for Hyperparameter Optimization and Meta-Learning](http://proceedings.mlr.press/v80/franceschi18a.html) | ICML | [code](https://github.com/prolearner/hyper-representation) | 6 | +| [Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_Optical_Flow_Guided_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/kitsune999/Optical-Flow-Guided-Feature) | 6 | +| [Breaking the Activation Function Bottleneck through Adaptive Parameterization](https://arxiv.org/abs/1805.08574) | NIPS | [code](https://github.com/flennerhag/alstm) | 6 | +| [Ultra Large-Scale Feature Selection using Count-Sketches](http://proceedings.mlr.press/v80/aghazadeh18a.html) | ICML | [code](https://github.com/rdspring1/MISSION) | 6 | +| [Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Dynamic_Scene_Deblurring_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhjwustc/cvpr18_rnn_deblur_matcaffe) | 6 | +| [Orthogonally Decoupled Variational Gaussian Processes](http://arxiv.org/abs/1809.08820v1) | NIPS | [code](https://github.com/hughsalimbeni/orth_decoupled_var_gps) | 6 | +| [Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design](http://proceedings.mlr.press/v80/lyu18a.html) | ICML | [code](https://github.com/Alaya-in-Matrix/MACE) | 6 | +| [A Modulation Module for Multi-task Learning with Applications in Image Retrieval](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiangyun_Zhao_A_Modulation_Module_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Zhaoxiangyun/Multi-Task-Modulation-Module) | 6 | +| [A Memory Network Approach for Story-Based Temporal Summarization of 360° Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_A_Memory_Network_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/sangho-vision/PFMN) | 6 | +| [Towards Effective Low-Bitwidth Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhuang_Towards_Effective_Low-Bitwidth_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/nowgood/QuantizeCNNModel) | 5 | +| [Disentangling Factors of Variation by Mixing Them](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Disentangling_Factors_of_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/HuQyang/Disentangling-Factors-of-Variation-by-Mixing-Them) | 5 | +| [Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web Prior](http://openaccess.thecvf.com/content_ECCV_2018/html/Sijia_Cai_Weakly-supervised_Video_Summarization_ECCV_2018_paper.html) | ECCV | [code](https://github.com/cssjcai/vesd) | 5 | +| [Learning Longer-term Dependencies in RNNs with Auxiliary Losses](http://proceedings.mlr.press/v80/trinh18a.html) | ICML | [code](https://github.com/belepi93/rnn-auxiliary-loss) | 5 | +| [Contour Knowledge Transfer for Salient Object Detection](http://openaccess.thecvf.com/content_ECCV_2018/html/Xin_Li_Contour_Knowledge_Transfer_ECCV_2018_paper.html) | ECCV | [code](https://github.com/lixin666/C2SNet) | 5 | +| [HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning](http://openaccess.thecvf.com/content_ECCV_2018/html/Thomas_Robert_HybridNet_Classification_and_ECCV_2018_paper.html) | ECCV | [code](https://github.com/dakshitagrawal97/HybridNet) | 5 | +| [Sidekick Policy Learning for Active Visual Exploration](http://openaccess.thecvf.com/content_ECCV_2018/html/Santhosh_Kumar_Ramakrishnan_Sidekick_Policy_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/srama2512/sidekicks) | 5 | +| [Learning to Localize Sound Source in Visual Scenes](http://openaccess.thecvf.com/content_cvpr_2018/papers/Senocak_Learning_to_Localize_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/ardasnck/learning_to_localize_sound) | 5 | +| [Neural Architecture Optimization](http://arxiv.org/abs/1808.07233v3) | NIPS | [code](https://github.com/dicarlolab/archconvnets) | 5 | +| [COLA: Decentralized Linear Learning](nan) | NIPS | [code](https://github.com/epfml/cola) | 5 | +| [Diverse and Coherent Paragraph Generation from Images](http://openaccess.thecvf.com/content_ECCV_2018/html/Moitreya_Chatterjee_Diverse_and_Coherent_ECCV_2018_paper.html) | ECCV | [code](https://github.com/metro-smiles/CapG_RevG_Code) | 5 | +| [DRACO: Byzantine-resilient Distributed Training via Redundant Gradients](http://proceedings.mlr.press/v80/chen18l.html) | ICML | [code](https://github.com/hwang595/Draco) | 5 | +| [Inter and Intra Topic Structure Learning with Word Embeddings](http://proceedings.mlr.press/v80/zhao18a.html) | ICML | [code](https://github.com/ethanhezhao/WEDTM) | 5 | +| [Estimating the Success of Unsupervised Image to Image Translation](http://openaccess.thecvf.com/content_ECCV_2018/html/Lior_Wolf_Estimating_the_Success_ECCV_2018_paper.html) | ECCV | [code](https://github.com/sagiebenaim/gan_bound) | 5 | +| [Dynamic-Structured Semantic Propagation Network](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liang_Dynamic-Structured_Semantic_Propagation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/limberc/DSSPN) | 5 | +| [The Description Length of Deep Learning models](https://arxiv.org/abs/1802.07044) | NIPS | [code](https://github.com/leonardblier/descriptionlengthdeeplearning) | 5 | +| [Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving](http://openaccess.thecvf.com/content_ECCV_2018/html/Peiliang_LI_Stereo_Vision-based_Semantic_ECCV_2018_paper.html) | ECCV | [code](https://github.com/zhanghanduo/stereo_semantic_mapping) | 5 | +| [Blind Justice: Fairness with Encrypted Sensitive Attributes](http://proceedings.mlr.press/v80/kilbertus18a.html) | ICML | [code](https://github.com/nikikilbertus/blind-justice) | 5 | +| [Transfer Learning via Learning to Transfer](http://proceedings.mlr.press/v80/wei18a.html) | ICML | [code](https://github.com/QuebecAI/webcam-transfer-learning-v1) | 5 | +| [Deepcode: Feedback Codes via Deep Learning](http://arxiv.org/abs/1807.00801v1) | NIPS | [code](https://github.com/hyejikim1/Deepcode) | 4 | +| [Configurable Markov Decision Processes](http://proceedings.mlr.press/v80/metelli18a.html) | ICML | [code](https://github.com/albertometelli/Configurable-Markov-Decision-Processes-ICML-2018) | 4 | +| [A Framework for Evaluating 6-DOF Object Trackers](http://openaccess.thecvf.com/content_ECCV_2018/html/Mathieu_Garon_A_Framework_for_ECCV_2018_paper.html) | ECCV | [code](https://github.com/lvsn/6DOF_tracking_evaluation) | 4 | +| [Differentially Private Database Release via Kernel Mean Embeddings](http://proceedings.mlr.press/v80/balog18a.html) | ICML | [code](https://github.com/matejbalog/RKHS-private-database) | 4 | +| [Recognizing Human Actions as the Evolution of Pose Estimation Maps](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Recognizing_Human_Actions_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/nkliuyifang/Skeleton-based-Human-Action-Recognition) | 4 | +| [Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images](http://openaccess.thecvf.com/content_cvpr_2018/papers/Orekondy_Connecting_Pixels_to_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/tribhuvanesh/visual_redactions) | 4 | +| [DeLS-3D: Deep Localization and Segmentation With a 3D Semantic Map](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_DeLS-3D_Deep_Localization_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/pengwangucla/DeLS-3D) | 4 | +| [Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification](http://openaccess.thecvf.com/content_ECCV_2018/html/Eric_Muller-Budack_Geolocation_Estimation_of_ECCV_2018_paper.html) | ECCV | [code](https://github.com/TIBHannover/GeoEstimation) | 4 | +| [Tracking Emerges by Colorizing Videos](http://openaccess.thecvf.com/content_ECCV_2018/html/Carl_Vondrick_Self-supervised_Tracking_by_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Oh-Yoojin/Tracking-Emerges-by-Colorizing-Videos) | 4 | +| [Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes](http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_He_Diverse_Conditional_Image_ECCV_2018_paper.html) | ECCV | [code](https://github.com/SSAW14/Image_Generation_with_Latent_Code) | 4 | +| [Inference Suboptimality in Variational Autoencoders](http://proceedings.mlr.press/v80/cremer18a.html) | ICML | [code](https://github.com/lxuechen/inference-suboptimality) | 4 | +| [Black Box FDR](http://proceedings.mlr.press/v80/tansey18a.html) | ICML | [code](https://github.com/tansey/bb-fdr) | 4 | +| [Feedback-Prop: Convolutional Neural Network Inference Under Partial Evidence](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Feedback-Prop_Convolutional_Neural_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/uvavision/feedbackprop) | 4 | +| [Quadrature-based features for kernel approximation](http://arxiv.org/abs/1802.03832v3) | NIPS | [code](https://github.com/quffka/quffka) | 4 | +| [Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking](http://openaccess.thecvf.com/content_ECCV_2018/html/Yingjie_Yao_Joint_Representation_and_ECCV_2018_paper.html) | ECCV | [code](https://github.com/tourmaline612/RTINet) | 4 | +| [Transferable Adversarial Perturbations](http://openaccess.thecvf.com/content_ECCV_2018/html/Bruce_Hou_Transferable_Adversarial_Perturbations_ECCV_2018_paper.html) | ECCV | [code](https://github.com/vinayprabhu/Gainsboro-box-attacks-) | 4 | +| [Single Image Water Hazard Detection using FCN with Reflection Attention Units](http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaofeng_Han_Single_Image_Water_ECCV_2018_paper.html) | ECCV | [code](https://github.com/Cow911/SingleImageWaterHazardDetectionWithRAU) | 4 | +| [Multimodal Generative Models for Scalable Weakly-Supervised Learning](http://arxiv.org/abs/1802.05335v2) | NIPS | [code](https://github.com/mhw32/multimodal-vae-public) | 4 | +| [Importance Weighted Transfer of Samples in Reinforcement Learning](http://proceedings.mlr.press/v80/tirinzoni18a.html) | ICML | [code](https://github.com/AndreaTirinzoni/iw-transfer-rl) | 3 | +| [Feature Generating Networks for Zero-Shot Learning](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xian_Feature_Generating_Networks_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/akku1506/Feature-Generating-Networks-for-ZSL) | 3 | +| [DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding](http://proceedings.mlr.press/v80/moreau18a.html) | ICML | [code](https://github.com/tomMoral/Dicod) | 3 | +| [CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces](nan) | NIPS | [code](https://github.com/maple-research-lab/CapProNet) | 3 | +| [Bidirectional Retrieval Made Simple](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wehrmann_Bidirectional_Retrieval_Made_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/jwehrmann/chain-vse) | 3 | +| [Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages](nan) | NIPS | [code](https://github.com/forest-snow/mtanchor_demo) | 3 | +| [A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liang_A_Hybrid_l1-l0_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/csjunxu/L1L0_TM-CVPR2018) | 3 | +| [Spatially-Adaptive Filter Units for Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tabernik_Spatially-Adaptive_Filter_Units_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/skokec/DAU-ConvNet) | 3 | +| [Learning to Branch](http://proceedings.mlr.press/v80/balcan18a.html) | ICML | [code](https://github.com/StoneyJackson/github-workflow-activity) | 3 | +| [Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives](nan) | NIPS | [code](https://github.com/IBM/Contrastive-Explanation-Method) | 3 | +| [Lifelong Learning via Progressive Distillation and Retrospection](http://openaccess.thecvf.com/content_ECCV_2018/html/Saihui_Hou_Progressive_Lifelong_Learning_ECCV_2018_paper.html) | ECCV | [code](https://github.com/hshustc/ECCV18_Lifelong_Learning) | 3 | +| [CLEAR: Cumulative LEARning for One-Shot One-Class Image Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kozerawski_CLEAR_Cumulative_LEARning_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/JKozerawski/CLEAR-osoc) | 3 | +| [Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care](http://proceedings.mlr.press/v80/schwab18a.html) | ICML | [code](https://github.com/d909b/DSMT-Nets) | 3 | +| [Learning Answer Embeddings for Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Learning_Answer_Embeddings_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/hexiang-hu/answer_embedding) | 3 | +| [Information Constraints on Auto-Encoding Variational Bayes](http://arxiv.org/abs/1805.08672v2) | NIPS | [code](https://github.com/romain-lopez/HCV) | 3 | +| [Parallel Bayesian Network Structure Learning](http://proceedings.mlr.press/v80/gao18b.html) | ICML | [code](https://github.com/bign8/PyStruct) | 3 | +| [Ring Loss: Convex Feature Normalization for Face Recognition](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zheng_Ring_Loss_Convex_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/vsatyakumar/Ring-Loss-Keras) | 3 | +| [Teaching Categories to Human Learners With Visual Explanations](http://openaccess.thecvf.com/content_cvpr_2018/papers/Aodha_Teaching_Categories_to_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/macaodha/explain_teach) | 3 | +| [Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization](http://proceedings.mlr.press/v80/zhang18g.html) | ICML | [code](https://github.com/zhangjiong724/spectral-RNN) | 3 | +| [Deep Burst Denoising](http://openaccess.thecvf.com/content_ECCV_2018/html/Clement_Godard_Deep_Burst_Denoising_ECCV_2018_paper.html) | ECCV | [code](https://github.com/mrharicot/deep_burst_denoising) | 3 | +| [Convergent Tree Backup and Retrace with Function Approximation](http://proceedings.mlr.press/v80/touati18a.html) | ICML | [code](https://github.com/ahmed-touati/convergent-off-policy) | 3 | +| [Gaze Prediction in Dynamic 360° Immersive Videos](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Gaze_Prediction_in_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/xuyanyu-shh/VR-EyeTracking) | 3 | +| [Statistical Recurrent Models on Manifold valued Data](http://arxiv.org/abs/1805.11204v1) | NIPS | [code](https://github.com/zhenxingjian/SPD-SRU) | 3 | +| [End-to-End Flow Correlation Tracking With Spatial-Temporal Attention](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhu_End-to-End_Flow_Correlation_CVPR_2018_paper.pdf) | CVPR | [code](https://github.com/zhengzhugithub/FlowTrack) | 3 |
↥ back to top @@ -669,643 +681,643 @@ Use [this](https://github.com/zziz/pwc/issues/11) thread to request us your favo ## 2017 | Title | Conf | Code | Stars | |:--------|:--------:|:--------:|:--------:| -| [Bridging the Gap Between Value and Policy Based Reinforcement Learning](http://papers.nips.cc/paper/6870-bridging-the-gap-between-value-and-policy-based-reinforcement-learning.pdf) | NIPS | [code](https://github.com/tensorflow/models) | 46593 | -| [REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models](http://papers.nips.cc/paper/6856-rebar-low-variance-unbiased-gradient-estimates-for-discrete-latent-variable-models.pdf) | NIPS | [code](https://github.com/tensorflow/models) | 46593 | -| [Focal Loss for Dense Object Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Lin_Focal_Loss_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/facebookresearch/Detectron) | 18356 | -| [Mask R-CNN](http://openaccess.thecvf.com/content_iccv_2017/html/He_Mask_R-CNN_ICCV_2017_paper.html) | ICCV | [code](https://github.com/matterport/Mask_RCNN) | 9493 | -| [Deep Photo Style Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Luan_Deep_Photo_Style_CVPR_2017_paper.html) | CVPR | [code](https://github.com/luanfujun/deep-photo-styletransfer) | 8655 | -| [LightGBM: A Highly Efficient Gradient Boosting Decision Tree](http://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf) | NIPS | [code](https://github.com/Microsoft/LightGBM) | 7536 | -| [Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation](http://papers.nips.cc/paper/7112-scalable-trust-region-method-for-deep-reinforcement-learning-using-kronecker-factored-approximation.pdf) | NIPS | [code](https://github.com/openai/baselines) | 6449 | -| [Attention is All you Need](http://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf) | NIPS | [code](https://github.com/tensorflow/tensor2tensor) | 6288 | -| [Large Pose 3D Face Reconstruction From a Single Image via Direct Volumetric CNN Regression](http://openaccess.thecvf.com/content_iccv_2017/html/Jackson_Large_Pose_3D_ICCV_2017_paper.html) | ICCV | [code](https://github.com/AaronJackson/vrn) | 3354 | -| [Densely Connected Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Densely_Connected_Convolutional_CVPR_2017_paper.html) | CVPR | [code](https://github.com/liuzhuang13/DenseNet) | 3130 | -| [A Unified Approach to Interpreting Model Predictions](http://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions.pdf) | NIPS | [code](https://github.com/slundberg/shap) | 3122 | -| [Deformable Convolutional Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Deformable_Convolutional_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/msracver/Deformable-ConvNets) | 2165 | -| [ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games](http://papers.nips.cc/paper/6859-elf-an-extensive-lightweight-and-flexible-research-platform-for-real-time-strategy-games.pdf) | NIPS | [code](https://github.com/facebookresearch/ELF) | 1823 | -| [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Qi_PointNet_Deep_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/charlesq34/pointnet) | 1523 | -| [Improved Training of Wasserstein GANs](http://papers.nips.cc/paper/7159-improved-training-of-wasserstein-gans.pdf) | NIPS | [code](https://github.com/igul222/improved_wgan_training) | 1405 | -| [Fully Convolutional Instance-Aware Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Fully_Convolutional_Instance-Aware_CVPR_2017_paper.html) | CVPR | [code](https://github.com/msracver/FCIS) | 1395 | -| [Aggregated Residual Transformations for Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Xie_Aggregated_Residual_Transformations_CVPR_2017_paper.html) | CVPR | [code](https://github.com/facebookresearch/ResNeXt) | 1361 | -| [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Ledig_Photo-Realistic_Single_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tensorlayer/srgan) | 1301 | -| [Unsupervised Image-to-Image Translation Networks](http://papers.nips.cc/paper/6672-unsupervised-image-to-image-translation-networks.pdf) | NIPS | [code](https://github.com/mingyuliutw/unit) | 1205 | -| [Photographic Image Synthesis With Cascaded Refinement Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Photographic_Image_Synthesis_ICCV_2017_paper.html) | ICCV | [code](https://github.com/CQFIO/PhotographicImageSynthesis) | 1142 | -| [High-Resolution Image Inpainting Using Multi-Scale Neural Patch Synthesis](http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_High-Resolution_Image_Inpainting_CVPR_2017_paper.html) | CVPR | [code](https://github.com/leehomyc/Faster-High-Res-Neural-Inpainting) | 1072 | -| [SphereFace: Deep Hypersphere Embedding for Face Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_SphereFace_Deep_Hypersphere_CVPR_2017_paper.html) | CVPR | [code](https://github.com/wy1iu/sphereface) | 1048 | -| [Deep Feature Flow for Video Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Deep_Feature_Flow_CVPR_2017_paper.html) | CVPR | [code](https://github.com/msracver/Deep-Feature-Flow) | 966 | -| [Bayesian GAN](http://papers.nips.cc/paper/6953-bayesian-gan.pdf) | NIPS | [code](https://github.com/andrewgordonwilson/bayesgan) | 942 | -| [Pyramid Scene Parsing Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhao_Pyramid_Scene_Parsing_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hszhao/PSPNet) | 934 | -| [Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes](http://papers.nips.cc/paper/7098-efficient-modeling-of-latent-information-in-supervised-learning-using-gaussian-processes.pdf) | NIPS | [code](https://github.com/SheffieldML/GPy) | 906 | -| [Finding Tiny Faces](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Finding_Tiny_Faces_CVPR_2017_paper.html) | CVPR | [code](https://github.com/peiyunh/tiny) | 856 | -| [Toward Multimodal Image-to-Image Translation](http://papers.nips.cc/paper/6650-toward-multimodal-image-to-image-translation.pdf) | NIPS | [code](https://github.com/junyanz/BiCycleGAN) | 794 | -| [Learning to Discover Cross-Domain Relations with Generative Adversarial Networks](http://proceedings.mlr.press/v70/kim17a.html) | ICML | [code](https://github.com/carpedm20/DiscoGAN-pytorch) | 784 | -| [YOLO9000: Better, Faster, Stronger](http://openaccess.thecvf.com/content_cvpr_2017/html/Redmon_YOLO9000_Better_Faster_CVPR_2017_paper.html) | CVPR | [code](https://github.com/philipperemy/yolo-9000) | 773 | -| [PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space](http://papers.nips.cc/paper/7095-pointnet-deep-hierarchical-feature-learning-on-point-sets-in-a-metric-space.pdf) | NIPS | [code](https://github.com/charlesq34/pointnet2) | 772 | -| [Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks](http://proceedings.mlr.press/v70/finn17a.html) | ICML | [code](https://github.com/cbfinn/maml) | 729 | -| [FlowNet 2.0: Evolution of Optical Flow Estimation With Deep Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Ilg_FlowNet_2.0_Evolution_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lmb-freiburg/flownet2) | 720 | -| [Channel Pruning for Accelerating Very Deep Neural Networks](http://openaccess.thecvf.com/content_iccv_2017/html/He_Channel_Pruning_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/yihui-he/channel-pruning) | 649 | -| [Dilated Residual Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Yu_Dilated_Residual_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fyu/drn) | 640 | -| [Inferring and Executing Programs for Visual Reasoning](http://openaccess.thecvf.com/content_iccv_2017/html/Johnson_Inferring_and_Executing_ICCV_2017_paper.html) | ICCV | [code](https://github.com/facebookresearch/clevr-iep) | 636 | -| [DSOD: Learning Deeply Supervised Object Detectors From Scratch](http://openaccess.thecvf.com/content_iccv_2017/html/Shen_DSOD_Learning_Deeply_ICCV_2017_paper.html) | ICCV | [code](https://github.com/szq0214/DSOD) | 582 | -| [Arbitrary Style Transfer in Real-Time With Adaptive Instance Normalization](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Arbitrary_Style_Transfer_ICCV_2017_paper.html) | ICCV | [code](https://github.com/xunhuang1995/AdaIN-style) | 572 | -| [Accelerating Eulerian Fluid Simulation With Convolutional Networks](http://proceedings.mlr.press/v70/tompson17a.html) | ICML | [code](https://github.com/google/FluidNet) | 570 | -| [Learning Disentangled Representations with Semi-Supervised Deep Generative Models](http://papers.nips.cc/paper/7174-learning-disentangled-representations-with-semi-supervised-deep-generative-models.pdf) | NIPS | [code](https://github.com/probtorch/probtorch) | 556 | -| [Inductive Representation Learning on Large Graphs](http://papers.nips.cc/paper/6703-inductive-representation-learning-on-large-graphs.pdf) | NIPS | [code](https://github.com/williamleif/GraphSAGE) | 552 | -| [Regressing Robust and Discriminative 3D Morphable Models With a Very Deep Neural Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Tran_Regressing_Robust_and_CVPR_2017_paper.html) | CVPR | [code](https://github.com/anhttran/3dmm_cnn) | 537 | -| [How Far Are We From Solving the 2D & 3D Face Alignment Problem? (And a Dataset of 230,000 3D Facial Landmarks)](http://openaccess.thecvf.com/content_iccv_2017/html/Bulat_How_Far_Are_ICCV_2017_paper.html) | ICCV | [code](https://github.com/1adrianb/2D-and-3D-face-alignment) | 526 | -| [SSH: Single Stage Headless Face Detector](http://openaccess.thecvf.com/content_iccv_2017/html/Najibi_SSH_Single_Stage_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mahyarnajibi/SSH) | 515 | -| [Learning From Simulated and Unsupervised Images Through Adversarial Training](http://openaccess.thecvf.com/content_cvpr_2017/html/Shrivastava_Learning_From_Simulated_CVPR_2017_paper.html) | CVPR | [code](https://github.com/carpedm20/simulated-unsupervised-tensorflow) | 492 | -| [Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space](http://openaccess.thecvf.com/content_cvpr_2017/html/Nguyen_Plug__Play_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Evolving-AI-Lab/ppgn) | 487 | -| [Video Frame Interpolation via Adaptive Convolution](http://openaccess.thecvf.com/content_cvpr_2017/html/Niklaus_Video_Frame_Interpolation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sniklaus/pytorch-sepconv) | 482 | -| [Video Frame Interpolation via Adaptive Separable Convolution](http://openaccess.thecvf.com/content_iccv_2017/html/Niklaus_Video_Frame_Interpolation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/sniklaus/pytorch-sepconv) | 482 | -| [GMS: Grid-based Motion Statistics for Fast, Ultra-Robust Feature Correspondence](http://openaccess.thecvf.com/content_cvpr_2017/html/Bian_GMS_Grid-based_Motion_CVPR_2017_paper.html) | CVPR | [code](https://github.com/JiawangBian/GMS-Feature-Matcher) | 460 | -| [Joint Detection and Identification Feature Learning for Person Search](http://openaccess.thecvf.com/content_cvpr_2017/html/Xiao_Joint_Detection_and_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ShuangLI59/person_search) | 459 | -| [Dual Path Networks](http://papers.nips.cc/paper/7033-dual-path-networks.pdf) | NIPS | [code](https://github.com/cypw/DPNs) | 451 | -| [Flow-Guided Feature Aggregation for Video Object Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Flow-Guided_Feature_Aggregation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/msracver/Flow-Guided-Feature-Aggregation) | 436 | -| [Deep Image Matting](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Deep_Image_Matting_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Joker316701882/Deep-Image-Matting) | 434 | -| [Richer Convolutional Features for Edge Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Richer_Convolutional_Features_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yun-liu/rcf) | 399 | -| [Annotating Object Instances With a Polygon-RNN](http://openaccess.thecvf.com/content_cvpr_2017/html/Castrejon_Annotating_Object_Instances_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fidler-lab/polyrnn-pp-pytorch) | 397 | -| [Recurrent Highway Networks](http://proceedings.mlr.press/v70/zilly17a.html) | ICML | [code](https://github.com/julian121266/RecurrentHighwayNetworks) | 397 | -| [Detect to Track and Track to Detect](http://openaccess.thecvf.com/content_iccv_2017/html/Feichtenhofer_Detect_to_Track_ICCV_2017_paper.html) | ICCV | [code](https://github.com/feichtenhofer/Detect-Track) | 387 | -| [RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_RefineNet_Multi-Path_Refinement_CVPR_2017_paper.html) | CVPR | [code](https://github.com/guosheng/refinenet) | 379 | -| [Detecting Oriented Text in Natural Images by Linking Segments](http://openaccess.thecvf.com/content_cvpr_2017/html/Shi_Detecting_Oriented_Text_CVPR_2017_paper.html) | CVPR | [code](https://github.com/dengdan/seglink) | 364 | -| [Deep Lattice Networks and Partial Monotonic Functions](http://papers.nips.cc/paper/6891-deep-lattice-networks-and-partial-monotonic-functions.pdf) | NIPS | [code](https://github.com/tensorflow/lattice) | 349 | -| [Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results](http://papers.nips.cc/paper/6719-mean-teachers-are-better-role-models-weight-averaged-consistency-targets-improve-semi-supervised-deep-learning-results.pdf) | NIPS | [code](https://github.com/CuriousAI/mean-teacher/) | 347 | -| [RON: Reverse Connection With Objectness Prior Networks for Object Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Kong_RON_Reverse_Connection_CVPR_2017_paper.html) | CVPR | [code](https://github.com/taokong/RON) | 345 | -| [Universal Style Transfer via Feature Transforms](http://papers.nips.cc/paper/6642-universal-style-transfer-via-feature-transforms.pdf) | NIPS | [code](https://github.com/Yijunmaverick/UniversalStyleTransfer) | 344 | -| [Residual Attention Network for Image Classification](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Residual_Attention_Network_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fwang91/residual-attention-network) | 329 | -| [One-Shot Video Object Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Caelles_One-Shot_Video_Object_CVPR_2017_paper.html) | CVPR | [code](https://github.com/scaelles/OSVOS-TensorFlow) | 316 | -| [Accurate Single Stage Detector Using Recurrent Rolling Convolution](http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_Accurate_Single_Stage_CVPR_2017_paper.html) | CVPR | [code](https://github.com/xiaohaoChen/rrc_detection) | 314 | -| [Feature Pyramid Networks for Object Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Feature_Pyramid_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/unsky/FPN) | 310 | -| [Efficient softmax approximation for GPUs](http://proceedings.mlr.press/v70/grave17a.html) | ICML | [code](https://github.com/facebookresearch/adaptive-softmax) | 304 | -| [OctNet: Learning Deep 3D Representations at High Resolutions](http://openaccess.thecvf.com/content_cvpr_2017/html/Riegler_OctNet_Learning_Deep_CVPR_2017_paper.html) | CVPR | [code](https://github.com/griegler/octnet) | 302 | -| [Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2017/html/Lai_Deep_Laplacian_Pyramid_CVPR_2017_paper.html) | CVPR | [code](https://github.com/phoenix104104/LapSRN) | 301 | -| [Pixel Recursive Super Resolution](http://openaccess.thecvf.com/content_iccv_2017/html/Dahl_Pixel_Recursive_Super_ICCV_2017_paper.html) | ICCV | [code](https://github.com/nilboy/pixel-recursive-super-resolution) | 301 | -| [Self-Critical Sequence Training for Image Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Rennie_Self-Critical_Sequence_Training_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ruotianluo/self-critical.pytorch) | 299 | -| [Age Progression/Regression by Conditional Adversarial Autoencoder](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Age_ProgressionRegression_by_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ZZUTK/Face-Aging-CAAE) | 297 | -| [Style Transfer from Non-Parallel Text by Cross-Alignment](http://papers.nips.cc/paper/7259-style-transfer-from-non-parallel-text-by-cross-alignment.pdf) | NIPS | [code](https://github.com/shentianxiao/language-style-transfer) | 296 | -| [Dilated Recurrent Neural Networks](http://papers.nips.cc/paper/6613-dilated-recurrent-neural-networks.pdf) | NIPS | [code](https://github.com/code-terminator/DilatedRNN) | 285 | -| [Lifting From the Deep: Convolutional 3D Pose Estimation From a Single Image](http://openaccess.thecvf.com/content_cvpr_2017/html/Tome_Lifting_From_the_CVPR_2017_paper.html) | CVPR | [code](https://github.com/DenisTome/Lifting-from-the-Deep-release) | 280 | -| [DeepBach: a Steerable Model for Bach Chorales Generation](http://proceedings.mlr.press/v70/hadjeres17a.html) | ICML | [code](https://github.com/Ghadjeres/DeepBach) | 276 | -| [The Predictron: End-To-End Learning and Planning](http://proceedings.mlr.press/v70/silver17a.html) | ICML | [code](https://github.com/zhongwen/predictron) | 274 | -| [Convolutional Sequence to Sequence Learning](http://proceedings.mlr.press/v70/gehring17a.html) | ICML | [code](https://github.com/tobyyouup/conv_seq2seq) | 258 | -| [OptNet: Differentiable Optimization as a Layer in Neural Networks](http://proceedings.mlr.press/v70/amos17a.html) | ICML | [code](https://github.com/locuslab/optnet) | 245 | -| [Prototypical Networks for Few-shot Learning](http://papers.nips.cc/paper/6996-prototypical-networks-for-few-shot-learning.pdf) | NIPS | [code](https://github.com/jakesnell/prototypical-networks) | 244 | -| [Deep Voice: Real-time Neural Text-to-Speech](http://proceedings.mlr.press/v70/arik17a.html) | ICML | [code](https://github.com/israelg99/deepvoice) | 242 | -| [Reinforcement Learning with Deep Energy-Based Policies](http://proceedings.mlr.press/v70/haarnoja17a.html) | ICML | [code](https://github.com/haarnoja/softqlearning) | 233 | -| [Learning Deep CNN Denoiser Prior for Image Restoration](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Learning_Deep_CNN_CVPR_2017_paper.html) | CVPR | [code](https://github.com/cszn/IRCNN) | 231 | -| [GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium](http://papers.nips.cc/paper/7240-gans-trained-by-a-two-time-scale-update-rule-converge-to-a-local-nash-equilibrium.pdf) | NIPS | [code](https://github.com/bioinf-jku/TTUR) | 229 | -| [A Point Set Generation Network for 3D Object Reconstruction From a Single Image](http://openaccess.thecvf.com/content_cvpr_2017/html/Fan_A_Point_Set_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fanhqme/PointSetGeneration) | 228 | -| [Deeply Supervised Salient Object Detection With Short Connections](http://openaccess.thecvf.com/content_cvpr_2017/html/Hou_Deeply_Supervised_Salient_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Joker316701882/Salient-Object-Detection) | 228 | -| [BlitzNet: A Real-Time Deep Network for Scene Understanding](http://openaccess.thecvf.com/content_iccv_2017/html/Dvornik_BlitzNet_A_Real-Time_ICCV_2017_paper.html) | ICCV | [code](https://github.com/dvornikita/blitznet) | 227 | -| [Language Modeling with Gated Convolutional Networks](http://proceedings.mlr.press/v70/dauphin17a.html) | ICML | [code](https://github.com/anantzoid/Language-Modeling-GatedCNN) | 221 | -| [Unlabeled Samples Generated by GAN Improve the Person Re-Identification Baseline in Vitro](http://openaccess.thecvf.com/content_iccv_2017/html/Zheng_Unlabeled_Samples_Generated_ICCV_2017_paper.html) | ICCV | [code](https://github.com/layumi/Person-reID_GAN) | 215 | -| [Stacked Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Stacked_Generative_Adversarial_CVPR_2017_paper.html) | CVPR | [code](https://github.com/xunhuang1995/SGAN) | 215 | -| [RMPE: Regional Multi-Person Pose Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Fang_RMPE_Regional_Multi-Person_ICCV_2017_paper.html) | ICCV | [code](https://github.com/MVIG-SJTU/RMPE) | 215 | -| [Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Lu_Knowing_When_to_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jiasenlu/AdaptiveAttention) | 214 | -| [Generative Face Completion](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Generative_Face_Completion_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Yijunmaverick/GenerativeFaceCompletion) | 212 | -| [VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Lee_VPGNet_Vanishing_Point_ICCV_2017_paper.html) | ICCV | [code](https://github.com/SeokjuLee/VPGNet) | 210 | -| [The Reversible Residual Network: Backpropagation Without Storing Activations](http://papers.nips.cc/paper/6816-the-reversible-residual-network-backpropagation-without-storing-activations.pdf) | NIPS | [code](https://github.com/renmengye/revnet-public) | 210 | -| [Recurrent Scale Approximation for Object Detection in CNN](http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Recurrent_Scale_Approximation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/sciencefans/RSA-for-object-detection) | 209 | -| [Learning From Synthetic Humans](http://openaccess.thecvf.com/content_cvpr_2017/html/Varol_Learning_From_Synthetic_CVPR_2017_paper.html) | CVPR | [code](https://github.com/gulvarol/surreal) | 207 | -| [Spatially Adaptive Computation Time for Residual Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Figurnov_Spatially_Adaptive_Computation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/mfigurnov/sact) | 203 | -| [Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Beyond_Face_Rotation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/HRLTY/TP-GAN) | 202 | -| [3D Bounding Box Estimation Using Deep Learning and Geometry](http://openaccess.thecvf.com/content_cvpr_2017/html/Mousavian_3D_Bounding_Box_CVPR_2017_paper.html) | CVPR | [code](https://github.com/smallcorgi/3D-Deepbox) | 200 | -| [Multi-View 3D Object Detection Network for Autonomous Driving](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Multi-View_3D_Object_CVPR_2017_paper.html) | CVPR | [code](https://github.com/bostondiditeam/MV3D) | 199 | -| [Visual Dialog](http://openaccess.thecvf.com/content_cvpr_2017/html/Das_Visual_Dialog_CVPR_2017_paper.html) | CVPR | [code](https://github.com/batra-mlp-lab/visdial) | 199 | -| [Interpretable Explanations of Black Boxes by Meaningful Perturbation](http://openaccess.thecvf.com/content_iccv_2017/html/Fong_Interpretable_Explanations_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jacobgil/pytorch-explain-black-box) | 192 | -| [Inverse Compositional Spatial Transformer Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Inverse_Compositional_Spatial_CVPR_2017_paper.html) | CVPR | [code](https://github.com/chenhsuanlin/inverse-compositional-STN) | 189 | -| [FastMask: Segment Multi-Scale Object Candidates in One Shot](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_FastMask_Segment_Multi-Scale_CVPR_2017_paper.html) | CVPR | [code](https://github.com/voidrank/FastMask) | 189 | -| [OnACID: Online Analysis of Calcium Imaging Data in Real Time](http://papers.nips.cc/paper/6832-onacid-online-analysis-of-calcium-imaging-data-in-real-time.pdf) | NIPS | [code](https://github.com/simonsfoundation/caiman) | 189 | -| [Semantic Scene Completion From a Single Depth Image](http://openaccess.thecvf.com/content_cvpr_2017/html/Song_Semantic_Scene_Completion_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shurans/sscnet) | 188 | -| [Learning Efficient Convolutional Networks Through Network Slimming](http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Learning_Efficient_Convolutional_ICCV_2017_paper.html) | ICCV | [code](https://github.com/liuzhuang13/slimming) | 186 | -| [Learning Feature Pyramids for Human Pose Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Yang_Learning_Feature_Pyramids_ICCV_2017_paper.html) | ICCV | [code](https://github.com/bearpaw/PyraNet) | 185 | -| [Be Your Own Prada: Fashion Synthesis With Structural Coherence](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Be_Your_Own_ICCV_2017_paper.html) | ICCV | [code](https://github.com/zhusz/ICCV17-fashionGAN) | 183 | -| [Scene Graph Generation by Iterative Message Passing](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Scene_Graph_Generation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/danfeiX/scene-graph-TF-release) | 182 | -| [Fast Image Processing With Fully-Convolutional Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Fast_Image_Processing_ICCV_2017_paper.html) | ICCV | [code](https://github.com/CQFIO/FastImageProcessing) | 180 | -| [Learning Multiple Tasks with Multilinear Relationship Networks](http://papers.nips.cc/paper/6757-learning-multiple-tasks-with-multilinear-relationship-networks.pdf) | NIPS | [code](https://github.com/thuml/Xlearn) | 178 | -| [Learning to Reason: End-To-End Module Networks for Visual Question Answering](http://openaccess.thecvf.com/content_iccv_2017/html/Hu_Learning_to_Reason_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ronghanghu/n2nmn) | 178 | -| [Single Shot Text Detector With Regional Attention](http://openaccess.thecvf.com/content_iccv_2017/html/He_Single_Shot_Text_ICCV_2017_paper.html) | ICCV | [code](https://github.com/BestSonny/SSTD) | 176 | -| [Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment With Limited Resources](http://openaccess.thecvf.com/content_iccv_2017/html/Bulat_Binarized_Convolutional_Landmark_ICCV_2017_paper.html) | ICCV | [code](https://github.com/1adrianb/binary-human-pose-estimation) | 175 | -| [Deep Feature Interpolation for Image Content Changes](http://openaccess.thecvf.com/content_cvpr_2017/html/Upchurch_Deep_Feature_Interpolation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/paulu/deepfeatinterp) | 170 | -| [On Human Motion Prediction Using Recurrent Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Martinez_On_Human_Motion_CVPR_2017_paper.html) | CVPR | [code](https://github.com/una-dinosauria/human-motion-prediction) | 167 | -| [Image Super-Resolution via Deep Recursive Residual Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Tai_Image_Super-Resolution_via_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tyshiwo/DRRN_CVPR17) | 163 | -| [Learning Cross-Modal Embeddings for Cooking Recipes and Food Images](http://openaccess.thecvf.com/content_cvpr_2017/html/Salvador_Learning_Cross-Modal_Embeddings_CVPR_2017_paper.html) | CVPR | [code](https://github.com/torralba-lab/im2recipe) | 160 | -| [Input Convex Neural Networks](http://proceedings.mlr.press/v70/amos17b.html) | ICML | [code](https://github.com/locuslab/icnn) | 159 | -| [Simple Does It: Weakly Supervised Instance and Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Khoreva_Simple_Does_It_CVPR_2017_paper.html) | CVPR | [code](https://github.com/philferriere/tfwss) | 159 | -| [Low-Shot Visual Recognition by Shrinking and Hallucinating Features](http://openaccess.thecvf.com/content_iccv_2017/html/Hariharan_Low-Shot_Visual_Recognition_ICCV_2017_paper.html) | ICCV | [code](https://github.com/facebookresearch/low-shot-shrink-hallucinate) | 158 | -| [Oriented Response Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Oriented_Response_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ZhouYanzhao/ORN) | 157 | -| [Soft Proposal Networks for Weakly Supervised Object Localization](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Soft_Proposal_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/yeezhu/SPN.pytorch) | 154 | -| [Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks](http://proceedings.mlr.press/v70/mescheder17a.html) | ICML | [code](https://github.com/LMescheder/AdversarialVariationalBayes) | 147 | -| [Axiomatic Attribution for Deep Networks](http://proceedings.mlr.press/v70/sundararajan17a.html) | ICML | [code](https://github.com/hiranumn/IntegratedGradients) | 146 | -| [Gradient Episodic Memory for Continual Learning](http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf) | NIPS | [code](https://github.com/facebookresearch/GradientEpisodicMemory) | 146 | -| [DSAC - Differentiable RANSAC for Camera Localization](http://openaccess.thecvf.com/content_cvpr_2017/html/Brachmann_DSAC_-_Differentiable_CVPR_2017_paper.html) | CVPR | [code](https://github.com/cvlab-dresden/DSAC) | 144 | -| [Attend to You: Personalized Image Captioning With Context Sequence Memory Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Attend_to_You_CVPR_2017_paper.html) | CVPR | [code](https://github.com/cesc-park/attend2u) | 143 | -| [Conditional Similarity Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Veit_Conditional_Similarity_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/andreasveit/conditional-similarity-networks) | 142 | -| [Language Modeling with Recurrent Highway Hypernetworks](http://papers.nips.cc/paper/6919-language-modeling-with-recurrent-highway-hypernetworks.pdf) | NIPS | [code](https://github.com/jsuarez5341/Recurrent-Highway-Hypernetworks-NIPS) | 141 | -| [Triple Generative Adversarial Nets](http://papers.nips.cc/paper/6997-triple-generative-adversarial-nets.pdf) | NIPS | [code](https://github.com/zhenxuan00/triple-gan) | 138 | -| [Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning](http://papers.nips.cc/paper/6974-interpolated-policy-gradient-merging-on-policy-and-off-policy-gradient-estimation-for-deep-reinforcement-learning.pdf) | NIPS | [code](https://github.com/shaneshixiang/rllabplusplus) | 138 | -| [One-Sided Unsupervised Domain Mapping](http://papers.nips.cc/paper/6677-one-sided-unsupervised-domain-mapping.pdf) | NIPS | [code](https://github.com/sagiebenaim/DistanceGAN) | 137 | -| [Detecting Visual Relationships With Deep Relational Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Dai_Detecting_Visual_Relationships_CVPR_2017_paper.html) | CVPR | [code](https://github.com/doubledaibo/drnet_cvpr2017) | 137 | -| [Attentive Recurrent Comparators](http://proceedings.mlr.press/v70/shyam17a.html) | ICML | [code](https://github.com/sanyam5/arc-pytorch) | 136 | -| [Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach](http://openaccess.thecvf.com/content_iccv_2017/html/Zhou_Towards_3D_Human_ICCV_2017_paper.html) | ICCV | [code](https://github.com/xingyizhou/pose-hg-3d) | 136 | -| [Learning a Multi-View Stereo Machine](http://papers.nips.cc/paper/6640-learning-a-multi-view-stereo-machine.pdf) | NIPS | [code](https://github.com/akar43/lsm) | 135 | -| [Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model](http://papers.nips.cc/paper/7145-deep-learning-for-precipitation-nowcasting-a-benchmark-and-a-new-model.pdf) | NIPS | [code](https://github.com/sxjscience/HKO-7) | 134 | -| [Multi-Context Attention for Human Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Chu_Multi-Context_Attention_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/bearpaw/pose-attention) | 131 | -| [Controlling Perceptual Factors in Neural Style Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Gatys_Controlling_Perceptual_Factors_CVPR_2017_paper.html) | CVPR | [code](https://github.com/leongatys/NeuralImageSynthesis) | 130 | -| [Bayesian Compression for Deep Learning](http://papers.nips.cc/paper/6921-bayesian-compression-for-deep-learning.pdf) | NIPS | [code](https://github.com/KarenUllrich/Tutorial_BayesianCompressionForDL) | 130 | -| [Adversarial Discriminative Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2017/html/Tzeng_Adversarial_Discriminative_Domain_CVPR_2017_paper.html) | CVPR | [code](https://github.com/corenel/pytorch-adda) | 129 | -| [Working hard to know your neighbor's margins: Local descriptor learning loss](http://papers.nips.cc/paper/7068-working-hard-to-know-your-neighbors-margins-local-descriptor-learning-loss.pdf) | NIPS | [code](https://github.com/DagnyT/hardnet) | 128 | -| [Concrete Dropout](http://papers.nips.cc/paper/6949-concrete-dropout.pdf) | NIPS | [code](https://github.com/yaringal/ConcreteDropout) | 127 | -| [SegFlow: Joint Learning for Video Object Segmentation and Optical Flow](http://openaccess.thecvf.com/content_iccv_2017/html/Cheng_SegFlow_Joint_Learning_ICCV_2017_paper.html) | ICCV | [code](https://github.com/JingchunCheng/SegFlow) | 127 | -| [Segmentation-Aware Convolutional Networks Using Local Attention Masks](http://openaccess.thecvf.com/content_iccv_2017/html/Harley_Segmentation-Aware_Convolutional_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/aharley/segaware) | 126 | -| [Detail-Revealing Deep Video Super-Resolution](http://openaccess.thecvf.com/content_iccv_2017/html/Tao_Detail-Revealing_Deep_Video_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jiangsutx/SPMC_VideoSR) | 126 | -| [CREST: Convolutional Residual Learning for Visual Tracking](http://openaccess.thecvf.com/content_iccv_2017/html/Song_CREST_Convolutional_Residual_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ybsong00/CREST-Release) | 126 | -| [Discriminative Correlation Filter With Channel and Spatial Reliability](http://openaccess.thecvf.com/content_cvpr_2017/html/Lukezic_Discriminative_Correlation_Filter_CVPR_2017_paper.html) | CVPR | [code](https://github.com/alanlukezic/csr-dcf) | 124 | -| [SVDNet for Pedestrian Retrieval](http://openaccess.thecvf.com/content_iccv_2017/html/Sun_SVDNet_for_Pedestrian_ICCV_2017_paper.html) | ICCV | [code](https://github.com/syfafterzy/SVDNet-for-Pedestrian-Retrieval) | 121 | -| [Semantic Image Synthesis via Adversarial Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Dong_Semantic_Image_Synthesis_ICCV_2017_paper.html) | ICCV | [code](https://github.com/woozzu/dong_iccv_2017) | 121 | -| [Spatiotemporal Multiplier Networks for Video Action Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Feichtenhofer_Spatiotemporal_Multiplier_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/feichtenhofer/st-resnet) | 121 | -| [PoseTrack: Joint Multi-Person Pose Estimation and Tracking](http://openaccess.thecvf.com/content_cvpr_2017/html/Iqbal_PoseTrack_Joint_Multi-Person_CVPR_2017_paper.html) | CVPR | [code](https://github.com/iqbalu/PoseTrack-CVPR2017) | 121 | -| [Hierarchical Attentive Recurrent Tracking](http://papers.nips.cc/paper/6898-hierarchical-attentive-recurrent-tracking.pdf) | NIPS | [code](https://github.com/akosiorek/hart) | 121 | -| [Good Semi-supervised Learning That Requires a Bad GAN](http://papers.nips.cc/paper/7229-good-semi-supervised-learning-that-requires-a-bad-gan.pdf) | NIPS | [code](https://github.com/kimiyoung/ssl_bad_gan) | 120 | -| [Deep Watershed Transform for Instance Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Bai_Deep_Watershed_Transform_CVPR_2017_paper.html) | CVPR | [code](https://github.com/min2209/dwt) | 120 | -| [Associative Domain Adaptation](http://openaccess.thecvf.com/content_iccv_2017/html/Haeusser_Associative_Domain_Adaptation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/haeusser/learning_by_association) | 119 | -| [Learning by Association -- A Versatile Semi-Supervised Training Method for Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Haeusser_Learning_by_Association_CVPR_2017_paper.html) | CVPR | [code](https://github.com/haeusser/learning_by_association) | 119 | -| [Value Prediction Network](http://papers.nips.cc/paper/7192-value-prediction-network.pdf) | NIPS | [code](https://github.com/junhyukoh/value-prediction-network) | 119 | -| [Unrestricted Facial Geometry Reconstruction Using Image-To-Image Translation](http://openaccess.thecvf.com/content_iccv_2017/html/Sela_Unrestricted_Facial_Geometry_ICCV_2017_paper.html) | ICCV | [code](https://github.com/matansel/pix2vertex) | 119 | -| [MemNet: A Persistent Memory Network for Image Restoration](http://openaccess.thecvf.com/content_iccv_2017/html/Tai_MemNet_A_Persistent_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tyshiwo/MemNet) | 119 | -| [Bayesian Optimization with Gradients](http://papers.nips.cc/paper/7111-bayesian-optimization-with-gradients.pdf) | NIPS | [code](https://github.com/wujian16/Cornell-MOE) | 117 | -| [TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning](http://papers.nips.cc/paper/6749-terngrad-ternary-gradients-to-reduce-communication-in-distributed-deep-learning.pdf) | NIPS | [code](https://github.com/wenwei202/terngrad) | 117 | -| [Compressed Sensing using Generative Models](http://proceedings.mlr.press/v70/bora17a.html) | ICML | [code](https://github.com/AshishBora/csgm) | 116 | -| [Switching Convolutional Neural Network for Crowd Counting](http://openaccess.thecvf.com/content_cvpr_2017/html/Sam_Switching_Convolutional_Neural_CVPR_2017_paper.html) | CVPR | [code](https://github.com/val-iisc/crowd-counting-scnn) | 116 | -| [WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Durand_WILDCAT_Weakly_Supervised_CVPR_2017_paper.html) | CVPR | [code](https://github.com/durandtibo/wildcat.pytorch) | 116 | -| [Show, Adapt and Tell: Adversarial Training of Cross-Domain Image Captioner](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Show_Adapt_and_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tsenghungchen/show-adapt-and-tell) | 115 | -| [Video Frame Synthesis Using Deep Voxel Flow](http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Video_Frame_Synthesis_ICCV_2017_paper.html) | ICCV | [code](https://github.com/liuziwei7/voxel-flow) | 114 | -| [Multiple Instance Detection Network With Online Instance Classifier Refinement](http://openaccess.thecvf.com/content_cvpr_2017/html/Tang_Multiple_Instance_Detection_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ppengtang/oicr) | 113 | -| [Deep Pyramidal Residual Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Han_Deep_Pyramidal_Residual_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jhkim89/PyramidNet) | 112 | -| [Train longer, generalize better: closing the generalization gap in large batch training of neural networks](http://papers.nips.cc/paper/6770-train-longer-generalize-better-closing-the-generalization-gap-in-large-batch-training-of-neural-networks.pdf) | NIPS | [code](https://github.com/eladhoffer/bigBatch) | 112 | -| [Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Split-Brain_Autoencoders_Unsupervised_CVPR_2017_paper.html) | CVPR | [code](https://github.com/richzhang/splitbrainauto) | 110 | -| [Unite the People: Closing the Loop Between 3D and 2D Human Representations](http://openaccess.thecvf.com/content_cvpr_2017/html/Lassner_Unite_the_People_CVPR_2017_paper.html) | CVPR | [code](https://github.com/classner/up) | 110 | -| [Learning Combinatorial Optimization Algorithms over Graphs](http://papers.nips.cc/paper/7214-learning-combinatorial-optimization-algorithms-over-graphs.pdf) | NIPS | [code](https://github.com/Hanjun-Dai/graph_comb_opt) | 109 | -| [FeUdal Networks for Hierarchical Reinforcement Learning](http://proceedings.mlr.press/v70/vezhnevets17a.html) | ICML | [code](https://github.com/dmakian/feudal_networks) | 107 | -| [ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression](http://openaccess.thecvf.com/content_iccv_2017/html/Luo_ThiNet_A_Filter_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Roll920/ThiNet) | 105 | -| [Learning a Deep Embedding Model for Zero-Shot Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Learning_a_Deep_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lzrobots/DeepEmbeddingModel_ZSL) | 104 | -| [ECO: Efficient Convolution Operators for Tracking](http://openaccess.thecvf.com/content_cvpr_2017/html/Danelljan_ECO_Efficient_Convolution_CVPR_2017_paper.html) | CVPR | [code](https://github.com/nicewsyly/ECO) | 103 | -| [SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_SCA-CNN_Spatial_and_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zjuchenlong/sca-cnn.cvpr17) | 102 | -| [Multi-View Supervision for Single-View Reconstruction via Differentiable Ray Consistency](http://openaccess.thecvf.com/content_cvpr_2017/html/Tulsiani_Multi-View_Supervision_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shubhtuls/drc) | 100 | -| [Task-based End-to-end Model Learning in Stochastic Optimization](http://papers.nips.cc/paper/7132-task-based-end-to-end-model-learning-in-stochastic-optimization.pdf) | NIPS | [code](https://github.com/locuslab/e2e-model-learning) | 100 | -| [Learning to Compose Domain-Specific Transformations for Data Augmentation](http://papers.nips.cc/paper/6916-learning-to-compose-domain-specific-transformations-for-data-augmentation.pdf) | NIPS | [code](https://github.com/HazyResearch/tanda) | 97 | -| [Genetic CNN](http://openaccess.thecvf.com/content_iccv_2017/html/Xie_Genetic_CNN_ICCV_2017_paper.html) | ICCV | [code](https://github.com/aqibsaeed/Genetic-CNN) | 97 | -| [HashNet: Deep Learning to Hash by Continuation](http://openaccess.thecvf.com/content_iccv_2017/html/Cao_HashNet_Deep_Learning_ICCV_2017_paper.html) | ICCV | [code](https://github.com/thuml/HashNet) | 97 | -| [Interleaved Group Convolutions](http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Interleaved_Group_Convolutions_ICCV_2017_paper.html) | ICCV | [code](https://github.com/hellozting/InterleavedGroupConvolutions) | 95 | -| [Deeply-Learned Part-Aligned Representations for Person Re-Identification](http://openaccess.thecvf.com/content_iccv_2017/html/Zhao_Deeply-Learned_Part-Aligned_Representations_ICCV_2017_paper.html) | ICCV | [code](https://github.com/zlmzju/part_reid) | 95 | -| [Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model](http://papers.nips.cc/paper/6635-best-of-both-worlds-transferring-knowledge-from-discriminative-learning-to-a-generative-visual-dialog-model.pdf) | NIPS | [code](https://github.com/jiasenlu/visDial.pytorch) | 94 | -| [Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Multi-Scale_Continuous_CRFs_CVPR_2017_paper.html) | CVPR | [code](https://github.com/danxuhk/ContinuousCRF-CNN) | 93 | -| [Octree Generating Networks: Efficient Convolutional Architectures for High-Resolution 3D Outputs](http://openaccess.thecvf.com/content_iccv_2017/html/Tatarchenko_Octree_Generating_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/lmb-freiburg/ogn) | 92 | -| [Semantic Autoencoder for Zero-Shot Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Kodirov_Semantic_Autoencoder_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Elyorcv/SAE) | 92 | -| [Deep Hyperspherical Learning](http://papers.nips.cc/paper/6984-deep-hyperspherical-learning.pdf) | NIPS | [code](https://github.com/wy1iu/SphereNet) | 92 | -| [Decoupled Neural Interfaces using Synthetic Gradients](http://proceedings.mlr.press/v70/jaderberg17a.html) | ICML | [code](https://github.com/andrewliao11/dni.pytorch) | 90 | -| [Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks](http://papers.nips.cc/paper/6960-geometric-matrix-completion-with-recurrent-multi-graph-neural-networks.pdf) | NIPS | [code](https://github.com/fmonti/mgcnn) | 90 | -| [Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search](http://papers.nips.cc/paper/6780-practical-bayesian-optimization-for-model-fitting-with-bayesian-adaptive-direct-search.pdf) | NIPS | [code](https://github.com/lacerbi/bads) | 90 | -| [Optical Flow Estimation Using a Spatial Pyramid Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Ranjan_Optical_Flow_Estimation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sniklaus/pytorch-spynet) | 90 | -| [AMC: Attention guided Multi-modal Correlation Learning for Image Search](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_AMC_Attention_guided_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kanchen-usc/AMC_ATT) | 90 | -| [Deep Video Deblurring for Hand-Held Cameras](http://openaccess.thecvf.com/content_cvpr_2017/html/Su_Deep_Video_Deblurring_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shuochsu/DeepVideoDeblurring) | 89 | -| [Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data](http://papers.nips.cc/paper/6784-unsupervised-learning-of-disentangled-and-interpretable-representations-from-sequential-data.pdf) | NIPS | [code](https://github.com/wnhsu/FactorizedHierarchicalVAE) | 88 | -| [Causal Effect Inference with Deep Latent-Variable Models](http://papers.nips.cc/paper/7223-causal-effect-inference-with-deep-latent-variable-models.pdf) | NIPS | [code](https://github.com/AMLab-Amsterdam/CEVAE) | 87 | -| [GANs for Biological Image Synthesis](http://openaccess.thecvf.com/content_iccv_2017/html/Osokin_GANs_for_Biological_ICCV_2017_paper.html) | ICCV | [code](https://github.com/aosokin/biogans) | 85 | -| [MMD GAN: Towards Deeper Understanding of Moment Matching Network](http://papers.nips.cc/paper/6815-mmd-gan-towards-deeper-understanding-of-moment-matching-network.pdf) | NIPS | [code](https://github.com/OctoberChang/MMD-GAN) | 84 | -| [Representation Learning by Learning to Count](http://openaccess.thecvf.com/content_iccv_2017/html/Noroozi_Representation_Learning_by_ICCV_2017_paper.html) | ICCV | [code](https://github.com/gitlimlab/Representation-Learning-by-Learning-to-Count) | 84 | -| [Optical Flow in Mostly Rigid Scenes](http://openaccess.thecvf.com/content_cvpr_2017/html/Wulff_Optical_Flow_in_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jswulff/mrflow) | 83 | -| [Fast-Slow Recurrent Neural Networks](http://papers.nips.cc/paper/7173-fast-slow-recurrent-neural-networks.pdf) | NIPS | [code](https://github.com/amujika/Fast-Slow-LSTM) | 82 | -| [Unsupervised Video Summarization With Adversarial LSTM Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Mahasseni_Unsupervised_Video_Summarization_CVPR_2017_paper.html) | CVPR | [code](https://github.com/j-min/Adversarial_Video_Summary) | 82 | -| [Constrained Policy Optimization](http://proceedings.mlr.press/v70/achiam17a.html) | ICML | [code](https://github.com/jachiam/cpo) | 81 | -| [A-NICE-MC: Adversarial Training for MCMC](http://papers.nips.cc/paper/7099-a-nice-mc-adversarial-training-for-mcmc.pdf) | NIPS | [code](https://github.com/jiamings/a-nice-mc) | 80 | -| [Coarse-To-Fine Volumetric Prediction for Single-Image 3D Human Pose](http://openaccess.thecvf.com/content_cvpr_2017/html/Pavlakos_Coarse-To-Fine_Volumetric_Prediction_CVPR_2017_paper.html) | CVPR | [code](https://github.com/geopavlakos/c2f-vol-train) | 80 | -| [End-To-End Instance Segmentation With Recurrent Attention](http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_End-To-End_Instance_Segmentation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/renmengye/rec-attend-public) | 78 | -| [DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data](http://openaccess.thecvf.com/content_cvpr_2017/html/Gurumurthy_DeLiGAN__Generative_CVPR_2017_paper.html) | CVPR | [code](https://github.com/val-iisc/deligan) | 78 | -| [Learning Shape Abstractions by Assembling Volumetric Primitives](http://openaccess.thecvf.com/content_cvpr_2017/html/Tulsiani_Learning_Shape_Abstractions_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shubhtuls/volumetricPrimitives) | 77 | -| [Local Binary Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Juefei-Xu_Local_Binary_Convolutional_CVPR_2017_paper.html) | CVPR | [code](https://github.com/juefeix/lbcnn.torch) | 77 | -| [Raster-To-Vector: Revisiting Floorplan Transformation](http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Raster-To-Vector_Revisiting_Floorplan_ICCV_2017_paper.html) | ICCV | [code](https://github.com/art-programmer/FloorplanTransformation) | 76 | -| [Positive-Unlabeled Learning with Non-Negative Risk Estimator](http://papers.nips.cc/paper/6765-positive-unlabeled-learning-with-non-negative-risk-estimator.pdf) | NIPS | [code](https://github.com/kiryor/nnPUlearning) | 76 | -| [Hard-Aware Deeply Cascaded Embedding](http://openaccess.thecvf.com/content_iccv_2017/html/Yuan_Hard-Aware_Deeply_Cascaded_ICCV_2017_paper.html) | ICCV | [code](https://github.com/PkuRainBow/Hard-Aware-Deeply-Cascaded-Embedding_release) | 75 | -| [Deep Image Harmonization](http://openaccess.thecvf.com/content_cvpr_2017/html/Tsai_Deep_Image_Harmonization_CVPR_2017_paper.html) | CVPR | [code](https://github.com/wasidennis/DeepHarmonization) | 73 | -| [Shape Completion Using 3D-Encoder-Predictor CNNs and Shape Synthesis](http://openaccess.thecvf.com/content_cvpr_2017/html/Dai_Shape_Completion_Using_CVPR_2017_paper.html) | CVPR | [code](https://github.com/angeladai/cnncomplete) | 73 | -| [Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Not_All_Pixels_CVPR_2017_paper.html) | CVPR | [code](https://github.com/liuziwei7/region-conv) | 73 | -| [Improved Stereo Matching With Constant Highway Networks and Reflective Confidence Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Shaked_Improved_Stereo_Matching_CVPR_2017_paper.html) | CVPR | [code](https://github.com/amitshaked/resmatch) | 72 | -| [Query-Guided Regression Network With Context Policy for Phrase Grounding](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Query-Guided_Regression_Network_ICCV_2017_paper.html) | ICCV | [code](https://github.com/kanchen-usc/QRC-Net) | 72 | -| [Top-Down Visual Saliency Guided by Captions](http://openaccess.thecvf.com/content_cvpr_2017/html/Ramanishka_Top-Down_Visual_Saliency_CVPR_2017_paper.html) | CVPR | [code](https://github.com/VisionLearningGroup/caption-guided-saliency) | 72 | -| [Feedback Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Zamir_Feedback_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/amir32002/feedback-networks) | 72 | -| [What Actions Are Needed for Understanding Human Actions in Videos?](http://openaccess.thecvf.com/content_iccv_2017/html/Sigurdsson_What_Actions_Are_ICCV_2017_paper.html) | ICCV | [code](https://github.com/gsig/actions-for-actions) | 71 | -| [Xception: Deep Learning With Depthwise Separable Convolutions](http://openaccess.thecvf.com/content_cvpr_2017/html/Chollet_Xception_Deep_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tstandley/Xception-PyTorch) | 71 | -| [Action-Decision Networks for Visual Tracking With Deep Reinforcement Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Yun_Action-Decision_Networks_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hellbell/ADNet) | 71 | -| [Video Propagation Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Jampani_Video_Propagation_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/varunjampani/video_prop_networks) | 70 | -| [Image-To-Image Translation With Conditional Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/williamFalcon/pix2pix-keras) | 70 | -| [Quality Aware Network for Set to Set Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Quality_Aware_Network_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sciencefans/Quality-Aware-Network) | 69 | -| [Self-Supervised Learning of Visual Features Through Embedding Images Into Text Topic Spaces](http://openaccess.thecvf.com/content_cvpr_2017/html/Gomez_Self-Supervised_Learning_of_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lluisgomez/TextTopicNet) | 69 | -| [Deep Subspace Clustering Networks](http://papers.nips.cc/paper/6608-deep-subspace-clustering-networks.pdf) | NIPS | [code](https://github.com/panji1990/Deep-subspace-clustering-networks) | 68 | -| [Escape From Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models](http://openaccess.thecvf.com/content_iccv_2017/html/Klokov_Escape_From_Cells_ICCV_2017_paper.html) | ICCV | [code](https://github.com/fxia22/kdnet.pytorch) | 68 | -| [A Distributional Perspective on Reinforcement Learning](http://proceedings.mlr.press/v70/bellemare17a.html) | ICML | [code](https://github.com/Silvicek/distributional-dqn) | 68 | -| [Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Physically-Based_Rendering_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yindaz/pbrs) | 67 | -| [Deep Transfer Learning with Joint Adaptation Networks](http://proceedings.mlr.press/v70/long17a.html) | ICML | [code](https://github.com/USTCPCS/CVPR2018_attention) | 67 | -| [Training Deep Networks without Learning Rates Through Coin Betting](http://papers.nips.cc/paper/6811-training-deep-networks-without-learning-rates-through-coin-betting.pdf) | NIPS | [code](https://github.com/bremen79/cocob) | 66 | -| [Full Resolution Image Compression With Recurrent Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Toderici_Full_Resolution_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/1zb/pytorch-image-comp-rnn) | 66 | -| [SurfaceNet: An End-To-End 3D Neural Network for Multiview Stereopsis](http://openaccess.thecvf.com/content_iccv_2017/html/Ji_SurfaceNet_An_End-To-End_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mjiUST/SurfaceNet) | 66 | -| [Doubly Stochastic Variational Inference for Deep Gaussian Processes](http://papers.nips.cc/paper/7045-doubly-stochastic-variational-inference-for-deep-gaussian-processes.pdf) | NIPS | [code](https://github.com/ICL-SML/Doubly-Stochastic-DGP) | 66 | -| [TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals](http://openaccess.thecvf.com/content_iccv_2017/html/Gao_TURN_TAP_Temporal_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jiyanggao/TURN-TAP) | 66 | -| [Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-Identification](http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Jointly_Attentive_Spatial-Temporal_ICCV_2017_paper.html) | ICCV | [code](https://github.com/shuangjiexu/Spatial-Temporal-Pooling-Networks-ReID) | 65 | -| [Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes With Deep Generative Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Soltani_Synthesizing_3D_Shapes_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Amir-Arsalan/Synthesize3DviaDepthOrSil) | 65 | -| [Dance Dance Convolution](http://proceedings.mlr.press/v70/donahue17a.html) | ICML | [code](https://github.com/chrisdonahue/ddc) | 65 | -| [Borrowing Treasures From the Wealthy: Deep Transfer Learning Through Selective Joint Fine-Tuning](http://openaccess.thecvf.com/content_cvpr_2017/html/Ge_Borrowing_Treasures_From_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ZYYSzj/Selective-Joint-Fine-tuning) | 64 | -| [Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes](http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Curriculum_Domain_Adaptation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/YangZhang4065/AdaptationSeg) | 64 | -| [Toward Controlled Generation of Text](http://proceedings.mlr.press/v70/hu17e.html) | ICML | [code](https://github.com/GBLin5566/toward-controlled-generation-of-text-pytorch) | 63 | -| [Person Re-Identification in the Wild](http://openaccess.thecvf.com/content_cvpr_2017/html/Zheng_Person_Re-Identification_in_CVPR_2017_paper.html) | CVPR | [code](https://github.com/liangzheng06/PRW-baseline) | 63 | -| [ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching](http://papers.nips.cc/paper/7133-alice-towards-understanding-adversarial-learning-for-joint-distribution-matching.pdf) | NIPS | [code](https://github.com/ChunyuanLI/ALICE) | 63 | -| [Differentiable Learning of Logical Rules for Knowledge Base Reasoning](http://papers.nips.cc/paper/6826-differentiable-learning-of-logical-rules-for-knowledge-base-reasoning.pdf) | NIPS | [code](https://github.com/fanyangxyz/Neural-LP) | 62 | -| [Person Search With Natural Language Description](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Person_Search_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ShuangLI59/Person-Search-with-Natural-Language-Description) | 61 | -| [Multi-Channel Weighted Nuclear Norm Minimization for Real Color Image Denoising](http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Multi-Channel_Weighted_Nuclear_ICCV_2017_paper.html) | ICCV | [code](https://github.com/csjunxu/MCWNNM-ICCV2017) | 61 | -| [Playing for Benchmarks](http://openaccess.thecvf.com/content_iccv_2017/html/Richter_Playing_for_Benchmarks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/PatrykChrabaszcz/Canonical_ES_Atari) | 61 | -| [Unsupervised Learning by Predicting Noise](http://proceedings.mlr.press/v70/bojanowski17a.html) | ICML | [code](https://github.com/facebookresearch/noise-as-targets) | 60 | -| [Localizing Moments in Video With Natural Language](http://openaccess.thecvf.com/content_iccv_2017/html/Hendricks_Localizing_Moments_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/LisaAnne/LocalizingMoments) | 60 | -| [End-To-End 3D Face Reconstruction With Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Dou_End-To-End_3D_Face_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ShownX/mxnet-E2FAR) | 60 | -| [CoupleNet: Coupling Global Structure With Local Parts for Object Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_CoupleNet_Coupling_Global_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tshizys/CoupleNet) | 59 | -| [AdaGAN: Boosting Generative Models](http://papers.nips.cc/paper/7126-adagan-boosting-generative-models.pdf) | NIPS | [code](https://github.com/tolstikhin/adagan) | 59 | -| [Convolutional Gaussian Processes](http://papers.nips.cc/paper/6877-convolutional-gaussian-processes.pdf) | NIPS | [code](https://github.com/markvdw/convgp/) | 57 | -| [A Deep Regression Architecture With Two-Stage Re-Initialization for High Performance Facial Landmark Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Lv_A_Deep_Regression_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shaoxiaohu/Face_Alignment_Two_Stage_Re-initialization) | 57 | -| [Modeling Relationships in Referential Expressions With Compositional Modular Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Modeling_Relationships_in_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ronghanghu/cmn) | 57 | -| [Curiosity-driven Exploration by Self-supervised Prediction](http://proceedings.mlr.press/v70/pathak17a.html) | ICML | [code](https://github.com/kimhc6028/pytorch-noreward-rl) | 56 | -| [Wavelet-SRNet: A Wavelet-Based CNN for Multi-Scale Face Super Resolution](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Wavelet-SRNet_A_Wavelet-Based_ICCV_2017_paper.html) | ICCV | [code](https://github.com/hhb072/WaveletSRNet) | 56 | -| [The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process](http://papers.nips.cc/paper/7252-the-neural-hawkes-process-a-neurally-self-modulating-multivariate-point-process.pdf) | NIPS | [code](https://github.com/HMEIatJHU/neurawkes) | 56 | -| [Online and Linear-Time Attention by Enforcing Monotonic Alignments](http://proceedings.mlr.press/v70/raffel17a.html) | ICML | [code](https://github.com/craffel/mad) | 56 | -| [Neural Expectation Maximization](http://papers.nips.cc/paper/7246-neural-expectation-maximization.pdf) | NIPS | [code](https://github.com/sjoerdvansteenkiste/Neural-EM) | 56 | -| [Dense-Captioning Events in Videos](http://openaccess.thecvf.com/content_iccv_2017/html/Krishna_Dense-Captioning_Events_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ranjaykrishna/densevid_eval) | 55 | -| [Factorized Bilinear Models for Image Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Li_Factorized_Bilinear_Models_ICCV_2017_paper.html) | ICCV | [code](https://github.com/lyttonhao/Factorized-Bilinear-Network) | 55 | -| [Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee](http://papers.nips.cc/paper/6910-net-trim-convex-pruning-of-deep-neural-networks-with-performance-guarantee.pdf) | NIPS | [code](https://github.com/DNNToolBox/Net-Trim-v1) | 54 | -| [On-the-fly Operation Batching in Dynamic Computation Graphs](http://papers.nips.cc/paper/6986-on-the-fly-operation-batching-in-dynamic-computation-graphs.pdf) | NIPS | [code](https://github.com/neulab/dynet-benchmark) | 54 | -| [Visual Translation Embedding Network for Visual Relation Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Visual_Translation_Embedding_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zawlin/cvpr17_vtranse) | 54 | -| [Learning Blind Motion Deblurring](http://openaccess.thecvf.com/content_iccv_2017/html/Wieschollek_Learning_Blind_Motion_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cgtuebingen/learning-blind-motion-deblurring) | 54 | -| [A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning](http://papers.nips.cc/paper/6951-a-disentangled-recognition-and-nonlinear-dynamics-model-for-unsupervised-learning.pdf) | NIPS | [code](https://github.com/simonkamronn/kvae) | 53 | -| [Towards Diverse and Natural Image Descriptions via a Conditional GAN](http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Towards_Diverse_and_ICCV_2017_paper.html) | ICCV | [code](https://github.com/doubledaibo/gancaption_iccv2017) | 53 | -| [CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Shou_CDC_Convolutional-De-Convolutional_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ColumbiaDVMM/CDC) | 53 | -| [A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing](http://openaccess.thecvf.com/content_iccv_2017/html/Fan_A_Generic_Deep_ICCV_2017_paper.html) | ICCV | [code](https://github.com/fqnchina/CEILNet) | 52 | -| [Deep IV: A Flexible Approach for Counterfactual Prediction](http://proceedings.mlr.press/v70/hartford17a.html) | ICML | [code](https://github.com/jhartford/DeepIV) | 52 | -| [Triangle Generative Adversarial Networks](http://papers.nips.cc/paper/7109-triangle-generative-adversarial-networks.pdf) | NIPS | [code](https://github.com/LiqunChen0606/Triangle-GAN) | 51 | -| [EAST: An Efficient and Accurate Scene Text Detector](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_EAST_An_Efficient_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Kathrine94/EAST) | 51 | -| [SST: Single-Stream Temporal Action Proposals](http://openaccess.thecvf.com/content_cvpr_2017/html/Buch_SST_Single-Stream_Temporal_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ranjaykrishna/SST) | 51 | -| [Predicting Deeper Into the Future of Semantic Segmentation](http://openaccess.thecvf.com/content_iccv_2017/html/Luc_Predicting_Deeper_Into_ICCV_2017_paper.html) | ICCV | [code](https://github.com/facebookresearch/SegmPred) | 51 | -| [L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space](http://openaccess.thecvf.com/content_cvpr_2017/html/Tian_L2-Net_Deep_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yuruntian/L2-Net) | 51 | -| [TALL: Temporal Activity Localization via Language Query](http://openaccess.thecvf.com/content_iccv_2017/html/Gao_TALL_Temporal_Activity_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jiyanggao/TALL) | 50 | -| [Hybrid Reward Architecture for Reinforcement Learning](http://papers.nips.cc/paper/7123-hybrid-reward-architecture-for-reinforcement-learning.pdf) | NIPS | [code](https://github.com/Maluuba/hra) | 50 | -| [Fast Fourier Color Constancy](http://openaccess.thecvf.com/content_cvpr_2017/html/Barron_Fast_Fourier_Color_CVPR_2017_paper.html) | CVPR | [code](https://github.com/google/ffcc) | 49 | -| [Modulating early visual processing by language](http://papers.nips.cc/paper/7237-modulating-early-visual-processing-by-language.pdf) | NIPS | [code](https://github.com/GuessWhatGame/guesswhat) | 49 | -| [Adversarial Examples for Semantic Segmentation and Object Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Xie_Adversarial_Examples_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cihangxie/DAG) | 49 | -| [Learning Discrete Representations via Information Maximizing Self-Augmented Training](http://proceedings.mlr.press/v70/hu17b.html) | ICML | [code](https://github.com/weihua916/imsat) | 49 | -| [Efficient Diffusion on Region Manifolds: Recovering Small Objects With Compact CNN Representations](http://openaccess.thecvf.com/content_cvpr_2017/html/Iscen_Efficient_Diffusion_on_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ahmetius/diffusion-retrieval) | 48 | -| [Real Time Image Saliency for Black Box Classifiers](http://papers.nips.cc/paper/7272-real-time-image-saliency-for-black-box-classifiers.pdf) | NIPS | [code](https://github.com/PiotrDabkowski/pytorch-saliency) | 48 | -| [FC4: Fully Convolutional Color Constancy With Confidence-Weighted Pooling](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_FC4_Fully_Convolutional_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yuanming-hu/fc4) | 47 | -| [Multiple People Tracking by Lifted Multicut and Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2017/html/Tang_Multiple_People_Tracking_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jutanke/cabbage) | 47 | -| [Learned D-AMP: Principled Neural Network based Compressive Image Recovery](http://papers.nips.cc/paper/6774-learned-d-amp-principled-neural-network-based-compressive-image-recovery.pdf) | NIPS | [code](https://github.com/ricedsp/D-AMP_Toolbox) | 47 | -| [GP CaKe: Effective brain connectivity with causal kernels](http://papers.nips.cc/paper/6696-gp-cake-effective-brain-connectivity-with-causal-kernels.pdf) | NIPS | [code](https://github.com/LucaAmbrogioni/GP-CaKe-project) | 46 | -| [Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network](http://papers.nips.cc/paper/6854-predicting-organic-reaction-outcomes-with-weisfeiler-lehman-network.pdf) | NIPS | [code](https://github.com/wengong-jin/nips17-rexgen) | 46 | -| [Semantic Video CNNs Through Representation Warping](http://openaccess.thecvf.com/content_iccv_2017/html/Gadde_Semantic_Video_CNNs_ICCV_2017_paper.html) | ICCV | [code](https://github.com/raghudeep/netwarp_public) | 46 | -| [Grammar Variational Autoencoder](http://proceedings.mlr.press/v70/kusner17a.html) | ICML | [code](https://github.com/episodeyang/grammar_variational_autoencoder) | 46 | -| [EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis](http://openaccess.thecvf.com/content_iccv_2017/html/Sajjadi_EnhanceNet_Single_Image_ICCV_2017_paper.html) | ICCV | [code](https://github.com/msmsajjadi/EnhanceNet-Code) | 46 | -| [Safe Model-based Reinforcement Learning with Stability Guarantees](http://papers.nips.cc/paper/6692-safe-model-based-reinforcement-learning-with-stability-guarantees.pdf) | NIPS | [code](https://github.com/befelix/safe_learning) | 45 | -| [Deep Spectral Clustering Learning](http://proceedings.mlr.press/v70/law17a.html) | ICML | [code](https://github.com/wlwkgus/DeepSpectralClustering) | 45 | -| [Semantic Compositional Networks for Visual Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Gan_Semantic_Compositional_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zhegan27/Semantic_Compositional_Nets) | 45 | -| [On-Demand Learning for Deep Image Restoration](http://openaccess.thecvf.com/content_iccv_2017/html/Gao_On-Demand_Learning_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/rhgao/on-demand-learning) | 45 | -| [Video Pixel Networks](http://proceedings.mlr.press/v70/kalchbrenner17a.html) | ICML | [code](https://github.com/3ammor/Video-Pixel-Networks) | 45 | -| [Stabilizing Training of Generative Adversarial Networks through Regularization](http://papers.nips.cc/paper/6797-stabilizing-training-of-generative-adversarial-networks-through-regularization.pdf) | NIPS | [code](https://github.com/rothk/Stabilizing_GANs) | 45 | -| [Structured Bayesian Pruning via Log-Normal Multiplicative Noise](http://papers.nips.cc/paper/7254-structured-bayesian-pruning-via-log-normal-multiplicative-noise.pdf) | NIPS | [code](https://github.com/necludov/group-sparsity-sbp) | 44 | -| [Deriving Neural Architectures from Sequence and Graph Kernels](http://proceedings.mlr.press/v70/lei17a.html) | ICML | [code](https://github.com/taolei87/icml17_knn) | 44 | -| [Masked Autoregressive Flow for Density Estimation](http://papers.nips.cc/paper/6828-masked-autoregressive-flow-for-density-estimation.pdf) | NIPS | [code](https://github.com/gpapamak/maf) | 44 | -| [Unsupervised Adaptation for Deep Stereo](http://openaccess.thecvf.com/content_iccv_2017/html/Tonioni_Unsupervised_Adaptation_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/CVLAB-Unibo/Unsupervised-Adaptation-for-Deep-Stereo) | 44 | -| [Learning Residual Images for Face Attribute Manipulation](http://openaccess.thecvf.com/content_cvpr_2017/html/Shen_Learning_Residual_Images_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Zhongdao/FaceAttributeManipulation) | 43 | -| [Learning to Generate Long-term Future via Hierarchical Prediction](http://proceedings.mlr.press/v70/villegas17a.html) | ICML | [code](https://github.com/rubenvillegas/icml2017hierchvid) | 43 | -| [Accurate Optical Flow via Direct Cost Volume Processing](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Accurate_Optical_Flow_CVPR_2017_paper.html) | CVPR | [code](https://github.com/IntelVCL/dcflow) | 42 | -| [Generalized Orderless Pooling Performs Implicit Salient Matching](http://openaccess.thecvf.com/content_iccv_2017/html/Simon_Generalized_Orderless_Pooling_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cvjena/alpha_pooling) | 42 | -| [Comparative Evaluation of Hand-Crafted and Learned Local Features](http://openaccess.thecvf.com/content_cvpr_2017/html/Schonberger_Comparative_Evaluation_of_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ahojnnes/local-feature-evaluation) | 42 | -| [SchNet: A continuous-filter convolutional neural network for modeling quantum interactions](http://papers.nips.cc/paper/6700-schnet-a-continuous-filter-convolutional-neural-network-for-modeling-quantum-interactions.pdf) | NIPS | [code](https://github.com/atomistic-machine-learning/SchNet) | 41 | -| [Temporal Generative Adversarial Nets With Singular Value Clipping](http://openaccess.thecvf.com/content_iccv_2017/html/Saito_Temporal_Generative_Adversarial_ICCV_2017_paper.html) | ICCV | [code](https://github.com/pfnet-research/tgan) | 41 | -| [Multiplicative Normalizing Flows for Variational Bayesian Neural Networks](http://proceedings.mlr.press/v70/louizos17a.html) | ICML | [code](https://github.com/AMLab-Amsterdam/MNF_VBNN) | 41 | -| [Neural Scene De-Rendering](http://openaccess.thecvf.com/content_cvpr_2017/html/Wu_Neural_Scene_De-Rendering_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jiajunwu/nsd) | 40 | -| [Semantic Image Inpainting With Deep Generative Models](http://openaccess.thecvf.com/content_cvpr_2017/html/Yeh_Semantic_Image_Inpainting_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ChengBinJin/semantic-image-inpainting) | 40 | -| [A Linear-Time Kernel Goodness-of-Fit Test](http://papers.nips.cc/paper/6630-a-linear-time-kernel-goodness-of-fit-test.pdf) | NIPS | [code](https://github.com/wittawatj/kernel-gof) | 40 | -| [Least Squares Generative Adversarial Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Mao_Least_Squares_Generative_ICCV_2017_paper.html) | ICCV | [code](https://github.com/GunhoChoi/LSGAN-TF) | 39 | -| [Diversified Texture Synthesis With Feed-Forward Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Diversified_Texture_Synthesis_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Yijunmaverick/MultiTextureSynthesis) | 39 | -| [No Fuss Distance Metric Learning Using Proxies](http://openaccess.thecvf.com/content_iccv_2017/html/Movshovitz-Attias_No_Fuss_Distance_ICCV_2017_paper.html) | ICCV | [code](https://github.com/dichotomies/proxy-nca) | 38 | -| [Template Matching With Deformable Diversity Similarity](http://openaccess.thecvf.com/content_cvpr_2017/html/Talmi_Template_Matching_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/roimehrez/DDIS) | 38 | -| [What's in a Question: Using Visual Questions as a Form of Supervision](http://openaccess.thecvf.com/content_cvpr_2017/html/Ganju_Whats_in_a_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sidgan/whats_in_a_question) | 38 | -| [Face Normals "In-The-Wild" Using Fully Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Trigeorgis_Face_Normals_In-The-Wild_CVPR_2017_paper.html) | CVPR | [code](https://github.com/trigeorgis/face_normals_cvpr17) | 38 | -| [Conditional Image Synthesis with Auxiliary Classifier GANs](http://proceedings.mlr.press/v70/odena17a.html) | ICML | [code](https://github.com/kimhc6028/acgan-pytorch) | 37 | -| [Neural Episodic Control](http://proceedings.mlr.press/v70/pritzel17a.html) | ICML | [code](https://github.com/EndingCredits/Neural-Episodic-Control) | 37 | -| [3D-PRNN: Generating Shape Primitives With Recurrent Neural Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Zou_3D-PRNN_Generating_Shape_ICCV_2017_paper.html) | ICCV | [code](https://github.com/zouchuhang/3D-PRNN) | 37 | -| [Structured Embedding Models for Grouped Data](http://papers.nips.cc/paper/6629-structured-embedding-models-for-grouped-data.pdf) | NIPS | [code](https://github.com/mariru/structured_embeddings) | 36 | -| [Learning Active Learning from Data](http://papers.nips.cc/paper/7010-learning-active-learning-from-data.pdf) | NIPS | [code](https://github.com/ksenia-konyushkova/LAL) | 36 | -| [Unified Deep Supervised Domain Adaptation and Generalization](http://openaccess.thecvf.com/content_iccv_2017/html/Motiian_Unified_Deep_Supervised_ICCV_2017_paper.html) | ICCV | [code](https://github.com/samotiian/CCSA) | 35 | -| [Transformation-Grounded Image Generation Network for Novel 3D View Synthesis](http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Transformation-Grounded_Image_Generation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/silverbottlep/tvsn) | 35 | -| [Structured Attentions for Visual Question Answering](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Structured_Attentions_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/shtechair/vqa-sva) | 34 | -| [Geometric Loss Functions for Camera Pose Regression With Deep Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Kendall_Geometric_Loss_Functions_CVPR_2017_paper.html) | CVPR | [code](https://github.com/futurely/deep-camera-relocalization) | 34 | -| [VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization](http://openaccess.thecvf.com/content_cvpr_2017/html/Clark_VidLoc_A_Deep_CVPR_2017_paper.html) | CVPR | [code](https://github.com/futurely/deep-camera-relocalization) | 34 | -| [QMDP-Net: Deep Learning for Planning under Partial Observability](http://papers.nips.cc/paper/7055-qmdp-net-deep-learning-for-planning-under-partial-observability.pdf) | NIPS | [code](https://github.com/AdaCompNUS/qmdp-net) | 34 | -| [Using Ranking-CNN for Age Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Using_Ranking-CNN_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/RankingCNN/Using-Ranking-CNN-for-Age-Estimation) | 33 | -| [Hierarchical Boundary-Aware Neural Encoder for Video Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Baraldi_Hierarchical_Boundary-Aware_Neural_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Yugnaynehc/banet) | 33 | -| [Unsupervised Learning of Disentangled Representations from Video](http://papers.nips.cc/paper/7028-unsupervised-learning-of-disentangled-representations-from-video.pdf) | NIPS | [code](https://github.com/edenton/drnet-py) | 32 | -| [Deep Learning on Lie Groups for Skeleton-Based Action Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Deep_Learning_on_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zzhiwu/LieNet) | 32 | -| [Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Liang_Deep_Variation-Structured_Reinforcement_CVPR_2017_paper.html) | CVPR | [code](https://github.com/nexusapoorvacus/DeepVariationStructuredRL) | 32 | -| [3D Point Cloud Registration for Localization Using a Deep Neural Network Auto-Encoder](http://openaccess.thecvf.com/content_cvpr_2017/html/Elbaz_3D_Point_Cloud_CVPR_2017_paper.html) | CVPR | [code](https://github.com/gilbaz/LORAX) | 32 | -| [StyleNet: Generating Attractive Visual Captions With Styles](http://openaccess.thecvf.com/content_cvpr_2017/html/Gan_StyleNet_Generating_Attractive_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kacky24/stylenet) | 32 | -| [Dynamic Word Embeddings](http://proceedings.mlr.press/v70/bamler17a.html) | ICML | [code](https://github.com/YingyuLiang/SemanticVector) | 32 | -| [Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon](http://papers.nips.cc/paper/7071-learning-to-prune-deep-neural-networks-via-layer-wise-optimal-brain-surgeon.pdf) | NIPS | [code](https://github.com/csyhhu/L-OBS) | 31 | -| [Continual Learning Through Synaptic Intelligence](http://proceedings.mlr.press/v70/zenke17a.html) | ICML | [code](https://github.com/ganguli-lab/pathint) | 31 | -| [Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes](http://openaccess.thecvf.com/content_cvpr_2017/html/Pohlen_Full-Resolution_Residual_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hiwonjoon/tf-frrn) | 31 | -| [Learning Detection With Diverse Proposals](http://openaccess.thecvf.com/content_cvpr_2017/html/Azadi_Learning_Detection_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/azadis/LDDP) | 31 | -| [LCNN: Lookup-Based Convolutional Neural Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Bagherinezhad_LCNN_Lookup-Based_Convolutional_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hessamb/lcnn) | 31 | -| [Towards Accurate Multi-Person Pose Estimation in the Wild](http://openaccess.thecvf.com/content_cvpr_2017/html/Papandreou_Towards_Accurate_Multi-Person_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hackiey/keypoints) | 30 | -| [Real-Time Neural Style Transfer for Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Real-Time_Neural_Style_CVPR_2017_paper.html) | CVPR | [code](https://github.com/curaai00/RT-StyleTransfer-forVideo) | 30 | -| [Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training](http://openaccess.thecvf.com/content_iccv_2017/html/Shetty_Speaking_the_Same_ICCV_2017_paper.html) | ICCV | [code](https://github.com/rakshithShetty/captionGAN) | 30 | -| [Deep Co-Occurrence Feature Learning for Visual Object Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Shih_Deep_Co-Occurrence_Feature_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yafangshih/Deep-COOC) | 29 | -| [Joint distribution optimal transportation for domain adaptation](http://papers.nips.cc/paper/6963-joint-distribution-optimal-transportation-for-domain-adaptation.pdf) | NIPS | [code](https://github.com/rflamary/JDOT) | 29 | -| [Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields](http://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Realtime_Multi-Person_2D_CVPR_2017_paper.html) | CVPR | [code](https://github.com/PoseAIChallenger/mxnet_pose_for_AI_challenger) | 29 | -| [SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization](http://proceedings.mlr.press/v70/kim17b.html) | ICML | [code](https://github.com/dalgu90/splitnet-wrn) | 29 | -| [The Statistical Recurrent Unit](http://proceedings.mlr.press/v70/oliva17a.html) | ICML | [code](https://github.com/DLHacks/SRU) | 29 | -| [A Unified Approach of Multi-Scale Deep and Hand-Crafted Features for Defocus Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Park_A_Unified_Approach_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zzangjinsun/DHDE_CVPR17) | 28 | -| [Learning Spread-Out Local Feature Descriptors](http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Learning_Spread-Out_Local_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ColumbiaDVMM/Spread-out_Local_Feature_Descriptor) | 28 | -| [Event-Based Visual Inertial Odometry](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Event-Based_Visual_Inertial_CVPR_2017_paper.html) | CVPR | [code](https://github.com/daniilidis-group/event_feature_tracking) | 27 | -| [DropoutNet: Addressing Cold Start in Recommender Systems](http://papers.nips.cc/paper/7081-dropoutnet-addressing-cold-start-in-recommender-systems.pdf) | NIPS | [code](https://github.com/layer6ai-labs/DropoutNet) | 27 | -| [Phrase Localization and Visual Relationship Detection With Comprehensive Image-Language Cues](http://openaccess.thecvf.com/content_iccv_2017/html/Plummer_Phrase_Localization_and_ICCV_2017_paper.html) | ICCV | [code](https://github.com/BryanPlummer/pl-clc) | 27 | -| [Harvesting Multiple Views for Marker-Less 3D Human Pose Annotations](http://openaccess.thecvf.com/content_cvpr_2017/html/Pavlakos_Harvesting_Multiple_Views_CVPR_2017_paper.html) | CVPR | [code](https://github.com/geopavlakos/harvesting) | 27 | -| [Deep 360 Pilot: Learning a Deep Agent for Piloting Through 360deg Sports Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Deep_360_Pilot_CVPR_2017_paper.html) | CVPR | [code](https://github.com/eborboihuc/Deep360Pilot-CVPR17) | 27 | -| [Neural Message Passing for Quantum Chemistry](http://proceedings.mlr.press/v70/gilmer17a.html) | ICML | [code](https://github.com/brain-research/mpnn) | 27 | -| [State-Frequency Memory Recurrent Neural Networks](http://proceedings.mlr.press/v70/hu17c.html) | ICML | [code](https://github.com/hhkunming/State-Frequency-Memory-Recurrent-Neural-Networks) | 27 | -| [DeepCD: Learning Deep Complementary Descriptors for Patch Representations](http://openaccess.thecvf.com/content_iccv_2017/html/Yang_DeepCD_Learning_Deep_ICCV_2017_paper.html) | ICCV | [code](https://github.com/shamangary/DeepCD) | 26 | -| [Contrastive Learning for Image Captioning](http://papers.nips.cc/paper/6691-contrastive-learning-for-image-captioning.pdf) | NIPS | [code](https://github.com/doubledaibo/clcaption_nips2017) | 26 | -| [Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure](http://papers.nips.cc/paper/6760-stochastic-optimization-with-variance-reduction-for-infinite-datasets-with-finite-sum-structure.pdf) | NIPS | [code](https://github.com/albietz/stochs) | 26 | -| [Learning High Dynamic Range From Outdoor Panoramas](http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Learning_High_Dynamic_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jacenfox/ldr2hdr-public) | 26 | -| [Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_SpeedAccuracy_Trade-Offs_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/rayanelleuch/Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors) | 26 | -| [Learning to Detect Salient Objects With Image-Level Supervision](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Learning_to_Detect_CVPR_2017_paper.html) | CVPR | [code](https://github.com/scott89/WSS) | 26 | -| [Improved Variational Autoencoders for Text Modeling using Dilated Convolutions](http://proceedings.mlr.press/v70/yang17d.html) | ICML | [code](https://github.com/ryokamoi/dcnn_textvae) | 26 | -| [Interspecies Knowledge Transfer for Facial Keypoint Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Rashid_Interspecies_Knowledge_Transfer_CVPR_2017_paper.html) | CVPR | [code](https://github.com/menorashid/animal_human_kp) | 25 | -| [YASS: Yet Another Spike Sorter](http://papers.nips.cc/paper/6989-yass-yet-another-spike-sorter.pdf) | NIPS | [code](https://github.com/paninski-lab/yass) | 25 | -| [Open Set Domain Adaptation](http://openaccess.thecvf.com/content_iccv_2017/html/Busto_Open_Set_Domain_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Heliot7/open-set-da) | 25 | -| [Domain-Adaptive Deep Network Compression](http://openaccess.thecvf.com/content_iccv_2017/html/Masana_Domain-Adaptive_Deep_Network_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mmasana/DALR) | 24 | -| [Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization](http://openaccess.thecvf.com/content_iccv_2017/html/Coskun_Long_Short-Term_Memory_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Seleucia/lstmkf_ICCV2017) | 24 | -| [Temporal Context Network for Activity Localization in Videos](http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Temporal_Context_Network_ICCV_2017_paper.html) | ICCV | [code](https://github.com/vdavid70619/TCN) | 24 | -| [Incremental Learning of Object Detectors Without Catastrophic Forgetting](http://openaccess.thecvf.com/content_iccv_2017/html/Shmelkov_Incremental_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/kshmelkov/incremental_detectors) | 24 | -| [Dense Captioning With Joint Inference and Visual Context](http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Dense_Captioning_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/linjieyangsc/densecap) | 24 | -| [Universal Adversarial Perturbations](http://openaccess.thecvf.com/content_cvpr_2017/html/Moosavi-Dezfooli_Universal_Adversarial_Perturbations_CVPR_2017_paper.html) | CVPR | [code](https://github.com/val-iisc/fast-feature-fool) | 24 | -| [Asymmetric Tri-training for Unsupervised Domain Adaptation](http://proceedings.mlr.press/v70/saito17a.html) | ICML | [code](https://github.com/vtddggg/ATDA) | 24 | -| [Reducing Reparameterization Gradient Variance](http://papers.nips.cc/paper/6961-reducing-reparameterization-gradient-variance.pdf) | NIPS | [code](https://github.com/andymiller/ReducedVarianceReparamGradients) | 24 | -| [Exploiting Saliency for Object Segmentation From Image Level Labels](http://openaccess.thecvf.com/content_cvpr_2017/html/Oh_Exploiting_Saliency_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/coallaoh/GuidedLabelling) | 24 | -| [A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering](http://papers.nips.cc/paper/6734-a-dirichlet-mixture-model-of-hawkes-processes-for-event-sequence-clustering.pdf) | NIPS | [code](https://github.com/HongtengXu/Hawkes-Process-Toolkit) | 24 | -| [Shading Annotations in the Wild](http://openaccess.thecvf.com/content_cvpr_2017/html/Kovacs_Shading_Annotations_in_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kovibalu/saw_release) | 24 | -| [Straight to Shapes: Real-Time Detection of Encoded Shapes](http://openaccess.thecvf.com/content_cvpr_2017/html/Jetley_Straight_to_Shapes_CVPR_2017_paper.html) | CVPR | [code](https://github.com/torrvision/straighttoshapes) | 23 | -| [Dual Discriminator Generative Adversarial Nets](http://papers.nips.cc/paper/6860-dual-discriminator-generative-adversarial-nets.pdf) | NIPS | [code](https://github.com/tund/D2GAN) | 23 | -| [Zero-Order Reverse Filtering](http://openaccess.thecvf.com/content_iccv_2017/html/Tao_Zero-Order_Reverse_Filtering_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jiangsutx/DeFilter) | 23 | -| [Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net](http://papers.nips.cc/paper/7026-variational-walkback-learning-a-transition-operator-as-a-stochastic-recurrent-net.pdf) | NIPS | [code](https://github.com/anirudh9119/walkback_nips17) | 23 | -| [Learning Spherical Convolution for Fast Features from 360° Imagery](http://papers.nips.cc/paper/6656-learning-spherical-convolution-for-fast-features-from-360-imagery.pdf) | NIPS | [code](https://github.com/sammy-su/Spherical-Convolution) | 22 | -| [Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier](http://proceedings.mlr.press/v70/futoma17a.html) | ICML | [code](https://github.com/jfutoma/MGP-RNN) | 22 | -| [Deep Cross-Modal Hashing](http://openaccess.thecvf.com/content_cvpr_2017/html/Jiang_Deep_Cross-Modal_Hashing_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jiangqy/DCMH-CVPR2017) | 22 | -| [When Unsupervised Domain Adaptation Meets Tensor Representations](http://openaccess.thecvf.com/content_iccv_2017/html/Lu_When_Unsupervised_Domain_ICCV_2017_paper.html) | ICCV | [code](https://github.com/poppinace/TAISL) | 22 | -| [Image Super-Resolution Using Dense Skip Connections](http://openaccess.thecvf.com/content_iccv_2017/html/Tong_Image_Super-Resolution_Using_ICCV_2017_paper.html) | ICCV | [code](https://github.com/kweisamx/TensorFlow-SR-DenseNet) | 22 | -| [Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Multimodal_Transfer_A_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fullfanta/multimodal_transfer) | 22 | -| [STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling](http://openaccess.thecvf.com/content_cvpr_2017/html/He_STD2P_RGBD_Semantic_CVPR_2017_paper.html) | CVPR | [code](https://github.com/SSAW14/STD2P) | 22 | -| [Learning Continuous Semantic Representations of Symbolic Expressions](http://proceedings.mlr.press/v70/allamanis17a.html) | ICML | [code](https://github.com/mast-group/eqnet) | 22 | -| [Deep Growing Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Wang_Deep_Growing_Learning_ICCV_2017_paper.html) | ICCV | [code](https://github.com/QData/deep2Read) | 21 | -| [Combined Group and Exclusive Sparsity for Deep Neural Networks](http://proceedings.mlr.press/v70/yoon17a.html) | ICML | [code](https://github.com/jaehong-yoon93/CGES) | 21 | -| [Hash Embeddings for Efficient Word Representations](http://papers.nips.cc/paper/7078-hash-embeddings-for-efficient-word-representations.pdf) | NIPS | [code](https://github.com/dsv77/hashembedding/) | 21 | -| [Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM](http://papers.nips.cc/paper/6850-accuracy-first-selecting-a-differential-privacy-level-for-accuracy-constrained-erm.pdf) | NIPS | [code](https://github.com/steven7woo/Accuracy-First-Differential-Privacy) | 21 | -| [Disentangled Representation Learning GAN for Pose-Invariant Face Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Tran_Disentangled_Representation_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zhangjunh/DR-GAN-by-pytorch) | 21 | -| [Learning to Pivot with Adversarial Networks](http://papers.nips.cc/paper/6699-learning-to-pivot-with-adversarial-networks.pdf) | NIPS | [code](https://github.com/glouppe/paper-learning-to-pivot) | 21 | -| [Learning Dynamic Siamese Network for Visual Object Tracking](http://openaccess.thecvf.com/content_iccv_2017/html/Guo_Learning_Dynamic_Siamese_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tsingqguo/DSiam) | 21 | -| [POSEidon: Face-From-Depth for Driver Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Borghi_POSEidon_Face-From-Depth_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/gdubrg/POSEidon-Biwi) | 20 | -| [Deep Metric Learning via Facility Location](http://openaccess.thecvf.com/content_cvpr_2017/html/Song_Deep_Metric_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/CongWeilin/cluster-loss-tensorflow) | 20 | -| [Automatic Spatially-Aware Fashion Concept Discovery](http://openaccess.thecvf.com/content_iccv_2017/html/Han_Automatic_Spatially-Aware_Fashion_ICCV_2017_paper.html) | ICCV | [code](https://github.com/xthan/fashion-200k) | 20 | -| [The Numerics of GANs](http://papers.nips.cc/paper/6779-the-numerics-of-gans.pdf) | NIPS | [code](https://github.com/LMescheder/TheNumericsOfGANs) | 20 | -| [From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur](http://openaccess.thecvf.com/content_cvpr_2017/html/Gong_From_Motion_Blur_CVPR_2017_paper.html) | CVPR | [code](https://github.com/donggong1/motion-flow-syn) | 20 | -| [Unpaired Image-To-Image Translation Using Cycle-Consistent Adversarial Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Unpaired_Image-To-Image_Translation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/adepierre/Caffe_CycleGAN) | 20 | -| [Zero-Inflated Exponential Family Embeddings](http://proceedings.mlr.press/v70/liu17a.html) | ICML | [code](https://github.com/blei-lab/zero-inflated-embedding) | 20 | -| [InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations](http://papers.nips.cc/paper/6971-infogail-interpretable-imitation-learning-from-visual-demonstrations.pdf) | NIPS | [code](https://github.com/ermongroup/infogail) | 20 | -| [Weakly-Supervised Learning of Visual Relations](http://openaccess.thecvf.com/content_iccv_2017/html/Peyre_Weakly-Supervised_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jpeyre/unrel) | 20 | -| [Multi-Label Image Recognition by Recurrently Discovering Attentional Regions](http://openaccess.thecvf.com/content_iccv_2017/html/Wang_Multi-Label_Image_Recognition_ICCV_2017_paper.html) | ICCV | [code](https://github.com/James-Yip/AttentionImageClass) | 20 | -| [Scene Parsing With Global Context Embedding](http://openaccess.thecvf.com/content_iccv_2017/html/Hung_Scene_Parsing_With_ICCV_2017_paper.html) | ICCV | [code](https://github.com/hfslyc/GCPNet) | 20 | -| [Context Selection for Embedding Models](http://papers.nips.cc/paper/7067-context-selection-for-embedding-models.pdf) | NIPS | [code](https://github.com/blei-lab/context-selection-embedding) | 20 | -| [Deep Mean-Shift Priors for Image Restoration](http://papers.nips.cc/paper/6678-deep-mean-shift-priors-for-image-restoration.pdf) | NIPS | [code](https://github.com/siavashBigdeli/DMSP) | 20 | -| [Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Skeleton_Key_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/feiyu1990/Skeleton-key) | 20 | -| [Fully-Adaptive Feature Sharing in Multi-Task Networks With Applications in Person Attribute Classification](http://openaccess.thecvf.com/content_cvpr_2017/html/Lu_Fully-Adaptive_Feature_Sharing_CVPR_2017_paper.html) | CVPR | [code](https://github.com/luyongxi/deep_share) | 19 | -| [Learning Compact Geometric Features](http://openaccess.thecvf.com/content_iccv_2017/html/Khoury_Learning_Compact_Geometric_ICCV_2017_paper.html) | ICCV | [code](https://github.com/marckhoury/CGF) | 19 | -| [Structured Generative Adversarial Networks](http://papers.nips.cc/paper/6979-structured-generative-adversarial-networks.pdf) | NIPS | [code](https://github.com/thudzj/StructuredGAN) | 19 | -| [Joint Gap Detection and Inpainting of Line Drawings](http://openaccess.thecvf.com/content_cvpr_2017/html/Sasaki_Joint_Gap_Detection_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kaidlc/CVPR2017_linedrawings) | 19 | -| [Chained Multi-Stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Zolfaghari_Chained_Multi-Stream_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mzolfaghari/chained-multistream-networks) | 19 | -| [Adversarial Feature Matching for Text Generation](http://proceedings.mlr.press/v70/zhang17b.html) | ICML | [code](https://github.com/Jeff-HOU/UROP-Adversarial-Feature-Matching-for-Text-Generation) | 18 | -| [BIER - Boosting Independent Embeddings Robustly](http://openaccess.thecvf.com/content_iccv_2017/html/Opitz_BIER_-_Boosting_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mop/bier) | 18 | -| [Predictive-Corrective Networks for Action Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Dave_Predictive-Corrective_Networks_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/achalddave/predictive-corrective) | 18 | -| [Stochastic Generative Hashing](http://proceedings.mlr.press/v70/dai17a.html) | ICML | [code](https://github.com/doubling/Stochastic_Generative_Hashing) | 18 | -| [A Bayesian Data Augmentation Approach for Learning Deep Models](http://papers.nips.cc/paper/6872-a-bayesian-data-augmentation-approach-for-learning-deep-models.pdf) | NIPS | [code](https://github.com/toantm/keras-bda) | 18 | -| [Attentive Semantic Video Generation Using Captions](http://openaccess.thecvf.com/content_iccv_2017/html/Marwah_Attentive_Semantic_Video_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Singularity42/cap2vid) | 18 | -| [MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_MDNet_A_Semantically_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zizhaozhang/mdnet-cvpr2017) | 18 | -| [Deep Unsupervised Similarity Learning Using Partially Ordered Sets](http://openaccess.thecvf.com/content_cvpr_2017/html/Bautista_Deep_Unsupervised_Similarity_CVPR_2017_paper.html) | CVPR | [code](https://github.com/asanakoy/deep_unsupervised_posets) | 17 | -| [DualNet: Learn Complementary Features for Image Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Hou_DualNet_Learn_Complementary_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ustc-vim/dualnet) | 17 | -| [Neural system identification for large populations separating “what” and “where”](http://papers.nips.cc/paper/6942-neural-system-identification-for-large-populations-separating-what-and-where.pdf) | NIPS | [code](https://github.com/david-klindt/NIPS2017) | 17 | -| [FALKON: An Optimal Large Scale Kernel Method](http://papers.nips.cc/paper/6978-falkon-an-optimal-large-scale-kernel-method.pdf) | NIPS | [code](https://github.com/LCSL/FALKON_paper) | 17 | -| [Deep Future Gaze: Gaze Anticipation on Egocentric Videos Using Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Deep_Future_Gaze_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Mengmi/deepfuturegaze_gan) | 17 | -| [Deep Learning with Topological Signatures](http://papers.nips.cc/paper/6761-deep-learning-with-topological-signatures.pdf) | NIPS | [code](https://github.com/c-hofer/nips2017) | 17 | -| [Streaming Sparse Gaussian Process Approximations](http://papers.nips.cc/paper/6922-streaming-sparse-gaussian-process-approximations.pdf) | NIPS | [code](https://github.com/thangbui/streaming_sparse_gp) | 17 | -| [RPAN: An End-To-End Recurrent Pose-Attention Network for Action Recognition in Videos](http://openaccess.thecvf.com/content_iccv_2017/html/Du_RPAN_An_End-To-End_ICCV_2017_paper.html) | ICCV | [code](https://github.com/agethen/RPAN) | 17 | -| [Awesome Typography: Statistics-Based Text Effects Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Awesome_Typography_Statistics-Based_CVPR_2017_paper.html) | CVPR | [code](https://github.com/williamyang1991/Text-Effects-Transfer) | 17 | -| [RoomNet: End-To-End Room Layout Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Lee_RoomNet_End-To-End_Room_ICCV_2017_paper.html) | ICCV | [code](https://github.com/GitBoSun/roomnet) | 17 | -| [Deep Spatial-Semantic Attention for Fine-Grained Sketch-Based Image Retrieval](http://openaccess.thecvf.com/content_iccv_2017/html/Song_Deep_Spatial-Semantic_Attention_ICCV_2017_paper.html) | ICCV | [code](https://github.com/yuchuochuo1023/Deep_SBIR_tf) | 16 | -| [Deep Supervised Discrete Hashing](http://papers.nips.cc/paper/6842-deep-supervised-discrete-hashing.pdf) | NIPS | [code](https://github.com/liqi-casia/DSDH-HashingCode) | 16 | -| [Few-Shot Learning Through an Information Retrieval Lens](http://papers.nips.cc/paper/6820-few-shot-learning-through-an-information-retrieval-lens.pdf) | NIPS | [code](https://github.com/eleniTriantafillou/few_shot_mAP_public) | 16 | -| [Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach](http://papers.nips.cc/paper/7023-estimating-accuracy-from-unlabeled-data-a-probabilistic-logic-approach.pdf) | NIPS | [code](https://github.com/eaplatanios/makina) | 16 | -| [Learning to Push the Limits of Efficient FFT-Based Image Deconvolution](http://openaccess.thecvf.com/content_iccv_2017/html/Kruse_Learning_to_Push_ICCV_2017_paper.html) | ICCV | [code](https://github.com/uschmidt83/fourier-deconvolution-network) | 16 | -| [Federated Multi-Task Learning](http://papers.nips.cc/paper/7029-federated-multi-task-learning.pdf) | NIPS | [code](https://github.com/gingsmith/fmtl) | 16 | -| [Label Distribution Learning Forests](http://papers.nips.cc/paper/6685-label-distribution-learning-forests.pdf) | NIPS | [code](https://github.com/shenwei1231/caffe-LDLForests) | 16 | -| [Deep Multitask Architecture for Integrated 2D and 3D Human Sensing](http://openaccess.thecvf.com/content_cvpr_2017/html/Popa_Deep_Multitask_Architecture_CVPR_2017_paper.html) | CVPR | [code](https://github.com/alinionutpopa/dmhs) | 16 | -| [Estimating Mutual Information for Discrete-Continuous Mixtures](http://papers.nips.cc/paper/7180-estimating-mutual-information-for-discrete-continuous-mixtures.pdf) | NIPS | [code](https://github.com/wgao9/mixed_KSG) | 16 | -| [Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes](http://openaccess.thecvf.com/content_cvpr_2017/html/Golestaneh_Spatially-Varying_Blur_Detection_CVPR_2017_paper.html) | CVPR | [code](https://github.com/isalirezag/HiFST) | 16 | -| [StyleBank: An Explicit Representation for Neural Image Style Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_StyleBank_An_Explicit_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jxcodetw/Stylebank) | 16 | -| [Surface Normals in the Wild](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Surface_Normals_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/umich-vl/surface_normals) | 15 | -| [Automatic Discovery of the Statistical Types of Variables in a Dataset](http://proceedings.mlr.press/v70/valera17a.html) | ICML | [code](https://github.com/ivaleraM/DataTypes) | 15 | -| [Learning Diverse Image Colorization](http://openaccess.thecvf.com/content_cvpr_2017/html/Deshpande_Learning_Diverse_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/aditya12agd5/divcolor) | 15 | -| [Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems](http://openaccess.thecvf.com/content_iccv_2017/html/Meinhardt_Learning_Proximal_Operators_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tum-vision/learn_prox_ops) | 15 | -| [Non-Local Deep Features for Salient Object Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Luo_Non-Local_Deep_Features_CVPR_2017_paper.html) | CVPR | [code](https://github.com/AceCoooool/NLFD-pytorch) | 15 | -| [Structure-Measure: A New Way to Evaluate Foreground Maps](http://openaccess.thecvf.com/content_iccv_2017/html/Fan_Structure-Measure_A_New_ICCV_2017_paper.html) | ICCV | [code](https://github.com/DengPingFan/S-measure) | 15 | -| [Shallow Updates for Deep Reinforcement Learning](http://papers.nips.cc/paper/6906-shallow-updates-for-deep-reinforcement-learning.pdf) | NIPS | [code](https://github.com/Shallow-Updates-for-Deep-RL/Shallow_Updates_for_Deep_RL) | 15 | -| [Wasserstein Generative Adversarial Networks](http://proceedings.mlr.press/v70/arjovsky17a.html) | ICML | [code](https://github.com/luslab/scRNAseq-WGAN-GP) | 15 | -| [Recurrent 3D Pose Sequence Machines](http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Recurrent_3D_Pose_CVPR_2017_paper.html) | CVPR | [code](https://github.com/MudeLin/RPSM) | 15 | -| [Variational Dropout Sparsifies Deep Neural Networks](http://proceedings.mlr.press/v70/molchanov17a.html) | ICML | [code](https://github.com/soskek/variational_dropout_sparsifies_dnn) | 15 | -| [Captioning Images With Diverse Objects](http://openaccess.thecvf.com/content_cvpr_2017/html/Venugopalan_Captioning_Images_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/vsubhashini/noc) | 15 | -| [Off-policy evaluation for slate recommendation](http://papers.nips.cc/paper/6954-off-policy-evaluation-for-slate-recommendation.pdf) | NIPS | [code](https://github.com/adith387/slates_semisynth_expts) | 15 | -| [Attributes2Classname: A Discriminative Model for Attribute-Based Unsupervised Zero-Shot Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Demirel_Attributes2Classname_A_Discriminative_ICCV_2017_paper.html) | ICCV | [code](https://github.com/berkandemirel/attributes2classname) | 14 | -| [Benchmarking Denoising Algorithms With Real Photographs](http://openaccess.thecvf.com/content_cvpr_2017/html/Plotz_Benchmarking_Denoising_Algorithms_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lbasek/image-denoising-benchmark) | 14 | -| [Neural Aggregation Network for Video Face Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Neural_Aggregation_Network_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jinyanxu/Neural-Aggregation-Network-for-Video-Face-Recognition) | 14 | -| [Learned Contextual Feature Reweighting for Image Geo-Localization](http://openaccess.thecvf.com/content_cvpr_2017/html/Kim_Learned_Contextual_Feature_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hyojinie/crn) | 14 | -| [Streaming Weak Submodularity: Interpreting Neural Networks on the Fly](http://papers.nips.cc/paper/6993-streaming-weak-submodularity-interpreting-neural-networks-on-the-fly.pdf) | NIPS | [code](https://github.com/eelenberg/streak) | 14 | -| [CVAE-GAN: Fine-Grained Image Generation Through Asymmetric Training](http://openaccess.thecvf.com/content_iccv_2017/html/Bao_CVAE-GAN_Fine-Grained_Image_ICCV_2017_paper.html) | ICCV | [code](https://github.com/yanzhicong/VAE-GAN) | 14 | -| [VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation](http://openaccess.thecvf.com/content_iccv_2017/html/Gan_VQS_Linking_Segmentations_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Cold-Winter/vqs) | 14 | -| [Spherical convolutions and their application in molecular modelling](http://papers.nips.cc/paper/6935-spherical-convolutions-and-their-application-in-molecular-modelling.pdf) | NIPS | [code](https://github.com/deepfold/NIPS2017) | 14 | -| [Multi-Information Source Optimization](http://papers.nips.cc/paper/7016-multi-information-source-optimization.pdf) | NIPS | [code](https://github.com/deepfold/NIPS2017) | 14 | -| [Convolutional Neural Network Architecture for Geometric Matching](http://openaccess.thecvf.com/content_cvpr_2017/html/Rocco_Convolutional_Neural_Network_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hjweide/convnet-for-geometric-matching) | 14 | -| [Neural Face Editing With Intrinsic Image Disentangling](http://openaccess.thecvf.com/content_cvpr_2017/html/Shu_Neural_Face_Editing_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zhixinshu/NeuralFaceEditing) | 14 | -| [Realistic Dynamic Facial Textures From a Single Image Using GANs](http://openaccess.thecvf.com/content_iccv_2017/html/Olszewski_Realistic_Dynamic_Facial_ICCV_2017_paper.html) | ICCV | [code](https://github.com/leehomyc/ICCV-2017-Paper) | 14 | -| [Predictive State Recurrent Neural Networks](http://papers.nips.cc/paper/7186-predictive-state-recurrent-neural-networks.pdf) | NIPS | [code](https://github.com/cmdowney/psrnn) | 13 | -| [Deep TextSpotter: An End-To-End Trainable Scene Text Localization and Recognition Framework](http://openaccess.thecvf.com/content_iccv_2017/html/Busta_Deep_TextSpotter_An_ICCV_2017_paper.html) | ICCV | [code](https://github.com/VeitL/OCR) | 13 | -| [ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events](http://papers.nips.cc/paper/6932-extremeweather-a-large-scale-climate-dataset-for-semi-supervised-detection-localization-and-understanding-of-extreme-weather-events.pdf) | NIPS | [code](https://github.com/eracah/hur-detect) | 13 | -| [Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs](http://papers.nips.cc/paper/6614-hunt-for-the-unique-stable-sparse-and-fast-feature-learning-on-graphs.pdf) | NIPS | [code](https://github.com/vermaMachineLearning/FGSD) | 13 | -| [Consensus Convolutional Sparse Coding](http://openaccess.thecvf.com/content_iccv_2017/html/Choudhury_Consensus_Convolutional_Sparse_ICCV_2017_paper.html) | ICCV | [code](https://github.com/vccimaging/CCSC_code_ICCV2017) | 13 | -| [Weakly Supervised Affordance Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Sawatzky_Weakly_Supervised_Affordance_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ykztawas/Weakly-Supervised-Affordance-Detection) | 13 | -| [Joint Learning of Object and Action Detectors](http://openaccess.thecvf.com/content_iccv_2017/html/Kalogeiton_Joint_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/vkalogeiton/joint-object-action-learning) | 13 | -| [Light Field Blind Motion Deblurring](http://openaccess.thecvf.com/content_cvpr_2017/html/Srinivasan_Light_Field_Blind_CVPR_2017_paper.html) | CVPR | [code](https://github.com/pratulsrinivasan/Light_Field_Blind_Motion_Deblurring) | 13 | -| [Asynchronous Stochastic Gradient Descent with Delay Compensation](http://proceedings.mlr.press/v70/zheng17b.html) | ICML | [code](https://github.com/Microsoft/Delayed-Compensation-Asynchronous-Stochastic-Gradient-Descent-for-Multiverso) | 13 | -| [Unrolled Memory Inner-Products: An Abstract GPU Operator for Efficient Vision-Related Computations](http://openaccess.thecvf.com/content_iccv_2017/html/Lin_Unrolled_Memory_Inner-Products_ICCV_2017_paper.html) | ICCV | [code](https://github.com/johnjohnlin/UMI) | 12 | -| [Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification](http://papers.nips.cc/paper/7125-maximizing-subset-accuracy-with-recurrent-neural-networks-in-multi-label-classification.pdf) | NIPS | [code](https://github.com/JinseokNam/mlc2seq) | 12 | -| [Self-Organized Text Detection With Minimal Post-Processing via Border Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Wu_Self-Organized_Text_Detection_ICCV_2017_paper.html) | ICCV | [code](https://github.com/saicoco/tf-sotd) | 12 | -| [Coordinated Multi-Agent Imitation Learning](http://proceedings.mlr.press/v70/le17a.html) | ICML | [code](https://github.com/hoangminhle/MultiAgent-ImitationLearning) | 12 | -| [Gradient descent GAN optimization is locally stable](http://papers.nips.cc/paper/7142-gradient-descent-gan-optimization-is-locally-stable.pdf) | NIPS | [code](https://github.com/locuslab/gradient_regularized_gan) | 12 | -| [Removing Rain From Single Images via a Deep Detail Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Fu_Removing_Rain_From_CVPR_2017_paper.html) | CVPR | [code](https://github.com/XMU-smartdsp/Removing_Rain) | 12 | -| [Convexified Convolutional Neural Networks](http://proceedings.mlr.press/v70/zhang17f.html) | ICML | [code](https://github.com/zhangyuc/CCNN) | 12 | -| [Multigrid Neural Architectures](http://openaccess.thecvf.com/content_cvpr_2017/html/Ke_Multigrid_Neural_Architectures_CVPR_2017_paper.html) | CVPR | [code](https://github.com/buttomnutstoast/Multigrid-Neural-Architectures) | 12 | -| [VegFru: A Domain-Specific Dataset for Fine-Grained Visual Categorization](http://openaccess.thecvf.com/content_iccv_2017/html/Hou_VegFru_A_Domain-Specific_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ustc-vim/vegfru) | 12 | -| [Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin](http://papers.nips.cc/paper/7255-attend-and-predict-understanding-gene-regulation-by-selective-attention-on-chromatin.pdf) | NIPS | [code](https://github.com/QData/AttentiveChrome) | 12 | -| [Differential Angular Imaging for Material Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Xue_Differential_Angular_Imaging_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jiaxue1993/DAIN) | 12 | -| [A Multilayer-Based Framework for Online Background Subtraction With Freely Moving Cameras](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_A_Multilayer-Based_Framework_ICCV_2017_paper.html) | ICCV | [code](https://github.com/EthanZhu90/MultilayerBSMC_ICCV17) | 11 | -| [Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation](http://papers.nips.cc/paper/6821-formal-guarantees-on-the-robustness-of-a-classifier-against-adversarial-manipulation.pdf) | NIPS | [code](https://github.com/max-andr/cross-lipschitz) | 11 | -| [Max-value Entropy Search for Efficient Bayesian Optimization](http://proceedings.mlr.press/v70/wang17e.html) | ICML | [code](https://github.com/zi-w/Max-value-Entropy-Search) | 11 | -| [Higher-Order Integration of Hierarchical Convolutional Activations for Fine-Grained Visual Categorization](http://openaccess.thecvf.com/content_iccv_2017/html/Cai_Higher-Order_Integration_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cssjcai/hihca) | 11 | -| [Generalized Deep Image to Image Regression](http://openaccess.thecvf.com/content_cvpr_2017/html/Santhanam_Generalized_Deep_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/venkai/RBDN) | 11 | -| [Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective](http://openaccess.thecvf.com/content_iccv_2017/html/Oh_Adversarial_Image_Perturbation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/coallaoh/AIP) | 11 | -| [Predicting Human Activities Using Stochastic Grammar](http://openaccess.thecvf.com/content_iccv_2017/html/Qi_Predicting_Human_Activities_ICCV_2017_paper.html) | ICCV | [code](https://github.com/SiyuanQi/grammar-activity-prediction) | 11 | -| [DESIRE: Distant Future Prediction in Dynamic Scenes With Interacting Agents](http://openaccess.thecvf.com/content_cvpr_2017/html/Lee_DESIRE_Distant_Future_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yadrimz/DESIRE) | 11 | -| [Fisher GAN](http://papers.nips.cc/paper/6845-fisher-gan.pdf) | NIPS | [code](https://github.com/tomsercu/FisherGAN) | 11 | -| [High-Order Attention Models for Visual Question Answering](http://papers.nips.cc/paper/6957-high-order-attention-models-for-visual-question-answering.pdf) | NIPS | [code](https://github.com/idansc/HighOrderAtten) | 11 | -| [IM2CAD](http://openaccess.thecvf.com/content_cvpr_2017/html/Izadinia_IM2CAD_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yyong119/IM2CAD) | 11 | -| [On Fairness and Calibration](http://papers.nips.cc/paper/7151-on-fairness-and-calibration.pdf) | NIPS | [code](https://github.com/gpleiss/equalized_odds_and_calibration) | 11 | -| [DeepPermNet: Visual Permutation Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Santa_Cruz_DeepPermNet_Visual_Permutation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/rfsantacruz/deep-perm-net) | 10 | -| [f-GANs in an Information Geometric Nutshell](http://papers.nips.cc/paper/6649-f-gans-in-an-information-geometric-nutshell.pdf) | NIPS | [code](https://github.com/qulizhen/fgan_info_geometric) | 10 | -| [Revisiting IM2GPS in the Deep Learning Era](http://openaccess.thecvf.com/content_iccv_2017/html/Vo_Revisiting_IM2GPS_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/lugiavn/revisiting-im2gps) | 10 | -| [Attentional Correlation Filter Network for Adaptive Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2017/html/Choi_Attentional_Correlation_Filter_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jongwon20000/ACFN) | 10 | -| [Learning Cross-Modal Deep Representations for Robust Pedestrian Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Learning_Cross-Modal_Deep_CVPR_2017_paper.html) | CVPR | [code](https://github.com/danxuhk/CMT-CNN) | 10 | -| [Confident Multiple Choice Learning](http://proceedings.mlr.press/v70/lee17b.html) | ICML | [code](https://github.com/chhwang/cmcl) | 10 | -| [Curriculum Dropout](http://openaccess.thecvf.com/content_iccv_2017/html/Morerio_Curriculum_Dropout_ICCV_2017_paper.html) | ICCV | [code](https://github.com/pmorerio/curriculum-dropout) | 9 | -| [Cognitive Mapping and Planning for Visual Navigation](http://openaccess.thecvf.com/content_cvpr_2017/html/Gupta_Cognitive_Mapping_and_CVPR_2017_paper.html) | CVPR | [code](https://github.com/agiantwhale/cognitive-mapping-agent) | 9 | -| [Optimized Pre-Processing for Discrimination Prevention](http://papers.nips.cc/paper/6988-optimized-pre-processing-for-discrimination-prevention.pdf) | NIPS | [code](https://github.com/fair-preprocessing/nips2017) | 9 | -| [Learning Motion Patterns in Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Tokmakov_Learning_Motion_Patterns_CVPR_2017_paper.html) | CVPR | [code](https://github.com/pirahansiah/opencv) | 9 | -| [Scalable Log Determinants for Gaussian Process Kernel Learning](http://papers.nips.cc/paper/7212-scalable-log-determinants-for-gaussian-process-kernel-learning.pdf) | NIPS | [code](https://github.com/kd383/GPML_SLD) | 9 | -| [A Hierarchical Approach for Generating Descriptive Image Paragraphs](http://openaccess.thecvf.com/content_cvpr_2017/html/Krause_A_Hierarchical_Approach_CVPR_2017_paper.html) | CVPR | [code](https://github.com/InnerPeace-Wu/im2p-tensorflow) | 9 | -| [Deep Crisp Boundaries](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Deep_Crisp_Boundaries_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Wangyupei/CED) | 9 | -| [Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization](http://papers.nips.cc/paper/6611-breaking-the-nonsmooth-barrier-a-scalable-parallel-method-for-composite-optimization.pdf) | NIPS | [code](https://github.com/fabianp/ProxASAGA) | 9 | -| [Practical Data-Dependent Metric Compression with Provable Guarantees](http://papers.nips.cc/paper/6855-practical-data-dependent-metric-compression-with-provable-guarantees.pdf) | NIPS | [code](https://github.com/talwagner/quadsketch) | 9 | -| [Do Deep Neural Networks Suffer from Crowding?](http://papers.nips.cc/paper/7146-do-deep-neural-networks-suffer-from-crowding.pdf) | NIPS | [code](https://github.com/CBMM/eccentricity) | 9 | -| [A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting](http://openaccess.thecvf.com/content_cvpr_2017/html/Queau_A_Non-Convex_Variational_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yqueau/robust_ps) | 9 | -| [End-To-End Learning of Geometry and Context for Deep Stereo Regression](http://openaccess.thecvf.com/content_iccv_2017/html/Kendall_End-To-End_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/liuruijin17/RickLiuGC) | 9 | -| [From Bayesian Sparsity to Gated Recurrent Nets](http://papers.nips.cc/paper/7139-from-bayesian-sparsity-to-gated-recurrent-nets.pdf) | NIPS | [code](https://github.com/hehaodele/SBL-LSTM-Net) | 8 | -| [Regret Minimization in MDPs with Options without Prior Knowledge](http://papers.nips.cc/paper/6909-regret-minimization-in-mdps-with-options-without-prior-knowledge.pdf) | NIPS | [code](https://github.com/RonanFR/UCRL) | 8 | -| [Following Gaze in Video](http://openaccess.thecvf.com/content_iccv_2017/html/Recasens_Following_Gaze_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/recasens/Gaze-Following) | 8 | -| [Model-Powered Conditional Independence Test](http://papers.nips.cc/paper/6888-model-powered-conditional-independence-test.pdf) | NIPS | [code](https://github.com/rajatsen91/CCIT) | 8 | -| [Cost efficient gradient boosting](http://papers.nips.cc/paper/6753-cost-efficient-gradient-boosting.pdf) | NIPS | [code](https://github.com/svenpeter42/LightGBM-CEGB) | 8 | -| [Reflectance Adaptive Filtering Improves Intrinsic Image Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Nestmeyer_Reflectance_Adaptive_Filtering_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tnestmeyer/reflectance-filtering) | 8 | -| [DeepNav: Learning to Navigate Large Cities](http://openaccess.thecvf.com/content_cvpr_2017/html/Brahmbhatt_DeepNav_Learning_to_CVPR_2017_paper.html) | CVPR | [code](https://github.com/samarth-robo/deepnav_cvpr17) | 8 | -| [Look, Listen and Learn](http://openaccess.thecvf.com/content_iccv_2017/html/Arandjelovic_Look_Listen_and_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Kajiyu/LLLNet) | 8 | -| [Attention-Aware Face Hallucination via Deep Reinforcement Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Attention-Aware_Face_Hallucination_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ykshi/facehallucination) | 8 | -| [Plan, Attend, Generate: Planning for Sequence-to-Sequence Models](http://papers.nips.cc/paper/7131-plan-attend-generate-planning-for-sequence-to-sequence-models.pdf) | NIPS | [code](https://github.com/Dutil/PAG) | 8 | -| [Introspective Neural Networks for Generative Modeling](http://openaccess.thecvf.com/content_iccv_2017/html/Lazarow_Introspective_Neural_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/intermilan/inng) | 8 | -| [Affinity Clustering: Hierarchical Clustering at Scale](http://papers.nips.cc/paper/7262-affinity-clustering-hierarchical-clustering-at-scale.pdf) | NIPS | [code](https://github.com/MahsaDerakhshan/AffinityClustering) | 8 | -| [Gaze Embeddings for Zero-Shot Image Classification](http://openaccess.thecvf.com/content_cvpr_2017/html/Karessli_Gaze_Embeddings_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Noura-kr/CVPR17) | 8 | -| [Input Switched Affine Networks: An RNN Architecture Designed for Interpretability](http://proceedings.mlr.press/v70/foerster17a.html) | ICML | [code](https://github.com/philipperemy/tensorflow-isan-rnn) | 8 | -| [Online multiclass boosting](http://papers.nips.cc/paper/6693-online-multiclass-boosting.pdf) | NIPS | [code](https://github.com/yhjung88/OnlineBoostingWithVFDT) | 8 | -| [Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images](http://openaccess.thecvf.com/content_iccv_2017/html/Orekondy_Towards_a_Visual_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tribhuvanesh/vpa) | 8 | -| [SubUNets: End-To-End Hand Shape and Continuous Sign Language Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Camgoz_SubUNets_End-To-End_Hand_ICCV_2017_paper.html) | ICCV | [code](https://github.com/neccam/SubUNets) | 7 | -| [Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition](http://papers.nips.cc/paper/6713-learning-koopman-invariant-subspaces-for-dynamic-mode-decomposition.pdf) | NIPS | [code](https://github.com/thetak11/learning-kis) | 7 | -| [Unsupervised Monocular Depth Estimation With Left-Right Consistency](http://openaccess.thecvf.com/content_cvpr_2017/html/Godard_Unsupervised_Monocular_Depth_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yukitsuji/monodepth_chainer) | 7 | -| [Personalized Image Aesthetics](http://openaccess.thecvf.com/content_iccv_2017/html/Ren_Personalized_Image_Aesthetics_ICCV_2017_paper.html) | ICCV | [code](https://github.com/alanspike/personalizedImageAesthetics) | 7 | -| [Reasoning About Fine-Grained Attribute Phrases Using Reference Games](http://openaccess.thecvf.com/content_iccv_2017/html/Su_Reasoning_About_Fine-Grained_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jongchyisu/attribute_phrases) | 7 | -| [Lost Relatives of the Gumbel Trick](http://proceedings.mlr.press/v70/balog17a.html) | ICML | [code](https://github.com/matejbalog/gumbel-relatives) | 7 | -| [Weakly Supervised Learning of Deep Metrics for Stereo Reconstruction](http://openaccess.thecvf.com/content_iccv_2017/html/Tulyakov_Weakly_Supervised_Learning_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tlkvstepan/mc-cnn-ws) | 7 | -| [Centered Weight Normalization in Accelerating Training of Deep Neural Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Centered_Weight_Normalization_ICCV_2017_paper.html) | ICCV | [code](https://github.com/huangleiBuaa/CenteredWN) | 6 | -| [Scalable Planning with Tensorflow for Hybrid Nonlinear Domains](http://papers.nips.cc/paper/7207-scalable-planning-with-tensorflow-for-hybrid-nonlinear-domains.pdf) | NIPS | [code](https://github.com/wuga214/TOOLBOX-Learning-and-Planning-through-Backpropagation) | 6 | -| [Convex Global 3D Registration With Lagrangian Duality](http://openaccess.thecvf.com/content_cvpr_2017/html/Briales_Convex_Global_3D_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jbriales/CVPR17) | 6 | -| [Building a Regular Decision Boundary With Deep Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Oyallon_Building_a_Regular_CVPR_2017_paper.html) | CVPR | [code](https://github.com/edouardoyallon/deep_separation_contraction) | 6 | -| [Learning Spatial Regularization With Image-Level Supervisions for Multi-Label Image Classification](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Learning_Spatial_Regularization_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Enjia/Spatial-Regularization-Network-in-Tensorflow) | 6 | -| [Forecasting Human Dynamics From Static Images](http://openaccess.thecvf.com/content_cvpr_2017/html/Chao_Forecasting_Human_Dynamics_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ywchao/skeleton2d3d) | 6 | -| [AOD-Net: All-In-One Dehazing Network](http://openaccess.thecvf.com/content_iccv_2017/html/Li_AOD-Net_All-In-One_Dehazing_ICCV_2017_paper.html) | ICCV | [code](https://github.com/weber0522bb/AODnet-by-pytorch) | 6 | -| [K-Medoids For K-Means Seeding](http://papers.nips.cc/paper/7104-k-medoids-for-k-means-seeding.pdf) | NIPS | [code](https://github.com/idiap/zentas) | 6 | -| [Diverse Image Annotation](http://openaccess.thecvf.com/content_cvpr_2017/html/Wu_Diverse_Image_Annotation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/wubaoyuan/DIA) | 6 | -| [Practical Hash Functions for Similarity Estimation and Dimensionality Reduction](http://papers.nips.cc/paper/7239-practical-hash-functions-for-similarity-estimation-and-dimensionality-reduction.pdf) | NIPS | [code](https://github.com/zera/Nips_MT) | 6 | -| [Deep Adaptive Image Clustering](http://openaccess.thecvf.com/content_iccv_2017/html/Chang_Deep_Adaptive_Image_ICCV_2017_paper.html) | ICCV | [code](https://github.com/HongtaoYang/DAC-tensorflow) | 6 | -| [Robust Adversarial Reinforcement Learning](http://proceedings.mlr.press/v70/pinto17a.html) | ICML | [code](https://github.com/Jekyll1021/RARL) | 6 | -| [Improving Training of Deep Neural Networks via Singular Value Bounding](http://openaccess.thecvf.com/content_cvpr_2017/html/Jia_Improving_Training_of_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kui-jia/svb) | 6 | -| [Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems](http://papers.nips.cc/paper/6838-analyzing-hidden-representations-in-end-to-end-automatic-speech-recognition-systems.pdf) | NIPS | [code](https://github.com/boknilev/asr-repr-analysis) | 6 | -| [Tensor Belief Propagation](http://proceedings.mlr.press/v70/wrigley17a.html) | ICML | [code](https://github.com/akxlr/tbp) | 6 | -| [Sparse convolutional coding for neuronal assembly detection](http://papers.nips.cc/paper/6958-sparse-convolutional-coding-for-neuronal-assembly-detection.pdf) | NIPS | [code](https://github.com/sccfnad/Sparse-convolutional-coding-for-neuronal-assembly-detection) | 6 | -| [Unsupervised Pixel-Level Domain Adaptation With Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Bousmalis_Unsupervised_Pixel-Level_Domain_CVPR_2017_paper.html) | CVPR | [code](https://github.com/rhythm92/Unsupervised-Pixel-Level-Domain-Adaptation-with-GAN) | 6 | -| [Bayesian inference on random simple graphs with power law degree distributions](http://proceedings.mlr.press/v70/lee17a.html) | ICML | [code](https://github.com/juho-lee/powerlawgraph) | 6 | -| [Tensor Biclustering](http://papers.nips.cc/paper/6730-tensor-biclustering.pdf) | NIPS | [code](https://github.com/SoheilFeizi/Tensor-Biclustering) | 6 | -| [Riemannian approach to batch normalization](http://papers.nips.cc/paper/7107-riemannian-approach-to-batch-normalization.pdf) | NIPS | [code](https://github.com/MinhyungCho/riemannian-batch-normalization) | 6 | -| [Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings](http://openaccess.thecvf.com/content_iccv_2017/html/Thewlis_Unsupervised_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/alldbi/Factorized-Spatial-Embeddings) | 6 | -| [Rolling-Shutter-Aware Differential SfM and Image Rectification](http://openaccess.thecvf.com/content_iccv_2017/html/Zhuang_Rolling-Shutter-Aware_Differential_SfM_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ThomasZiegler/RS-aware-differential-SfM) | 5 | -| [Active Decision Boundary Annotation With Deep Generative Models](http://openaccess.thecvf.com/content_iccv_2017/html/Huijser_Active_Decision_Boundary_ICCV_2017_paper.html) | ICCV | [code](https://github.com/MiriamHu/ActiveBoundary) | 5 | -| [Object Co-Skeletonization With Co-Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Jerripothula_Object_Co-Skeletonization_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jkoteswarrao/Object-Co-skeletonization-with-Co-segmentation) | 5 | -| [Discover and Learn New Objects From Documentaries](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Discover_and_Learn_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hellock/documentary-learning) | 5 | -| [Understanding Black-box Predictions via Influence Functions](http://proceedings.mlr.press/v70/koh17a.html) | ICML | [code](https://github.com/eolecvk/InfluenceFunctions) | 5 | -| [Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach](http://openaccess.thecvf.com/content_cvpr_2017/html/Patrini_Making_Deep_Neural_CVPR_2017_paper.html) | CVPR | [code](https://github.com/GarrettLee/label_noise_correction) | 5 | -| [Decoupling "when to update" from "how to update"](http://papers.nips.cc/paper/6697-decoupling-when-to-update-from-how-to-update.pdf) | NIPS | [code](https://github.com/emalach/UpdateByDisagreement) | 5 | -| [MarioQA: Answering Questions by Watching Gameplay Videos](http://openaccess.thecvf.com/content_iccv_2017/html/Mun_MarioQA_Answering_Questions_ICCV_2017_paper.html) | ICCV | [code](https://github.com/JonghwanMun/MarioQA) | 5 | -| [Differentially private Bayesian learning on distributed data](http://papers.nips.cc/paper/6915-differentially-private-bayesian-learning-on-distributed-data.pdf) | NIPS | [code](https://github.com/DPBayes/dca-nips2017) | 5 | -| [Grad-CAM: Visual Explanations From Deep Networks via Gradient-Based Localization](http://openaccess.thecvf.com/content_iccv_2017/html/Selvaraju_Grad-CAM_Visual_Explanations_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cydonia999/Grad-CAM-in-TensorFlow) | 5 | -| [Question Asking as Program Generation](http://papers.nips.cc/paper/6705-question-asking-as-program-generation.pdf) | NIPS | [code](https://github.com/anselmrothe/question_dataset) | 5 | -| [Conic Scan-and-Cover algorithms for nonparametric topic modeling](http://papers.nips.cc/paper/6977-conic-scan-and-cover-algorithms-for-nonparametric-topic-modeling.pdf) | NIPS | [code](https://github.com/moonfolk/Geometric-Topic-Modeling) | 5 | -| [Lip Reading Sentences in the Wild](http://openaccess.thecvf.com/content_cvpr_2017/html/Chung_Lip_Reading_Sentences_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lsrock1/WLSNet_pytorch) | 5 | -| [ROAM: A Rich Object Appearance Model With Application to Rotoscoping](http://openaccess.thecvf.com/content_cvpr_2017/html/Miksik_ROAM_A_Rich_CVPR_2017_paper.html) | CVPR | [code](https://github.com/omiksik/roam) | 5 | -| [NeuralFDR: Learning Discovery Thresholds from Hypothesis Features](http://papers.nips.cc/paper/6752-neuralfdr-learning-discovery-thresholds-from-hypothesis-features.pdf) | NIPS | [code](https://github.com/fxia22/NeuralFDR) | 5 | -| [Viraliency: Pooling Local Virality](http://openaccess.thecvf.com/content_cvpr_2017/html/Alameda-Pineda_Viraliency_Pooling_Local_CVPR_2017_paper.html) | CVPR | [code](https://github.com/xavirema/lena_pooling) | 5 | -| [Learning Algorithms for Active Learning](http://proceedings.mlr.press/v70/bachman17a.html) | ICML | [code](https://github.com/vtphan/Code4Brownies) | 5 | -| [Point to Set Similarity Based Deep Feature Learning for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Point_to_Set_CVPR_2017_paper.html) | CVPR | [code](https://github.com/samaonline/Point-to-Set-Similarity-Based-Deep-Feature-Learning-for-Person-Re-identification) | 5 | -| [Click Here: Human-Localized Keypoints as Guidance for Viewpoint Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Szeto_Click_Here_Human-Localized_ICCV_2017_paper.html) | ICCV | [code](https://github.com/rszeto/click-here-cnn) | 5 | -| [The World of Fast Moving Objects](http://openaccess.thecvf.com/content_cvpr_2017/html/Rozumnyi_The_World_of_CVPR_2017_paper.html) | CVPR | [code](https://github.com/qixuanHou/Mapping-My-Break) | 5 | -| [Cross-Modality Binary Code Learning via Fusion Similarity Hashing](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Cross-Modality_Binary_Code_CVPR_2017_paper.html) | CVPR | [code](https://github.com/LynnHongLiu/FSH) | 5 | -| [Testing and Learning on Distributions with Symmetric Noise Invariance](http://papers.nips.cc/paper/6733-testing-and-learning-on-distributions-with-symmetric-noise-invariance.pdf) | NIPS | [code](https://github.com/hcllaw/phase_learn) | 5 | -| [Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference](http://papers.nips.cc/paper/7268-sticking-the-landing-simple-lower-variance-gradient-estimators-for-variational-inference.pdf) | NIPS | [code](https://github.com/geoffroeder/iwae) | 5 | -| [Diving into the shallows: a computational perspective on large-scale shallow learning](http://papers.nips.cc/paper/6968-diving-into-the-shallows-a-computational-perspective-on-large-scale-shallow-learning.pdf) | NIPS | [code](https://github.com/EigenPro/EigenPro-tensorflow) | 5 | -| [Rotation Equivariant Vector Field Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Marcos_Rotation_Equivariant_Vector_ICCV_2017_paper.html) | ICCV | [code](https://github.com/dmarcosg/RotEqNet) | 5 | -| [Recursive Sampling for the Nystrom Method](http://papers.nips.cc/paper/6973-recursive-sampling-for-the-nystrom-method.pdf) | NIPS | [code](https://github.com/cnmusco/recursive-nystrom) | 5 | -| [Learning From Video and Text via Large-Scale Discriminative Clustering](http://openaccess.thecvf.com/content_iccv_2017/html/Miech_Learning_From_Video_ICCV_2017_paper.html) | ICCV | [code](https://github.com/antoine77340/iccv17learning) | 5 | -| [Global optimization of Lipschitz functions](http://proceedings.mlr.press/v70/malherbe17a.html) | ICML | [code](https://github.com/Sycor4x/lipo) | 5 | -| [Device Placement Optimization with Reinforcement Learning](http://proceedings.mlr.press/v70/mirhoseini17a.html) | ICML | [code](https://github.com/indrajeet95/Device-Placement-Optimization-with-Reinforcement-Learning) | 4 | -| [Alternating Direction Graph Matching](http://openaccess.thecvf.com/content_cvpr_2017/html/Le-Huu_Alternating_Direction_Graph_CVPR_2017_paper.html) | CVPR | [code](https://github.com/netw0rkf10w/adgm) | 4 | -| [MEC: Memory-efficient Convolution for Deep Neural Network](http://proceedings.mlr.press/v70/cho17a.html) | ICML | [code](https://github.com/CSshengxy/MEC) | 4 | -| [Expert Gate: Lifelong Learning With a Network of Experts](http://openaccess.thecvf.com/content_cvpr_2017/html/Aljundi_Expert_Gate_Lifelong_CVPR_2017_paper.html) | CVPR | [code](https://github.com/rahafaljundi/Expert-Gate) | 4 | -| [A Simple yet Effective Baseline for 3D Human Pose Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Martinez_A_Simple_yet_ICCV_2017_paper.html) | ICCV | [code](https://github.com/nulledge/bilinear) | 4 | -| [On Structured Prediction Theory with Calibrated Convex Surrogate Losses](http://papers.nips.cc/paper/6634-on-structured-prediction-theory-with-calibrated-convex-surrogate-losses.pdf) | NIPS | [code](https://github.com/aosokin/consistentSurrogates_derivations) | 4 | -| [Sub-sampled Cubic Regularization for Non-convex Optimization](http://proceedings.mlr.press/v70/kohler17a.html) | ICML | [code](https://github.com/dalab/subsampled_cubic_regularization) | 4 | -| [Generalized Semantic Preserving Hashing for N-Label Cross-Modal Retrieval](http://openaccess.thecvf.com/content_cvpr_2017/html/Mandal_Generalized_Semantic_Preserving_CVPR_2017_paper.html) | CVPR | [code](https://github.com/devraj89/Generalized-Semantic-Preserving-Hashing-for-N-Label-Cross-Modal-Retrieval) | 4 | -| [Bottleneck Conditional Density Estimation](http://proceedings.mlr.press/v70/shu17a.html) | ICML | [code](https://github.com/RuiShu/bcde) | 4 | -| [Learning Cooperative Visual Dialog Agents With Deep Reinforcement Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Das_Learning_Cooperative_Visual_ICCV_2017_paper.html) | ICCV | [code](https://github.com/schopra8/Cooperative_Vis_Diag_RL) | 4 | -| [Multi-way Interacting Regression via Factorization Machines](http://papers.nips.cc/paper/6853-multi-way-interacting-regression-via-factorization-machines.pdf) | NIPS | [code](https://github.com/moonfolk/MiFM) | 4 | -| [Joint Discovery of Object States and Manipulation Actions](http://openaccess.thecvf.com/content_iccv_2017/html/Alayrac_Joint_Discovery_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jalayrac/object-states-action) | 4 | -| [Predicting Salient Face in Multiple-Face Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Predicting_Salient_Face_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tonysy/salient-face-in-MUVFET) | 4 | -| [From Red Wine to Red Tomato: Composition With Context](http://openaccess.thecvf.com/content_cvpr_2017/html/Misra_From_Red_Wine_CVPR_2017_paper.html) | CVPR | [code](https://github.com/imisra/composing_cvpr17) | 4 | -| [Encoder Based Lifelong Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Rannen_Encoder_Based_Lifelong_ICCV_2017_paper.html) | ICCV | [code](https://github.com/rahafaljundi/Encoder-Based-Lifelong-learning) | 4 | -| [Deep Recurrent Neural Network-Based Identification of Precursor microRNAs](http://papers.nips.cc/paper/6882-deep-recurrent-neural-network-based-identification-of-precursor-micrornas.pdf) | NIPS | [code](https://github.com/eleventh83/deepMiRGene) | 4 | -| [Guarantees for Greedy Maximization of Non-submodular Functions with Applications](http://proceedings.mlr.press/v70/bian17a.html) | ICML | [code](https://github.com/bianan/non-submodular-max) | 4 | -| [Pose-Aware Person Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Kumar_Pose-Aware_Person_Recognition_CVPR_2017_paper.html) | CVPR | [code](https://github.com/vijaykumar01/person_recognition) | 4 | -| [Zero-Shot Recognition Using Dual Visual-Semantic Mapping Paths](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Zero-Shot_Recognition_Using_CVPR_2017_paper.html) | CVPR | [code](https://github.com/YanaLee/Zero-Shot-Recognition-using-Dual-Visual-Semantic-Mapping-Paths) | 4 | -| [Asynchronous Distributed Variational Gaussian Processes for Regression](nan) | ICML | [code](https://github.com/hao-peng/ADVGP) | 3 | -| [Saliency Pattern Detection by Ranking Structured Trees](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Saliency_Pattern_Detection_ICCV_2017_paper.html) | ICCV | [code](https://github.com/zhulei2016/RST-saliency) | 3 | -| [Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System](http://papers.nips.cc/paper/6849-toward-goal-driven-neural-network-models-for-the-rodent-whisker-trigeminal-system.pdf) | NIPS | [code](https://github.com/neuroailab/whisker_model) | 3 | -| [Learning Non-Maximum Suppression](http://openaccess.thecvf.com/content_cvpr_2017/html/Hosang_Learning_Non-Maximum_Suppression_CVPR_2017_paper.html) | CVPR | [code](https://github.com/XingchenYu/pedestrian_detection_iosapp) | 3 | -| [Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC](http://proceedings.mlr.press/v70/cong17a.html) | ICML | [code](https://github.com/mingyuanzhou/DeepLDA_TLASGR_MCMC) | 3 | -| [Discriminative Bimodal Networks for Visual Localization and Detection With Natural Language Queries](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Discriminative_Bimodal_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/YutingZhang/dbnet-caffe-matlab) | 3 | -| [AdaNet: Adaptive Structural Learning of Artificial Neural Networks](http://proceedings.mlr.press/v70/cortes17a.html) | ICML | [code](https://github.com/davidabek1/adanet) | 3 | -| [Large Margin Object Tracking With Circulant Feature Maps](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Large_Margin_Object_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sallymmx/LMCF) | 3 | -| [Compatible Reward Inverse Reinforcement Learning](http://papers.nips.cc/paper/6800-compatible-reward-inverse-reinforcement-learning.pdf) | NIPS | [code](https://github.com/albertometelli/crirl) | 3 | -| [Adversarial Surrogate Losses for Ordinal Regression](http://papers.nips.cc/paper/6659-adversarial-surrogate-losses-for-ordinal-regression.pdf) | NIPS | [code](https://github.com/rizalzaf/adversarial-ordinal) | 3 | -| [Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms](http://papers.nips.cc/paper/6652-continuous-dr-submodular-maximization-structure-and-algorithms.pdf) | NIPS | [code](https://github.com/bianan) | 3 | -| [Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning](http://papers.nips.cc/paper/7154-unifying-pac-and-regret-uniform-pac-bounds-for-episodic-reinforcement-learning.pdf) | NIPS | [code](https://github.com/chrodan/FiniteEpisodicRL.jl) | 3 | -| [A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control](http://papers.nips.cc/paper/7177-a-framework-for-multi-armedbandit-testing-with-online-fdr-control.pdf) | NIPS | [code](https://github.com/fanny-yang/MABFDR) | 3 | -| [Counting Everyday Objects in Everyday Scenes](http://openaccess.thecvf.com/content_cvpr_2017/html/Chattopadhyay_Counting_Everyday_Objects_CVPR_2017_paper.html) | CVPR | [code](https://github.com/prithv1/cvpr2017_counting) | 3 | -| [Loss Max-Pooling for Semantic Image Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Bulo_Loss_Max-Pooling_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jjkke88/LMP) | 3 | -| [Aesthetic Critiques Generation for Photos](http://openaccess.thecvf.com/content_iccv_2017/html/Chang_Aesthetic_Critiques_Generation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/kunghunglu/DeepPhotoCritic-ICCV17) | 3 | -| [Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems](http://papers.nips.cc/paper/6798-expectation-propagation-with-stochastic-kinetic-model-in-complex-interaction-systems.pdf) | NIPS | [code](https://github.com/lefangcs/Expectation-Propagation-with-Stochastic-Kinetic-Model-in-Complex-Interaction-Systems) | 3 | -| [Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs](http://papers.nips.cc/paper/7049-near-optimal-edge-evaluation-in-explicit-generalized-binomial-graphs.pdf) | NIPS | [code](https://github.com/sanjibac/matlab_learning_collision_checking) | 3 | +| [Bridging the Gap Between Value and Policy Based Reinforcement Learning](http://papers.nips.cc/paper/6870-bridging-the-gap-between-value-and-policy-based-reinforcement-learning.pdf) | NIPS | [code](https://github.com/tensorflow/models) | 46593 | +| [REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models](http://papers.nips.cc/paper/6856-rebar-low-variance-unbiased-gradient-estimates-for-discrete-latent-variable-models.pdf) | NIPS | [code](https://github.com/tensorflow/models) | 46593 | +| [Focal Loss for Dense Object Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Lin_Focal_Loss_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/facebookresearch/Detectron) | 18356 | +| [Mask R-CNN](http://openaccess.thecvf.com/content_iccv_2017/html/He_Mask_R-CNN_ICCV_2017_paper.html) | ICCV | [code](https://github.com/matterport/Mask_RCNN) | 9493 | +| [Deep Photo Style Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Luan_Deep_Photo_Style_CVPR_2017_paper.html) | CVPR | [code](https://github.com/luanfujun/deep-photo-styletransfer) | 8655 | +| [LightGBM: A Highly Efficient Gradient Boosting Decision Tree](http://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf) | NIPS | [code](https://github.com/Microsoft/LightGBM) | 7536 | +| [Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation](http://papers.nips.cc/paper/7112-scalable-trust-region-method-for-deep-reinforcement-learning-using-kronecker-factored-approximation.pdf) | NIPS | [code](https://github.com/openai/baselines) | 6449 | +| [Attention is All you Need](http://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf) | NIPS | [code](https://github.com/tensorflow/tensor2tensor) | 6288 | +| [Large Pose 3D Face Reconstruction From a Single Image via Direct Volumetric CNN Regression](http://openaccess.thecvf.com/content_iccv_2017/html/Jackson_Large_Pose_3D_ICCV_2017_paper.html) | ICCV | [code](https://github.com/AaronJackson/vrn) | 3354 | +| [Densely Connected Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Densely_Connected_Convolutional_CVPR_2017_paper.html) | CVPR | [code](https://github.com/liuzhuang13/DenseNet) | 3130 | +| [A Unified Approach to Interpreting Model Predictions](http://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions.pdf) | NIPS | [code](https://github.com/slundberg/shap) | 3122 | +| [Deformable Convolutional Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Deformable_Convolutional_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/msracver/Deformable-ConvNets) | 2165 | +| [ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games](http://papers.nips.cc/paper/6859-elf-an-extensive-lightweight-and-flexible-research-platform-for-real-time-strategy-games.pdf) | NIPS | [code](https://github.com/facebookresearch/ELF) | 1823 | +| [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Qi_PointNet_Deep_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/charlesq34/pointnet) | 1523 | +| [Improved Training of Wasserstein GANs](http://papers.nips.cc/paper/7159-improved-training-of-wasserstein-gans.pdf) | NIPS | [code](https://github.com/igul222/improved_wgan_training) | 1405 | +| [Fully Convolutional Instance-Aware Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Fully_Convolutional_Instance-Aware_CVPR_2017_paper.html) | CVPR | [code](https://github.com/msracver/FCIS) | 1395 | +| [Aggregated Residual Transformations for Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Xie_Aggregated_Residual_Transformations_CVPR_2017_paper.html) | CVPR | [code](https://github.com/facebookresearch/ResNeXt) | 1361 | +| [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Ledig_Photo-Realistic_Single_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tensorlayer/srgan) | 1301 | +| [Unsupervised Image-to-Image Translation Networks](http://papers.nips.cc/paper/6672-unsupervised-image-to-image-translation-networks.pdf) | NIPS | [code](https://github.com/mingyuliutw/unit) | 1205 | +| [Photographic Image Synthesis With Cascaded Refinement Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Photographic_Image_Synthesis_ICCV_2017_paper.html) | ICCV | [code](https://github.com/CQFIO/PhotographicImageSynthesis) | 1142 | +| [High-Resolution Image Inpainting Using Multi-Scale Neural Patch Synthesis](http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_High-Resolution_Image_Inpainting_CVPR_2017_paper.html) | CVPR | [code](https://github.com/leehomyc/Faster-High-Res-Neural-Inpainting) | 1072 | +| [SphereFace: Deep Hypersphere Embedding for Face Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_SphereFace_Deep_Hypersphere_CVPR_2017_paper.html) | CVPR | [code](https://github.com/wy1iu/sphereface) | 1048 | +| [Deep Feature Flow for Video Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Deep_Feature_Flow_CVPR_2017_paper.html) | CVPR | [code](https://github.com/msracver/Deep-Feature-Flow) | 966 | +| [Bayesian GAN](http://papers.nips.cc/paper/6953-bayesian-gan.pdf) | NIPS | [code](https://github.com/andrewgordonwilson/bayesgan) | 942 | +| [Pyramid Scene Parsing Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhao_Pyramid_Scene_Parsing_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hszhao/PSPNet) | 934 | +| [Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes](http://papers.nips.cc/paper/7098-efficient-modeling-of-latent-information-in-supervised-learning-using-gaussian-processes.pdf) | NIPS | [code](https://github.com/SheffieldML/GPy) | 906 | +| [Finding Tiny Faces](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Finding_Tiny_Faces_CVPR_2017_paper.html) | CVPR | [code](https://github.com/peiyunh/tiny) | 856 | +| [Toward Multimodal Image-to-Image Translation](http://papers.nips.cc/paper/6650-toward-multimodal-image-to-image-translation.pdf) | NIPS | [code](https://github.com/junyanz/BiCycleGAN) | 794 | +| [Learning to Discover Cross-Domain Relations with Generative Adversarial Networks](http://proceedings.mlr.press/v70/kim17a.html) | ICML | [code](https://github.com/carpedm20/DiscoGAN-pytorch) | 784 | +| [YOLO9000: Better, Faster, Stronger](http://openaccess.thecvf.com/content_cvpr_2017/html/Redmon_YOLO9000_Better_Faster_CVPR_2017_paper.html) | CVPR | [code](https://github.com/philipperemy/yolo-9000) | 773 | +| [PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space](http://papers.nips.cc/paper/7095-pointnet-deep-hierarchical-feature-learning-on-point-sets-in-a-metric-space.pdf) | NIPS | [code](https://github.com/charlesq34/pointnet2) | 772 | +| [Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks](http://proceedings.mlr.press/v70/finn17a.html) | ICML | [code](https://github.com/cbfinn/maml) | 729 | +| [FlowNet 2.0: Evolution of Optical Flow Estimation With Deep Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Ilg_FlowNet_2.0_Evolution_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lmb-freiburg/flownet2) | 720 | +| [Channel Pruning for Accelerating Very Deep Neural Networks](http://openaccess.thecvf.com/content_iccv_2017/html/He_Channel_Pruning_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/yihui-he/channel-pruning) | 649 | +| [Dilated Residual Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Yu_Dilated_Residual_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fyu/drn) | 640 | +| [Inferring and Executing Programs for Visual Reasoning](http://openaccess.thecvf.com/content_iccv_2017/html/Johnson_Inferring_and_Executing_ICCV_2017_paper.html) | ICCV | [code](https://github.com/facebookresearch/clevr-iep) | 636 | +| [DSOD: Learning Deeply Supervised Object Detectors From Scratch](http://openaccess.thecvf.com/content_iccv_2017/html/Shen_DSOD_Learning_Deeply_ICCV_2017_paper.html) | ICCV | [code](https://github.com/szq0214/DSOD) | 582 | +| [Arbitrary Style Transfer in Real-Time With Adaptive Instance Normalization](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Arbitrary_Style_Transfer_ICCV_2017_paper.html) | ICCV | [code](https://github.com/xunhuang1995/AdaIN-style) | 572 | +| [Accelerating Eulerian Fluid Simulation With Convolutional Networks](http://proceedings.mlr.press/v70/tompson17a.html) | ICML | [code](https://github.com/google/FluidNet) | 570 | +| [Learning Disentangled Representations with Semi-Supervised Deep Generative Models](http://papers.nips.cc/paper/7174-learning-disentangled-representations-with-semi-supervised-deep-generative-models.pdf) | NIPS | [code](https://github.com/probtorch/probtorch) | 556 | +| [Inductive Representation Learning on Large Graphs](http://papers.nips.cc/paper/6703-inductive-representation-learning-on-large-graphs.pdf) | NIPS | [code](https://github.com/williamleif/GraphSAGE) | 552 | +| [Regressing Robust and Discriminative 3D Morphable Models With a Very Deep Neural Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Tran_Regressing_Robust_and_CVPR_2017_paper.html) | CVPR | [code](https://github.com/anhttran/3dmm_cnn) | 537 | +| [How Far Are We From Solving the 2D & 3D Face Alignment Problem? (And a Dataset of 230,000 3D Facial Landmarks)](http://openaccess.thecvf.com/content_iccv_2017/html/Bulat_How_Far_Are_ICCV_2017_paper.html) | ICCV | [code](https://github.com/1adrianb/2D-and-3D-face-alignment) | 526 | +| [SSH: Single Stage Headless Face Detector](http://openaccess.thecvf.com/content_iccv_2017/html/Najibi_SSH_Single_Stage_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mahyarnajibi/SSH) | 515 | +| [Learning From Simulated and Unsupervised Images Through Adversarial Training](http://openaccess.thecvf.com/content_cvpr_2017/html/Shrivastava_Learning_From_Simulated_CVPR_2017_paper.html) | CVPR | [code](https://github.com/carpedm20/simulated-unsupervised-tensorflow) | 492 | +| [Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space](http://openaccess.thecvf.com/content_cvpr_2017/html/Nguyen_Plug__Play_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Evolving-AI-Lab/ppgn) | 487 | +| [Video Frame Interpolation via Adaptive Convolution](http://openaccess.thecvf.com/content_cvpr_2017/html/Niklaus_Video_Frame_Interpolation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sniklaus/pytorch-sepconv) | 482 | +| [Video Frame Interpolation via Adaptive Separable Convolution](http://openaccess.thecvf.com/content_iccv_2017/html/Niklaus_Video_Frame_Interpolation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/sniklaus/pytorch-sepconv) | 482 | +| [GMS: Grid-based Motion Statistics for Fast, Ultra-Robust Feature Correspondence](http://openaccess.thecvf.com/content_cvpr_2017/html/Bian_GMS_Grid-based_Motion_CVPR_2017_paper.html) | CVPR | [code](https://github.com/JiawangBian/GMS-Feature-Matcher) | 460 | +| [Joint Detection and Identification Feature Learning for Person Search](http://openaccess.thecvf.com/content_cvpr_2017/html/Xiao_Joint_Detection_and_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ShuangLI59/person_search) | 459 | +| [Dual Path Networks](http://papers.nips.cc/paper/7033-dual-path-networks.pdf) | NIPS | [code](https://github.com/cypw/DPNs) | 451 | +| [Flow-Guided Feature Aggregation for Video Object Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Flow-Guided_Feature_Aggregation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/msracver/Flow-Guided-Feature-Aggregation) | 436 | +| [Deep Image Matting](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Deep_Image_Matting_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Joker316701882/Deep-Image-Matting) | 434 | +| [Richer Convolutional Features for Edge Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Richer_Convolutional_Features_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yun-liu/rcf) | 399 | +| [Annotating Object Instances With a Polygon-RNN](http://openaccess.thecvf.com/content_cvpr_2017/html/Castrejon_Annotating_Object_Instances_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fidler-lab/polyrnn-pp-pytorch) | 397 | +| [Recurrent Highway Networks](http://proceedings.mlr.press/v70/zilly17a.html) | ICML | [code](https://github.com/julian121266/RecurrentHighwayNetworks) | 397 | +| [Detect to Track and Track to Detect](http://openaccess.thecvf.com/content_iccv_2017/html/Feichtenhofer_Detect_to_Track_ICCV_2017_paper.html) | ICCV | [code](https://github.com/feichtenhofer/Detect-Track) | 387 | +| [RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_RefineNet_Multi-Path_Refinement_CVPR_2017_paper.html) | CVPR | [code](https://github.com/guosheng/refinenet) | 379 | +| [Detecting Oriented Text in Natural Images by Linking Segments](http://openaccess.thecvf.com/content_cvpr_2017/html/Shi_Detecting_Oriented_Text_CVPR_2017_paper.html) | CVPR | [code](https://github.com/dengdan/seglink) | 364 | +| [Deep Lattice Networks and Partial Monotonic Functions](http://papers.nips.cc/paper/6891-deep-lattice-networks-and-partial-monotonic-functions.pdf) | NIPS | [code](https://github.com/tensorflow/lattice) | 349 | +| [Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results](http://papers.nips.cc/paper/6719-mean-teachers-are-better-role-models-weight-averaged-consistency-targets-improve-semi-supervised-deep-learning-results.pdf) | NIPS | [code](https://github.com/CuriousAI/mean-teacher/) | 347 | +| [RON: Reverse Connection With Objectness Prior Networks for Object Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Kong_RON_Reverse_Connection_CVPR_2017_paper.html) | CVPR | [code](https://github.com/taokong/RON) | 345 | +| [Universal Style Transfer via Feature Transforms](http://papers.nips.cc/paper/6642-universal-style-transfer-via-feature-transforms.pdf) | NIPS | [code](https://github.com/Yijunmaverick/UniversalStyleTransfer) | 344 | +| [Residual Attention Network for Image Classification](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Residual_Attention_Network_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fwang91/residual-attention-network) | 329 | +| [One-Shot Video Object Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Caelles_One-Shot_Video_Object_CVPR_2017_paper.html) | CVPR | [code](https://github.com/scaelles/OSVOS-TensorFlow) | 316 | +| [Accurate Single Stage Detector Using Recurrent Rolling Convolution](http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_Accurate_Single_Stage_CVPR_2017_paper.html) | CVPR | [code](https://github.com/xiaohaoChen/rrc_detection) | 314 | +| [Feature Pyramid Networks for Object Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Feature_Pyramid_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/unsky/FPN) | 310 | +| [Efficient softmax approximation for GPUs](http://proceedings.mlr.press/v70/grave17a.html) | ICML | [code](https://github.com/facebookresearch/adaptive-softmax) | 304 | +| [OctNet: Learning Deep 3D Representations at High Resolutions](http://openaccess.thecvf.com/content_cvpr_2017/html/Riegler_OctNet_Learning_Deep_CVPR_2017_paper.html) | CVPR | [code](https://github.com/griegler/octnet) | 302 | +| [Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2017/html/Lai_Deep_Laplacian_Pyramid_CVPR_2017_paper.html) | CVPR | [code](https://github.com/phoenix104104/LapSRN) | 301 | +| [Pixel Recursive Super Resolution](http://openaccess.thecvf.com/content_iccv_2017/html/Dahl_Pixel_Recursive_Super_ICCV_2017_paper.html) | ICCV | [code](https://github.com/nilboy/pixel-recursive-super-resolution) | 301 | +| [Self-Critical Sequence Training for Image Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Rennie_Self-Critical_Sequence_Training_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ruotianluo/self-critical.pytorch) | 299 | +| [Age Progression/Regression by Conditional Adversarial Autoencoder](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Age_ProgressionRegression_by_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ZZUTK/Face-Aging-CAAE) | 297 | +| [Style Transfer from Non-Parallel Text by Cross-Alignment](http://papers.nips.cc/paper/7259-style-transfer-from-non-parallel-text-by-cross-alignment.pdf) | NIPS | [code](https://github.com/shentianxiao/language-style-transfer) | 296 | +| [Dilated Recurrent Neural Networks](http://papers.nips.cc/paper/6613-dilated-recurrent-neural-networks.pdf) | NIPS | [code](https://github.com/code-terminator/DilatedRNN) | 285 | +| [Lifting From the Deep: Convolutional 3D Pose Estimation From a Single Image](http://openaccess.thecvf.com/content_cvpr_2017/html/Tome_Lifting_From_the_CVPR_2017_paper.html) | CVPR | [code](https://github.com/DenisTome/Lifting-from-the-Deep-release) | 280 | +| [DeepBach: a Steerable Model for Bach Chorales Generation](http://proceedings.mlr.press/v70/hadjeres17a.html) | ICML | [code](https://github.com/Ghadjeres/DeepBach) | 276 | +| [The Predictron: End-To-End Learning and Planning](http://proceedings.mlr.press/v70/silver17a.html) | ICML | [code](https://github.com/zhongwen/predictron) | 274 | +| [Convolutional Sequence to Sequence Learning](http://proceedings.mlr.press/v70/gehring17a.html) | ICML | [code](https://github.com/tobyyouup/conv_seq2seq) | 258 | +| [OptNet: Differentiable Optimization as a Layer in Neural Networks](http://proceedings.mlr.press/v70/amos17a.html) | ICML | [code](https://github.com/locuslab/optnet) | 245 | +| [Prototypical Networks for Few-shot Learning](http://papers.nips.cc/paper/6996-prototypical-networks-for-few-shot-learning.pdf) | NIPS | [code](https://github.com/jakesnell/prototypical-networks) | 244 | +| [Deep Voice: Real-time Neural Text-to-Speech](http://proceedings.mlr.press/v70/arik17a.html) | ICML | [code](https://github.com/israelg99/deepvoice) | 242 | +| [Reinforcement Learning with Deep Energy-Based Policies](http://proceedings.mlr.press/v70/haarnoja17a.html) | ICML | [code](https://github.com/haarnoja/softqlearning) | 233 | +| [Learning Deep CNN Denoiser Prior for Image Restoration](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Learning_Deep_CNN_CVPR_2017_paper.html) | CVPR | [code](https://github.com/cszn/IRCNN) | 231 | +| [GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium](http://papers.nips.cc/paper/7240-gans-trained-by-a-two-time-scale-update-rule-converge-to-a-local-nash-equilibrium.pdf) | NIPS | [code](https://github.com/bioinf-jku/TTUR) | 229 | +| [A Point Set Generation Network for 3D Object Reconstruction From a Single Image](http://openaccess.thecvf.com/content_cvpr_2017/html/Fan_A_Point_Set_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fanhqme/PointSetGeneration) | 228 | +| [Deeply Supervised Salient Object Detection With Short Connections](http://openaccess.thecvf.com/content_cvpr_2017/html/Hou_Deeply_Supervised_Salient_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Joker316701882/Salient-Object-Detection) | 228 | +| [BlitzNet: A Real-Time Deep Network for Scene Understanding](http://openaccess.thecvf.com/content_iccv_2017/html/Dvornik_BlitzNet_A_Real-Time_ICCV_2017_paper.html) | ICCV | [code](https://github.com/dvornikita/blitznet) | 227 | +| [Language Modeling with Gated Convolutional Networks](http://proceedings.mlr.press/v70/dauphin17a.html) | ICML | [code](https://github.com/anantzoid/Language-Modeling-GatedCNN) | 221 | +| [Unlabeled Samples Generated by GAN Improve the Person Re-Identification Baseline in Vitro](http://openaccess.thecvf.com/content_iccv_2017/html/Zheng_Unlabeled_Samples_Generated_ICCV_2017_paper.html) | ICCV | [code](https://github.com/layumi/Person-reID_GAN) | 215 | +| [Stacked Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Stacked_Generative_Adversarial_CVPR_2017_paper.html) | CVPR | [code](https://github.com/xunhuang1995/SGAN) | 215 | +| [RMPE: Regional Multi-Person Pose Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Fang_RMPE_Regional_Multi-Person_ICCV_2017_paper.html) | ICCV | [code](https://github.com/MVIG-SJTU/RMPE) | 215 | +| [Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Lu_Knowing_When_to_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jiasenlu/AdaptiveAttention) | 214 | +| [Generative Face Completion](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Generative_Face_Completion_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Yijunmaverick/GenerativeFaceCompletion) | 212 | +| [VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Lee_VPGNet_Vanishing_Point_ICCV_2017_paper.html) | ICCV | [code](https://github.com/SeokjuLee/VPGNet) | 210 | +| [The Reversible Residual Network: Backpropagation Without Storing Activations](http://papers.nips.cc/paper/6816-the-reversible-residual-network-backpropagation-without-storing-activations.pdf) | NIPS | [code](https://github.com/renmengye/revnet-public) | 210 | +| [Recurrent Scale Approximation for Object Detection in CNN](http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Recurrent_Scale_Approximation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/sciencefans/RSA-for-object-detection) | 209 | +| [Learning From Synthetic Humans](http://openaccess.thecvf.com/content_cvpr_2017/html/Varol_Learning_From_Synthetic_CVPR_2017_paper.html) | CVPR | [code](https://github.com/gulvarol/surreal) | 207 | +| [Spatially Adaptive Computation Time for Residual Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Figurnov_Spatially_Adaptive_Computation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/mfigurnov/sact) | 203 | +| [Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Beyond_Face_Rotation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/HRLTY/TP-GAN) | 202 | +| [3D Bounding Box Estimation Using Deep Learning and Geometry](http://openaccess.thecvf.com/content_cvpr_2017/html/Mousavian_3D_Bounding_Box_CVPR_2017_paper.html) | CVPR | [code](https://github.com/smallcorgi/3D-Deepbox) | 200 | +| [Multi-View 3D Object Detection Network for Autonomous Driving](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Multi-View_3D_Object_CVPR_2017_paper.html) | CVPR | [code](https://github.com/bostondiditeam/MV3D) | 199 | +| [Visual Dialog](http://openaccess.thecvf.com/content_cvpr_2017/html/Das_Visual_Dialog_CVPR_2017_paper.html) | CVPR | [code](https://github.com/batra-mlp-lab/visdial) | 199 | +| [Interpretable Explanations of Black Boxes by Meaningful Perturbation](http://openaccess.thecvf.com/content_iccv_2017/html/Fong_Interpretable_Explanations_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jacobgil/pytorch-explain-black-box) | 192 | +| [Inverse Compositional Spatial Transformer Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Inverse_Compositional_Spatial_CVPR_2017_paper.html) | CVPR | [code](https://github.com/chenhsuanlin/inverse-compositional-STN) | 189 | +| [FastMask: Segment Multi-Scale Object Candidates in One Shot](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_FastMask_Segment_Multi-Scale_CVPR_2017_paper.html) | CVPR | [code](https://github.com/voidrank/FastMask) | 189 | +| [OnACID: Online Analysis of Calcium Imaging Data in Real Time](http://papers.nips.cc/paper/6832-onacid-online-analysis-of-calcium-imaging-data-in-real-time.pdf) | NIPS | [code](https://github.com/simonsfoundation/caiman) | 189 | +| [Semantic Scene Completion From a Single Depth Image](http://openaccess.thecvf.com/content_cvpr_2017/html/Song_Semantic_Scene_Completion_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shurans/sscnet) | 188 | +| [Learning Efficient Convolutional Networks Through Network Slimming](http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Learning_Efficient_Convolutional_ICCV_2017_paper.html) | ICCV | [code](https://github.com/liuzhuang13/slimming) | 186 | +| [Learning Feature Pyramids for Human Pose Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Yang_Learning_Feature_Pyramids_ICCV_2017_paper.html) | ICCV | [code](https://github.com/bearpaw/PyraNet) | 185 | +| [Be Your Own Prada: Fashion Synthesis With Structural Coherence](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Be_Your_Own_ICCV_2017_paper.html) | ICCV | [code](https://github.com/zhusz/ICCV17-fashionGAN) | 183 | +| [Scene Graph Generation by Iterative Message Passing](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Scene_Graph_Generation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/danfeiX/scene-graph-TF-release) | 182 | +| [Fast Image Processing With Fully-Convolutional Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Fast_Image_Processing_ICCV_2017_paper.html) | ICCV | [code](https://github.com/CQFIO/FastImageProcessing) | 180 | +| [Learning Multiple Tasks with Multilinear Relationship Networks](http://papers.nips.cc/paper/6757-learning-multiple-tasks-with-multilinear-relationship-networks.pdf) | NIPS | [code](https://github.com/thuml/Xlearn) | 178 | +| [Learning to Reason: End-To-End Module Networks for Visual Question Answering](http://openaccess.thecvf.com/content_iccv_2017/html/Hu_Learning_to_Reason_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ronghanghu/n2nmn) | 178 | +| [Single Shot Text Detector With Regional Attention](http://openaccess.thecvf.com/content_iccv_2017/html/He_Single_Shot_Text_ICCV_2017_paper.html) | ICCV | [code](https://github.com/BestSonny/SSTD) | 176 | +| [Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment With Limited Resources](http://openaccess.thecvf.com/content_iccv_2017/html/Bulat_Binarized_Convolutional_Landmark_ICCV_2017_paper.html) | ICCV | [code](https://github.com/1adrianb/binary-human-pose-estimation) | 175 | +| [Deep Feature Interpolation for Image Content Changes](http://openaccess.thecvf.com/content_cvpr_2017/html/Upchurch_Deep_Feature_Interpolation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/paulu/deepfeatinterp) | 170 | +| [On Human Motion Prediction Using Recurrent Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Martinez_On_Human_Motion_CVPR_2017_paper.html) | CVPR | [code](https://github.com/una-dinosauria/human-motion-prediction) | 167 | +| [Image Super-Resolution via Deep Recursive Residual Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Tai_Image_Super-Resolution_via_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tyshiwo/DRRN_CVPR17) | 163 | +| [Learning Cross-Modal Embeddings for Cooking Recipes and Food Images](http://openaccess.thecvf.com/content_cvpr_2017/html/Salvador_Learning_Cross-Modal_Embeddings_CVPR_2017_paper.html) | CVPR | [code](https://github.com/torralba-lab/im2recipe) | 160 | +| [Input Convex Neural Networks](http://proceedings.mlr.press/v70/amos17b.html) | ICML | [code](https://github.com/locuslab/icnn) | 159 | +| [Simple Does It: Weakly Supervised Instance and Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Khoreva_Simple_Does_It_CVPR_2017_paper.html) | CVPR | [code](https://github.com/philferriere/tfwss) | 159 | +| [Low-Shot Visual Recognition by Shrinking and Hallucinating Features](http://openaccess.thecvf.com/content_iccv_2017/html/Hariharan_Low-Shot_Visual_Recognition_ICCV_2017_paper.html) | ICCV | [code](https://github.com/facebookresearch/low-shot-shrink-hallucinate) | 158 | +| [Oriented Response Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Oriented_Response_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ZhouYanzhao/ORN) | 157 | +| [Soft Proposal Networks for Weakly Supervised Object Localization](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Soft_Proposal_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/yeezhu/SPN.pytorch) | 154 | +| [Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks](http://proceedings.mlr.press/v70/mescheder17a.html) | ICML | [code](https://github.com/LMescheder/AdversarialVariationalBayes) | 147 | +| [Axiomatic Attribution for Deep Networks](http://proceedings.mlr.press/v70/sundararajan17a.html) | ICML | [code](https://github.com/hiranumn/IntegratedGradients) | 146 | +| [Gradient Episodic Memory for Continual Learning](http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf) | NIPS | [code](https://github.com/facebookresearch/GradientEpisodicMemory) | 146 | +| [DSAC - Differentiable RANSAC for Camera Localization](http://openaccess.thecvf.com/content_cvpr_2017/html/Brachmann_DSAC_-_Differentiable_CVPR_2017_paper.html) | CVPR | [code](https://github.com/cvlab-dresden/DSAC) | 144 | +| [Attend to You: Personalized Image Captioning With Context Sequence Memory Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Attend_to_You_CVPR_2017_paper.html) | CVPR | [code](https://github.com/cesc-park/attend2u) | 143 | +| [Conditional Similarity Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Veit_Conditional_Similarity_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/andreasveit/conditional-similarity-networks) | 142 | +| [Language Modeling with Recurrent Highway Hypernetworks](http://papers.nips.cc/paper/6919-language-modeling-with-recurrent-highway-hypernetworks.pdf) | NIPS | [code](https://github.com/jsuarez5341/Recurrent-Highway-Hypernetworks-NIPS) | 141 | +| [Triple Generative Adversarial Nets](http://papers.nips.cc/paper/6997-triple-generative-adversarial-nets.pdf) | NIPS | [code](https://github.com/zhenxuan00/triple-gan) | 138 | +| [Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning](http://papers.nips.cc/paper/6974-interpolated-policy-gradient-merging-on-policy-and-off-policy-gradient-estimation-for-deep-reinforcement-learning.pdf) | NIPS | [code](https://github.com/shaneshixiang/rllabplusplus) | 138 | +| [One-Sided Unsupervised Domain Mapping](http://papers.nips.cc/paper/6677-one-sided-unsupervised-domain-mapping.pdf) | NIPS | [code](https://github.com/sagiebenaim/DistanceGAN) | 137 | +| [Detecting Visual Relationships With Deep Relational Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Dai_Detecting_Visual_Relationships_CVPR_2017_paper.html) | CVPR | [code](https://github.com/doubledaibo/drnet_cvpr2017) | 137 | +| [Attentive Recurrent Comparators](http://proceedings.mlr.press/v70/shyam17a.html) | ICML | [code](https://github.com/sanyam5/arc-pytorch) | 136 | +| [Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach](http://openaccess.thecvf.com/content_iccv_2017/html/Zhou_Towards_3D_Human_ICCV_2017_paper.html) | ICCV | [code](https://github.com/xingyizhou/pose-hg-3d) | 136 | +| [Learning a Multi-View Stereo Machine](http://papers.nips.cc/paper/6640-learning-a-multi-view-stereo-machine.pdf) | NIPS | [code](https://github.com/akar43/lsm) | 135 | +| [Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model](http://papers.nips.cc/paper/7145-deep-learning-for-precipitation-nowcasting-a-benchmark-and-a-new-model.pdf) | NIPS | [code](https://github.com/sxjscience/HKO-7) | 134 | +| [Multi-Context Attention for Human Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Chu_Multi-Context_Attention_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/bearpaw/pose-attention) | 131 | +| [Controlling Perceptual Factors in Neural Style Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Gatys_Controlling_Perceptual_Factors_CVPR_2017_paper.html) | CVPR | [code](https://github.com/leongatys/NeuralImageSynthesis) | 130 | +| [Bayesian Compression for Deep Learning](http://papers.nips.cc/paper/6921-bayesian-compression-for-deep-learning.pdf) | NIPS | [code](https://github.com/KarenUllrich/Tutorial_BayesianCompressionForDL) | 130 | +| [Adversarial Discriminative Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2017/html/Tzeng_Adversarial_Discriminative_Domain_CVPR_2017_paper.html) | CVPR | [code](https://github.com/corenel/pytorch-adda) | 129 | +| [Working hard to know your neighbor's margins: Local descriptor learning loss](http://papers.nips.cc/paper/7068-working-hard-to-know-your-neighbors-margins-local-descriptor-learning-loss.pdf) | NIPS | [code](https://github.com/DagnyT/hardnet) | 128 | +| [Concrete Dropout](http://papers.nips.cc/paper/6949-concrete-dropout.pdf) | NIPS | [code](https://github.com/yaringal/ConcreteDropout) | 127 | +| [SegFlow: Joint Learning for Video Object Segmentation and Optical Flow](http://openaccess.thecvf.com/content_iccv_2017/html/Cheng_SegFlow_Joint_Learning_ICCV_2017_paper.html) | ICCV | [code](https://github.com/JingchunCheng/SegFlow) | 127 | +| [Segmentation-Aware Convolutional Networks Using Local Attention Masks](http://openaccess.thecvf.com/content_iccv_2017/html/Harley_Segmentation-Aware_Convolutional_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/aharley/segaware) | 126 | +| [Detail-Revealing Deep Video Super-Resolution](http://openaccess.thecvf.com/content_iccv_2017/html/Tao_Detail-Revealing_Deep_Video_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jiangsutx/SPMC_VideoSR) | 126 | +| [CREST: Convolutional Residual Learning for Visual Tracking](http://openaccess.thecvf.com/content_iccv_2017/html/Song_CREST_Convolutional_Residual_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ybsong00/CREST-Release) | 126 | +| [Discriminative Correlation Filter With Channel and Spatial Reliability](http://openaccess.thecvf.com/content_cvpr_2017/html/Lukezic_Discriminative_Correlation_Filter_CVPR_2017_paper.html) | CVPR | [code](https://github.com/alanlukezic/csr-dcf) | 124 | +| [SVDNet for Pedestrian Retrieval](http://openaccess.thecvf.com/content_iccv_2017/html/Sun_SVDNet_for_Pedestrian_ICCV_2017_paper.html) | ICCV | [code](https://github.com/syfafterzy/SVDNet-for-Pedestrian-Retrieval) | 121 | +| [Semantic Image Synthesis via Adversarial Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Dong_Semantic_Image_Synthesis_ICCV_2017_paper.html) | ICCV | [code](https://github.com/woozzu/dong_iccv_2017) | 121 | +| [Spatiotemporal Multiplier Networks for Video Action Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Feichtenhofer_Spatiotemporal_Multiplier_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/feichtenhofer/st-resnet) | 121 | +| [PoseTrack: Joint Multi-Person Pose Estimation and Tracking](http://openaccess.thecvf.com/content_cvpr_2017/html/Iqbal_PoseTrack_Joint_Multi-Person_CVPR_2017_paper.html) | CVPR | [code](https://github.com/iqbalu/PoseTrack-CVPR2017) | 121 | +| [Hierarchical Attentive Recurrent Tracking](http://papers.nips.cc/paper/6898-hierarchical-attentive-recurrent-tracking.pdf) | NIPS | [code](https://github.com/akosiorek/hart) | 121 | +| [Good Semi-supervised Learning That Requires a Bad GAN](http://papers.nips.cc/paper/7229-good-semi-supervised-learning-that-requires-a-bad-gan.pdf) | NIPS | [code](https://github.com/kimiyoung/ssl_bad_gan) | 120 | +| [Deep Watershed Transform for Instance Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Bai_Deep_Watershed_Transform_CVPR_2017_paper.html) | CVPR | [code](https://github.com/min2209/dwt) | 120 | +| [Associative Domain Adaptation](http://openaccess.thecvf.com/content_iccv_2017/html/Haeusser_Associative_Domain_Adaptation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/haeusser/learning_by_association) | 119 | +| [Learning by Association -- A Versatile Semi-Supervised Training Method for Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Haeusser_Learning_by_Association_CVPR_2017_paper.html) | CVPR | [code](https://github.com/haeusser/learning_by_association) | 119 | +| [Value Prediction Network](http://papers.nips.cc/paper/7192-value-prediction-network.pdf) | NIPS | [code](https://github.com/junhyukoh/value-prediction-network) | 119 | +| [Unrestricted Facial Geometry Reconstruction Using Image-To-Image Translation](http://openaccess.thecvf.com/content_iccv_2017/html/Sela_Unrestricted_Facial_Geometry_ICCV_2017_paper.html) | ICCV | [code](https://github.com/matansel/pix2vertex) | 119 | +| [MemNet: A Persistent Memory Network for Image Restoration](http://openaccess.thecvf.com/content_iccv_2017/html/Tai_MemNet_A_Persistent_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tyshiwo/MemNet) | 119 | +| [Bayesian Optimization with Gradients](http://papers.nips.cc/paper/7111-bayesian-optimization-with-gradients.pdf) | NIPS | [code](https://github.com/wujian16/Cornell-MOE) | 117 | +| [TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning](http://papers.nips.cc/paper/6749-terngrad-ternary-gradients-to-reduce-communication-in-distributed-deep-learning.pdf) | NIPS | [code](https://github.com/wenwei202/terngrad) | 117 | +| [Compressed Sensing using Generative Models](http://proceedings.mlr.press/v70/bora17a.html) | ICML | [code](https://github.com/AshishBora/csgm) | 116 | +| [Switching Convolutional Neural Network for Crowd Counting](http://openaccess.thecvf.com/content_cvpr_2017/html/Sam_Switching_Convolutional_Neural_CVPR_2017_paper.html) | CVPR | [code](https://github.com/val-iisc/crowd-counting-scnn) | 116 | +| [WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Durand_WILDCAT_Weakly_Supervised_CVPR_2017_paper.html) | CVPR | [code](https://github.com/durandtibo/wildcat.pytorch) | 116 | +| [Show, Adapt and Tell: Adversarial Training of Cross-Domain Image Captioner](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Show_Adapt_and_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tsenghungchen/show-adapt-and-tell) | 115 | +| [Video Frame Synthesis Using Deep Voxel Flow](http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Video_Frame_Synthesis_ICCV_2017_paper.html) | ICCV | [code](https://github.com/liuziwei7/voxel-flow) | 114 | +| [Multiple Instance Detection Network With Online Instance Classifier Refinement](http://openaccess.thecvf.com/content_cvpr_2017/html/Tang_Multiple_Instance_Detection_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ppengtang/oicr) | 113 | +| [Deep Pyramidal Residual Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Han_Deep_Pyramidal_Residual_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jhkim89/PyramidNet) | 112 | +| [Train longer, generalize better: closing the generalization gap in large batch training of neural networks](http://papers.nips.cc/paper/6770-train-longer-generalize-better-closing-the-generalization-gap-in-large-batch-training-of-neural-networks.pdf) | NIPS | [code](https://github.com/eladhoffer/bigBatch) | 112 | +| [Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Split-Brain_Autoencoders_Unsupervised_CVPR_2017_paper.html) | CVPR | [code](https://github.com/richzhang/splitbrainauto) | 110 | +| [Unite the People: Closing the Loop Between 3D and 2D Human Representations](http://openaccess.thecvf.com/content_cvpr_2017/html/Lassner_Unite_the_People_CVPR_2017_paper.html) | CVPR | [code](https://github.com/classner/up) | 110 | +| [Learning Combinatorial Optimization Algorithms over Graphs](http://papers.nips.cc/paper/7214-learning-combinatorial-optimization-algorithms-over-graphs.pdf) | NIPS | [code](https://github.com/Hanjun-Dai/graph_comb_opt) | 109 | +| [FeUdal Networks for Hierarchical Reinforcement Learning](http://proceedings.mlr.press/v70/vezhnevets17a.html) | ICML | [code](https://github.com/dmakian/feudal_networks) | 107 | +| [ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression](http://openaccess.thecvf.com/content_iccv_2017/html/Luo_ThiNet_A_Filter_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Roll920/ThiNet) | 105 | +| [Learning a Deep Embedding Model for Zero-Shot Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Learning_a_Deep_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lzrobots/DeepEmbeddingModel_ZSL) | 104 | +| [ECO: Efficient Convolution Operators for Tracking](http://openaccess.thecvf.com/content_cvpr_2017/html/Danelljan_ECO_Efficient_Convolution_CVPR_2017_paper.html) | CVPR | [code](https://github.com/nicewsyly/ECO) | 103 | +| [SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_SCA-CNN_Spatial_and_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zjuchenlong/sca-cnn.cvpr17) | 102 | +| [Multi-View Supervision for Single-View Reconstruction via Differentiable Ray Consistency](http://openaccess.thecvf.com/content_cvpr_2017/html/Tulsiani_Multi-View_Supervision_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shubhtuls/drc) | 100 | +| [Task-based End-to-end Model Learning in Stochastic Optimization](http://papers.nips.cc/paper/7132-task-based-end-to-end-model-learning-in-stochastic-optimization.pdf) | NIPS | [code](https://github.com/locuslab/e2e-model-learning) | 100 | +| [Learning to Compose Domain-Specific Transformations for Data Augmentation](http://papers.nips.cc/paper/6916-learning-to-compose-domain-specific-transformations-for-data-augmentation.pdf) | NIPS | [code](https://github.com/HazyResearch/tanda) | 97 | +| [Genetic CNN](http://openaccess.thecvf.com/content_iccv_2017/html/Xie_Genetic_CNN_ICCV_2017_paper.html) | ICCV | [code](https://github.com/aqibsaeed/Genetic-CNN) | 97 | +| [HashNet: Deep Learning to Hash by Continuation](http://openaccess.thecvf.com/content_iccv_2017/html/Cao_HashNet_Deep_Learning_ICCV_2017_paper.html) | ICCV | [code](https://github.com/thuml/HashNet) | 97 | +| [Interleaved Group Convolutions](http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Interleaved_Group_Convolutions_ICCV_2017_paper.html) | ICCV | [code](https://github.com/hellozting/InterleavedGroupConvolutions) | 95 | +| [Deeply-Learned Part-Aligned Representations for Person Re-Identification](http://openaccess.thecvf.com/content_iccv_2017/html/Zhao_Deeply-Learned_Part-Aligned_Representations_ICCV_2017_paper.html) | ICCV | [code](https://github.com/zlmzju/part_reid) | 95 | +| [Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model](http://papers.nips.cc/paper/6635-best-of-both-worlds-transferring-knowledge-from-discriminative-learning-to-a-generative-visual-dialog-model.pdf) | NIPS | [code](https://github.com/jiasenlu/visDial.pytorch) | 94 | +| [Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Multi-Scale_Continuous_CRFs_CVPR_2017_paper.html) | CVPR | [code](https://github.com/danxuhk/ContinuousCRF-CNN) | 93 | +| [Octree Generating Networks: Efficient Convolutional Architectures for High-Resolution 3D Outputs](http://openaccess.thecvf.com/content_iccv_2017/html/Tatarchenko_Octree_Generating_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/lmb-freiburg/ogn) | 92 | +| [Semantic Autoencoder for Zero-Shot Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Kodirov_Semantic_Autoencoder_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Elyorcv/SAE) | 92 | +| [Deep Hyperspherical Learning](http://papers.nips.cc/paper/6984-deep-hyperspherical-learning.pdf) | NIPS | [code](https://github.com/wy1iu/SphereNet) | 92 | +| [Decoupled Neural Interfaces using Synthetic Gradients](http://proceedings.mlr.press/v70/jaderberg17a.html) | ICML | [code](https://github.com/andrewliao11/dni.pytorch) | 90 | +| [Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks](http://papers.nips.cc/paper/6960-geometric-matrix-completion-with-recurrent-multi-graph-neural-networks.pdf) | NIPS | [code](https://github.com/fmonti/mgcnn) | 90 | +| [Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search](http://papers.nips.cc/paper/6780-practical-bayesian-optimization-for-model-fitting-with-bayesian-adaptive-direct-search.pdf) | NIPS | [code](https://github.com/lacerbi/bads) | 90 | +| [Optical Flow Estimation Using a Spatial Pyramid Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Ranjan_Optical_Flow_Estimation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sniklaus/pytorch-spynet) | 90 | +| [AMC: Attention guided Multi-modal Correlation Learning for Image Search](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_AMC_Attention_guided_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kanchen-usc/AMC_ATT) | 90 | +| [Deep Video Deblurring for Hand-Held Cameras](http://openaccess.thecvf.com/content_cvpr_2017/html/Su_Deep_Video_Deblurring_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shuochsu/DeepVideoDeblurring) | 89 | +| [Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data](http://papers.nips.cc/paper/6784-unsupervised-learning-of-disentangled-and-interpretable-representations-from-sequential-data.pdf) | NIPS | [code](https://github.com/wnhsu/FactorizedHierarchicalVAE) | 88 | +| [Causal Effect Inference with Deep Latent-Variable Models](http://papers.nips.cc/paper/7223-causal-effect-inference-with-deep-latent-variable-models.pdf) | NIPS | [code](https://github.com/AMLab-Amsterdam/CEVAE) | 87 | +| [GANs for Biological Image Synthesis](http://openaccess.thecvf.com/content_iccv_2017/html/Osokin_GANs_for_Biological_ICCV_2017_paper.html) | ICCV | [code](https://github.com/aosokin/biogans) | 85 | +| [MMD GAN: Towards Deeper Understanding of Moment Matching Network](http://papers.nips.cc/paper/6815-mmd-gan-towards-deeper-understanding-of-moment-matching-network.pdf) | NIPS | [code](https://github.com/OctoberChang/MMD-GAN) | 84 | +| [Representation Learning by Learning to Count](http://openaccess.thecvf.com/content_iccv_2017/html/Noroozi_Representation_Learning_by_ICCV_2017_paper.html) | ICCV | [code](https://github.com/gitlimlab/Representation-Learning-by-Learning-to-Count) | 84 | +| [Optical Flow in Mostly Rigid Scenes](http://openaccess.thecvf.com/content_cvpr_2017/html/Wulff_Optical_Flow_in_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jswulff/mrflow) | 83 | +| [Fast-Slow Recurrent Neural Networks](http://papers.nips.cc/paper/7173-fast-slow-recurrent-neural-networks.pdf) | NIPS | [code](https://github.com/amujika/Fast-Slow-LSTM) | 82 | +| [Unsupervised Video Summarization With Adversarial LSTM Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Mahasseni_Unsupervised_Video_Summarization_CVPR_2017_paper.html) | CVPR | [code](https://github.com/j-min/Adversarial_Video_Summary) | 82 | +| [Constrained Policy Optimization](http://proceedings.mlr.press/v70/achiam17a.html) | ICML | [code](https://github.com/jachiam/cpo) | 81 | +| [A-NICE-MC: Adversarial Training for MCMC](http://papers.nips.cc/paper/7099-a-nice-mc-adversarial-training-for-mcmc.pdf) | NIPS | [code](https://github.com/jiamings/a-nice-mc) | 80 | +| [Coarse-To-Fine Volumetric Prediction for Single-Image 3D Human Pose](http://openaccess.thecvf.com/content_cvpr_2017/html/Pavlakos_Coarse-To-Fine_Volumetric_Prediction_CVPR_2017_paper.html) | CVPR | [code](https://github.com/geopavlakos/c2f-vol-train) | 80 | +| [End-To-End Instance Segmentation With Recurrent Attention](http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_End-To-End_Instance_Segmentation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/renmengye/rec-attend-public) | 78 | +| [DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data](http://openaccess.thecvf.com/content_cvpr_2017/html/Gurumurthy_DeLiGAN__Generative_CVPR_2017_paper.html) | CVPR | [code](https://github.com/val-iisc/deligan) | 78 | +| [Learning Shape Abstractions by Assembling Volumetric Primitives](http://openaccess.thecvf.com/content_cvpr_2017/html/Tulsiani_Learning_Shape_Abstractions_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shubhtuls/volumetricPrimitives) | 77 | +| [Local Binary Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Juefei-Xu_Local_Binary_Convolutional_CVPR_2017_paper.html) | CVPR | [code](https://github.com/juefeix/lbcnn.torch) | 77 | +| [Raster-To-Vector: Revisiting Floorplan Transformation](http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Raster-To-Vector_Revisiting_Floorplan_ICCV_2017_paper.html) | ICCV | [code](https://github.com/art-programmer/FloorplanTransformation) | 76 | +| [Positive-Unlabeled Learning with Non-Negative Risk Estimator](http://papers.nips.cc/paper/6765-positive-unlabeled-learning-with-non-negative-risk-estimator.pdf) | NIPS | [code](https://github.com/kiryor/nnPUlearning) | 76 | +| [Hard-Aware Deeply Cascaded Embedding](http://openaccess.thecvf.com/content_iccv_2017/html/Yuan_Hard-Aware_Deeply_Cascaded_ICCV_2017_paper.html) | ICCV | [code](https://github.com/PkuRainBow/Hard-Aware-Deeply-Cascaded-Embedding_release) | 75 | +| [Deep Image Harmonization](http://openaccess.thecvf.com/content_cvpr_2017/html/Tsai_Deep_Image_Harmonization_CVPR_2017_paper.html) | CVPR | [code](https://github.com/wasidennis/DeepHarmonization) | 73 | +| [Shape Completion Using 3D-Encoder-Predictor CNNs and Shape Synthesis](http://openaccess.thecvf.com/content_cvpr_2017/html/Dai_Shape_Completion_Using_CVPR_2017_paper.html) | CVPR | [code](https://github.com/angeladai/cnncomplete) | 73 | +| [Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Not_All_Pixels_CVPR_2017_paper.html) | CVPR | [code](https://github.com/liuziwei7/region-conv) | 73 | +| [Improved Stereo Matching With Constant Highway Networks and Reflective Confidence Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Shaked_Improved_Stereo_Matching_CVPR_2017_paper.html) | CVPR | [code](https://github.com/amitshaked/resmatch) | 72 | +| [Query-Guided Regression Network With Context Policy for Phrase Grounding](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Query-Guided_Regression_Network_ICCV_2017_paper.html) | ICCV | [code](https://github.com/kanchen-usc/QRC-Net) | 72 | +| [Top-Down Visual Saliency Guided by Captions](http://openaccess.thecvf.com/content_cvpr_2017/html/Ramanishka_Top-Down_Visual_Saliency_CVPR_2017_paper.html) | CVPR | [code](https://github.com/VisionLearningGroup/caption-guided-saliency) | 72 | +| [Feedback Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Zamir_Feedback_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/amir32002/feedback-networks) | 72 | +| [What Actions Are Needed for Understanding Human Actions in Videos?](http://openaccess.thecvf.com/content_iccv_2017/html/Sigurdsson_What_Actions_Are_ICCV_2017_paper.html) | ICCV | [code](https://github.com/gsig/actions-for-actions) | 71 | +| [Xception: Deep Learning With Depthwise Separable Convolutions](http://openaccess.thecvf.com/content_cvpr_2017/html/Chollet_Xception_Deep_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tstandley/Xception-PyTorch) | 71 | +| [Action-Decision Networks for Visual Tracking With Deep Reinforcement Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Yun_Action-Decision_Networks_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hellbell/ADNet) | 71 | +| [Video Propagation Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Jampani_Video_Propagation_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/varunjampani/video_prop_networks) | 70 | +| [Image-To-Image Translation With Conditional Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/williamFalcon/pix2pix-keras) | 70 | +| [Quality Aware Network for Set to Set Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Quality_Aware_Network_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sciencefans/Quality-Aware-Network) | 69 | +| [Self-Supervised Learning of Visual Features Through Embedding Images Into Text Topic Spaces](http://openaccess.thecvf.com/content_cvpr_2017/html/Gomez_Self-Supervised_Learning_of_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lluisgomez/TextTopicNet) | 69 | +| [Deep Subspace Clustering Networks](http://papers.nips.cc/paper/6608-deep-subspace-clustering-networks.pdf) | NIPS | [code](https://github.com/panji1990/Deep-subspace-clustering-networks) | 68 | +| [Escape From Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models](http://openaccess.thecvf.com/content_iccv_2017/html/Klokov_Escape_From_Cells_ICCV_2017_paper.html) | ICCV | [code](https://github.com/fxia22/kdnet.pytorch) | 68 | +| [A Distributional Perspective on Reinforcement Learning](http://proceedings.mlr.press/v70/bellemare17a.html) | ICML | [code](https://github.com/Silvicek/distributional-dqn) | 68 | +| [Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Physically-Based_Rendering_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yindaz/pbrs) | 67 | +| [Deep Transfer Learning with Joint Adaptation Networks](http://proceedings.mlr.press/v70/long17a.html) | ICML | [code](https://github.com/USTCPCS/CVPR2018_attention) | 67 | +| [Training Deep Networks without Learning Rates Through Coin Betting](http://papers.nips.cc/paper/6811-training-deep-networks-without-learning-rates-through-coin-betting.pdf) | NIPS | [code](https://github.com/bremen79/cocob) | 66 | +| [Full Resolution Image Compression With Recurrent Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Toderici_Full_Resolution_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/1zb/pytorch-image-comp-rnn) | 66 | +| [SurfaceNet: An End-To-End 3D Neural Network for Multiview Stereopsis](http://openaccess.thecvf.com/content_iccv_2017/html/Ji_SurfaceNet_An_End-To-End_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mjiUST/SurfaceNet) | 66 | +| [Doubly Stochastic Variational Inference for Deep Gaussian Processes](http://papers.nips.cc/paper/7045-doubly-stochastic-variational-inference-for-deep-gaussian-processes.pdf) | NIPS | [code](https://github.com/ICL-SML/Doubly-Stochastic-DGP) | 66 | +| [TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals](http://openaccess.thecvf.com/content_iccv_2017/html/Gao_TURN_TAP_Temporal_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jiyanggao/TURN-TAP) | 66 | +| [Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-Identification](http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Jointly_Attentive_Spatial-Temporal_ICCV_2017_paper.html) | ICCV | [code](https://github.com/shuangjiexu/Spatial-Temporal-Pooling-Networks-ReID) | 65 | +| [Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes With Deep Generative Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Soltani_Synthesizing_3D_Shapes_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Amir-Arsalan/Synthesize3DviaDepthOrSil) | 65 | +| [Dance Dance Convolution](http://proceedings.mlr.press/v70/donahue17a.html) | ICML | [code](https://github.com/chrisdonahue/ddc) | 65 | +| [Borrowing Treasures From the Wealthy: Deep Transfer Learning Through Selective Joint Fine-Tuning](http://openaccess.thecvf.com/content_cvpr_2017/html/Ge_Borrowing_Treasures_From_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ZYYSzj/Selective-Joint-Fine-tuning) | 64 | +| [Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes](http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Curriculum_Domain_Adaptation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/YangZhang4065/AdaptationSeg) | 64 | +| [Toward Controlled Generation of Text](http://proceedings.mlr.press/v70/hu17e.html) | ICML | [code](https://github.com/GBLin5566/toward-controlled-generation-of-text-pytorch) | 63 | +| [Person Re-Identification in the Wild](http://openaccess.thecvf.com/content_cvpr_2017/html/Zheng_Person_Re-Identification_in_CVPR_2017_paper.html) | CVPR | [code](https://github.com/liangzheng06/PRW-baseline) | 63 | +| [ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching](http://papers.nips.cc/paper/7133-alice-towards-understanding-adversarial-learning-for-joint-distribution-matching.pdf) | NIPS | [code](https://github.com/ChunyuanLI/ALICE) | 63 | +| [Differentiable Learning of Logical Rules for Knowledge Base Reasoning](http://papers.nips.cc/paper/6826-differentiable-learning-of-logical-rules-for-knowledge-base-reasoning.pdf) | NIPS | [code](https://github.com/fanyangxyz/Neural-LP) | 62 | +| [Person Search With Natural Language Description](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Person_Search_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ShuangLI59/Person-Search-with-Natural-Language-Description) | 61 | +| [Multi-Channel Weighted Nuclear Norm Minimization for Real Color Image Denoising](http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Multi-Channel_Weighted_Nuclear_ICCV_2017_paper.html) | ICCV | [code](https://github.com/csjunxu/MCWNNM-ICCV2017) | 61 | +| [Playing for Benchmarks](http://openaccess.thecvf.com/content_iccv_2017/html/Richter_Playing_for_Benchmarks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/PatrykChrabaszcz/Canonical_ES_Atari) | 61 | +| [Unsupervised Learning by Predicting Noise](http://proceedings.mlr.press/v70/bojanowski17a.html) | ICML | [code](https://github.com/facebookresearch/noise-as-targets) | 60 | +| [Localizing Moments in Video With Natural Language](http://openaccess.thecvf.com/content_iccv_2017/html/Hendricks_Localizing_Moments_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/LisaAnne/LocalizingMoments) | 60 | +| [End-To-End 3D Face Reconstruction With Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Dou_End-To-End_3D_Face_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ShownX/mxnet-E2FAR) | 60 | +| [CoupleNet: Coupling Global Structure With Local Parts for Object Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_CoupleNet_Coupling_Global_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tshizys/CoupleNet) | 59 | +| [AdaGAN: Boosting Generative Models](http://papers.nips.cc/paper/7126-adagan-boosting-generative-models.pdf) | NIPS | [code](https://github.com/tolstikhin/adagan) | 59 | +| [Convolutional Gaussian Processes](http://papers.nips.cc/paper/6877-convolutional-gaussian-processes.pdf) | NIPS | [code](https://github.com/markvdw/convgp/) | 57 | +| [A Deep Regression Architecture With Two-Stage Re-Initialization for High Performance Facial Landmark Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Lv_A_Deep_Regression_CVPR_2017_paper.html) | CVPR | [code](https://github.com/shaoxiaohu/Face_Alignment_Two_Stage_Re-initialization) | 57 | +| [Modeling Relationships in Referential Expressions With Compositional Modular Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Modeling_Relationships_in_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ronghanghu/cmn) | 57 | +| [Curiosity-driven Exploration by Self-supervised Prediction](http://proceedings.mlr.press/v70/pathak17a.html) | ICML | [code](https://github.com/kimhc6028/pytorch-noreward-rl) | 56 | +| [Wavelet-SRNet: A Wavelet-Based CNN for Multi-Scale Face Super Resolution](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Wavelet-SRNet_A_Wavelet-Based_ICCV_2017_paper.html) | ICCV | [code](https://github.com/hhb072/WaveletSRNet) | 56 | +| [The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process](http://papers.nips.cc/paper/7252-the-neural-hawkes-process-a-neurally-self-modulating-multivariate-point-process.pdf) | NIPS | [code](https://github.com/HMEIatJHU/neurawkes) | 56 | +| [Online and Linear-Time Attention by Enforcing Monotonic Alignments](http://proceedings.mlr.press/v70/raffel17a.html) | ICML | [code](https://github.com/craffel/mad) | 56 | +| [Neural Expectation Maximization](http://papers.nips.cc/paper/7246-neural-expectation-maximization.pdf) | NIPS | [code](https://github.com/sjoerdvansteenkiste/Neural-EM) | 56 | +| [Dense-Captioning Events in Videos](http://openaccess.thecvf.com/content_iccv_2017/html/Krishna_Dense-Captioning_Events_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ranjaykrishna/densevid_eval) | 55 | +| [Factorized Bilinear Models for Image Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Li_Factorized_Bilinear_Models_ICCV_2017_paper.html) | ICCV | [code](https://github.com/lyttonhao/Factorized-Bilinear-Network) | 55 | +| [Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee](http://papers.nips.cc/paper/6910-net-trim-convex-pruning-of-deep-neural-networks-with-performance-guarantee.pdf) | NIPS | [code](https://github.com/DNNToolBox/Net-Trim-v1) | 54 | +| [On-the-fly Operation Batching in Dynamic Computation Graphs](http://papers.nips.cc/paper/6986-on-the-fly-operation-batching-in-dynamic-computation-graphs.pdf) | NIPS | [code](https://github.com/neulab/dynet-benchmark) | 54 | +| [Visual Translation Embedding Network for Visual Relation Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Visual_Translation_Embedding_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zawlin/cvpr17_vtranse) | 54 | +| [Learning Blind Motion Deblurring](http://openaccess.thecvf.com/content_iccv_2017/html/Wieschollek_Learning_Blind_Motion_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cgtuebingen/learning-blind-motion-deblurring) | 54 | +| [A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning](http://papers.nips.cc/paper/6951-a-disentangled-recognition-and-nonlinear-dynamics-model-for-unsupervised-learning.pdf) | NIPS | [code](https://github.com/simonkamronn/kvae) | 53 | +| [Towards Diverse and Natural Image Descriptions via a Conditional GAN](http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Towards_Diverse_and_ICCV_2017_paper.html) | ICCV | [code](https://github.com/doubledaibo/gancaption_iccv2017) | 53 | +| [CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Shou_CDC_Convolutional-De-Convolutional_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ColumbiaDVMM/CDC) | 53 | +| [A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing](http://openaccess.thecvf.com/content_iccv_2017/html/Fan_A_Generic_Deep_ICCV_2017_paper.html) | ICCV | [code](https://github.com/fqnchina/CEILNet) | 52 | +| [Deep IV: A Flexible Approach for Counterfactual Prediction](http://proceedings.mlr.press/v70/hartford17a.html) | ICML | [code](https://github.com/jhartford/DeepIV) | 52 | +| [Triangle Generative Adversarial Networks](http://papers.nips.cc/paper/7109-triangle-generative-adversarial-networks.pdf) | NIPS | [code](https://github.com/LiqunChen0606/Triangle-GAN) | 51 | +| [EAST: An Efficient and Accurate Scene Text Detector](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_EAST_An_Efficient_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Kathrine94/EAST) | 51 | +| [SST: Single-Stream Temporal Action Proposals](http://openaccess.thecvf.com/content_cvpr_2017/html/Buch_SST_Single-Stream_Temporal_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ranjaykrishna/SST) | 51 | +| [Predicting Deeper Into the Future of Semantic Segmentation](http://openaccess.thecvf.com/content_iccv_2017/html/Luc_Predicting_Deeper_Into_ICCV_2017_paper.html) | ICCV | [code](https://github.com/facebookresearch/SegmPred) | 51 | +| [L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space](http://openaccess.thecvf.com/content_cvpr_2017/html/Tian_L2-Net_Deep_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yuruntian/L2-Net) | 51 | +| [TALL: Temporal Activity Localization via Language Query](http://openaccess.thecvf.com/content_iccv_2017/html/Gao_TALL_Temporal_Activity_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jiyanggao/TALL) | 50 | +| [Hybrid Reward Architecture for Reinforcement Learning](http://papers.nips.cc/paper/7123-hybrid-reward-architecture-for-reinforcement-learning.pdf) | NIPS | [code](https://github.com/Maluuba/hra) | 50 | +| [Fast Fourier Color Constancy](http://openaccess.thecvf.com/content_cvpr_2017/html/Barron_Fast_Fourier_Color_CVPR_2017_paper.html) | CVPR | [code](https://github.com/google/ffcc) | 49 | +| [Modulating early visual processing by language](http://papers.nips.cc/paper/7237-modulating-early-visual-processing-by-language.pdf) | NIPS | [code](https://github.com/GuessWhatGame/guesswhat) | 49 | +| [Adversarial Examples for Semantic Segmentation and Object Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Xie_Adversarial_Examples_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cihangxie/DAG) | 49 | +| [Learning Discrete Representations via Information Maximizing Self-Augmented Training](http://proceedings.mlr.press/v70/hu17b.html) | ICML | [code](https://github.com/weihua916/imsat) | 49 | +| [Efficient Diffusion on Region Manifolds: Recovering Small Objects With Compact CNN Representations](http://openaccess.thecvf.com/content_cvpr_2017/html/Iscen_Efficient_Diffusion_on_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ahmetius/diffusion-retrieval) | 48 | +| [Real Time Image Saliency for Black Box Classifiers](http://papers.nips.cc/paper/7272-real-time-image-saliency-for-black-box-classifiers.pdf) | NIPS | [code](https://github.com/PiotrDabkowski/pytorch-saliency) | 48 | +| [FC4: Fully Convolutional Color Constancy With Confidence-Weighted Pooling](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_FC4_Fully_Convolutional_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yuanming-hu/fc4) | 47 | +| [Multiple People Tracking by Lifted Multicut and Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2017/html/Tang_Multiple_People_Tracking_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jutanke/cabbage) | 47 | +| [Learned D-AMP: Principled Neural Network based Compressive Image Recovery](http://papers.nips.cc/paper/6774-learned-d-amp-principled-neural-network-based-compressive-image-recovery.pdf) | NIPS | [code](https://github.com/ricedsp/D-AMP_Toolbox) | 47 | +| [GP CaKe: Effective brain connectivity with causal kernels](http://papers.nips.cc/paper/6696-gp-cake-effective-brain-connectivity-with-causal-kernels.pdf) | NIPS | [code](https://github.com/LucaAmbrogioni/GP-CaKe-project) | 46 | +| [Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network](http://papers.nips.cc/paper/6854-predicting-organic-reaction-outcomes-with-weisfeiler-lehman-network.pdf) | NIPS | [code](https://github.com/wengong-jin/nips17-rexgen) | 46 | +| [Semantic Video CNNs Through Representation Warping](http://openaccess.thecvf.com/content_iccv_2017/html/Gadde_Semantic_Video_CNNs_ICCV_2017_paper.html) | ICCV | [code](https://github.com/raghudeep/netwarp_public) | 46 | +| [Grammar Variational Autoencoder](http://proceedings.mlr.press/v70/kusner17a.html) | ICML | [code](https://github.com/episodeyang/grammar_variational_autoencoder) | 46 | +| [EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis](http://openaccess.thecvf.com/content_iccv_2017/html/Sajjadi_EnhanceNet_Single_Image_ICCV_2017_paper.html) | ICCV | [code](https://github.com/msmsajjadi/EnhanceNet-Code) | 46 | +| [Safe Model-based Reinforcement Learning with Stability Guarantees](http://papers.nips.cc/paper/6692-safe-model-based-reinforcement-learning-with-stability-guarantees.pdf) | NIPS | [code](https://github.com/befelix/safe_learning) | 45 | +| [Deep Spectral Clustering Learning](http://proceedings.mlr.press/v70/law17a.html) | ICML | [code](https://github.com/wlwkgus/DeepSpectralClustering) | 45 | +| [Semantic Compositional Networks for Visual Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Gan_Semantic_Compositional_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zhegan27/Semantic_Compositional_Nets) | 45 | +| [On-Demand Learning for Deep Image Restoration](http://openaccess.thecvf.com/content_iccv_2017/html/Gao_On-Demand_Learning_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/rhgao/on-demand-learning) | 45 | +| [Video Pixel Networks](http://proceedings.mlr.press/v70/kalchbrenner17a.html) | ICML | [code](https://github.com/3ammor/Video-Pixel-Networks) | 45 | +| [Stabilizing Training of Generative Adversarial Networks through Regularization](http://papers.nips.cc/paper/6797-stabilizing-training-of-generative-adversarial-networks-through-regularization.pdf) | NIPS | [code](https://github.com/rothk/Stabilizing_GANs) | 45 | +| [Structured Bayesian Pruning via Log-Normal Multiplicative Noise](http://papers.nips.cc/paper/7254-structured-bayesian-pruning-via-log-normal-multiplicative-noise.pdf) | NIPS | [code](https://github.com/necludov/group-sparsity-sbp) | 44 | +| [Deriving Neural Architectures from Sequence and Graph Kernels](http://proceedings.mlr.press/v70/lei17a.html) | ICML | [code](https://github.com/taolei87/icml17_knn) | 44 | +| [Masked Autoregressive Flow for Density Estimation](http://papers.nips.cc/paper/6828-masked-autoregressive-flow-for-density-estimation.pdf) | NIPS | [code](https://github.com/gpapamak/maf) | 44 | +| [Unsupervised Adaptation for Deep Stereo](http://openaccess.thecvf.com/content_iccv_2017/html/Tonioni_Unsupervised_Adaptation_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/CVLAB-Unibo/Unsupervised-Adaptation-for-Deep-Stereo) | 44 | +| [Learning Residual Images for Face Attribute Manipulation](http://openaccess.thecvf.com/content_cvpr_2017/html/Shen_Learning_Residual_Images_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Zhongdao/FaceAttributeManipulation) | 43 | +| [Learning to Generate Long-term Future via Hierarchical Prediction](http://proceedings.mlr.press/v70/villegas17a.html) | ICML | [code](https://github.com/rubenvillegas/icml2017hierchvid) | 43 | +| [Accurate Optical Flow via Direct Cost Volume Processing](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Accurate_Optical_Flow_CVPR_2017_paper.html) | CVPR | [code](https://github.com/IntelVCL/dcflow) | 42 | +| [Generalized Orderless Pooling Performs Implicit Salient Matching](http://openaccess.thecvf.com/content_iccv_2017/html/Simon_Generalized_Orderless_Pooling_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cvjena/alpha_pooling) | 42 | +| [Comparative Evaluation of Hand-Crafted and Learned Local Features](http://openaccess.thecvf.com/content_cvpr_2017/html/Schonberger_Comparative_Evaluation_of_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ahojnnes/local-feature-evaluation) | 42 | +| [SchNet: A continuous-filter convolutional neural network for modeling quantum interactions](http://papers.nips.cc/paper/6700-schnet-a-continuous-filter-convolutional-neural-network-for-modeling-quantum-interactions.pdf) | NIPS | [code](https://github.com/atomistic-machine-learning/SchNet) | 41 | +| [Temporal Generative Adversarial Nets With Singular Value Clipping](http://openaccess.thecvf.com/content_iccv_2017/html/Saito_Temporal_Generative_Adversarial_ICCV_2017_paper.html) | ICCV | [code](https://github.com/pfnet-research/tgan) | 41 | +| [Multiplicative Normalizing Flows for Variational Bayesian Neural Networks](http://proceedings.mlr.press/v70/louizos17a.html) | ICML | [code](https://github.com/AMLab-Amsterdam/MNF_VBNN) | 41 | +| [Neural Scene De-Rendering](http://openaccess.thecvf.com/content_cvpr_2017/html/Wu_Neural_Scene_De-Rendering_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jiajunwu/nsd) | 40 | +| [Semantic Image Inpainting With Deep Generative Models](http://openaccess.thecvf.com/content_cvpr_2017/html/Yeh_Semantic_Image_Inpainting_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ChengBinJin/semantic-image-inpainting) | 40 | +| [A Linear-Time Kernel Goodness-of-Fit Test](http://papers.nips.cc/paper/6630-a-linear-time-kernel-goodness-of-fit-test.pdf) | NIPS | [code](https://github.com/wittawatj/kernel-gof) | 40 | +| [Least Squares Generative Adversarial Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Mao_Least_Squares_Generative_ICCV_2017_paper.html) | ICCV | [code](https://github.com/GunhoChoi/LSGAN-TF) | 39 | +| [Diversified Texture Synthesis With Feed-Forward Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Diversified_Texture_Synthesis_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Yijunmaverick/MultiTextureSynthesis) | 39 | +| [No Fuss Distance Metric Learning Using Proxies](http://openaccess.thecvf.com/content_iccv_2017/html/Movshovitz-Attias_No_Fuss_Distance_ICCV_2017_paper.html) | ICCV | [code](https://github.com/dichotomies/proxy-nca) | 38 | +| [Template Matching With Deformable Diversity Similarity](http://openaccess.thecvf.com/content_cvpr_2017/html/Talmi_Template_Matching_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/roimehrez/DDIS) | 38 | +| [What's in a Question: Using Visual Questions as a Form of Supervision](http://openaccess.thecvf.com/content_cvpr_2017/html/Ganju_Whats_in_a_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sidgan/whats_in_a_question) | 38 | +| [Face Normals "In-The-Wild" Using Fully Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Trigeorgis_Face_Normals_In-The-Wild_CVPR_2017_paper.html) | CVPR | [code](https://github.com/trigeorgis/face_normals_cvpr17) | 38 | +| [Conditional Image Synthesis with Auxiliary Classifier GANs](http://proceedings.mlr.press/v70/odena17a.html) | ICML | [code](https://github.com/kimhc6028/acgan-pytorch) | 37 | +| [Neural Episodic Control](http://proceedings.mlr.press/v70/pritzel17a.html) | ICML | [code](https://github.com/EndingCredits/Neural-Episodic-Control) | 37 | +| [3D-PRNN: Generating Shape Primitives With Recurrent Neural Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Zou_3D-PRNN_Generating_Shape_ICCV_2017_paper.html) | ICCV | [code](https://github.com/zouchuhang/3D-PRNN) | 37 | +| [Structured Embedding Models for Grouped Data](http://papers.nips.cc/paper/6629-structured-embedding-models-for-grouped-data.pdf) | NIPS | [code](https://github.com/mariru/structured_embeddings) | 36 | +| [Learning Active Learning from Data](http://papers.nips.cc/paper/7010-learning-active-learning-from-data.pdf) | NIPS | [code](https://github.com/ksenia-konyushkova/LAL) | 36 | +| [Unified Deep Supervised Domain Adaptation and Generalization](http://openaccess.thecvf.com/content_iccv_2017/html/Motiian_Unified_Deep_Supervised_ICCV_2017_paper.html) | ICCV | [code](https://github.com/samotiian/CCSA) | 35 | +| [Transformation-Grounded Image Generation Network for Novel 3D View Synthesis](http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Transformation-Grounded_Image_Generation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/silverbottlep/tvsn) | 35 | +| [Structured Attentions for Visual Question Answering](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Structured_Attentions_for_ICCV_2017_paper.html) | ICCV | [code](https://github.com/shtechair/vqa-sva) | 34 | +| [Geometric Loss Functions for Camera Pose Regression With Deep Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Kendall_Geometric_Loss_Functions_CVPR_2017_paper.html) | CVPR | [code](https://github.com/futurely/deep-camera-relocalization) | 34 | +| [VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization](http://openaccess.thecvf.com/content_cvpr_2017/html/Clark_VidLoc_A_Deep_CVPR_2017_paper.html) | CVPR | [code](https://github.com/futurely/deep-camera-relocalization) | 34 | +| [QMDP-Net: Deep Learning for Planning under Partial Observability](http://papers.nips.cc/paper/7055-qmdp-net-deep-learning-for-planning-under-partial-observability.pdf) | NIPS | [code](https://github.com/AdaCompNUS/qmdp-net) | 34 | +| [Using Ranking-CNN for Age Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Using_Ranking-CNN_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/RankingCNN/Using-Ranking-CNN-for-Age-Estimation) | 33 | +| [Hierarchical Boundary-Aware Neural Encoder for Video Captioning](http://openaccess.thecvf.com/content_cvpr_2017/html/Baraldi_Hierarchical_Boundary-Aware_Neural_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Yugnaynehc/banet) | 33 | +| [Unsupervised Learning of Disentangled Representations from Video](http://papers.nips.cc/paper/7028-unsupervised-learning-of-disentangled-representations-from-video.pdf) | NIPS | [code](https://github.com/edenton/drnet-py) | 32 | +| [Deep Learning on Lie Groups for Skeleton-Based Action Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Deep_Learning_on_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zzhiwu/LieNet) | 32 | +| [Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Liang_Deep_Variation-Structured_Reinforcement_CVPR_2017_paper.html) | CVPR | [code](https://github.com/nexusapoorvacus/DeepVariationStructuredRL) | 32 | +| [3D Point Cloud Registration for Localization Using a Deep Neural Network Auto-Encoder](http://openaccess.thecvf.com/content_cvpr_2017/html/Elbaz_3D_Point_Cloud_CVPR_2017_paper.html) | CVPR | [code](https://github.com/gilbaz/LORAX) | 32 | +| [StyleNet: Generating Attractive Visual Captions With Styles](http://openaccess.thecvf.com/content_cvpr_2017/html/Gan_StyleNet_Generating_Attractive_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kacky24/stylenet) | 32 | +| [Dynamic Word Embeddings](http://proceedings.mlr.press/v70/bamler17a.html) | ICML | [code](https://github.com/YingyuLiang/SemanticVector) | 32 | +| [Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon](http://papers.nips.cc/paper/7071-learning-to-prune-deep-neural-networks-via-layer-wise-optimal-brain-surgeon.pdf) | NIPS | [code](https://github.com/csyhhu/L-OBS) | 31 | +| [Continual Learning Through Synaptic Intelligence](http://proceedings.mlr.press/v70/zenke17a.html) | ICML | [code](https://github.com/ganguli-lab/pathint) | 31 | +| [Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes](http://openaccess.thecvf.com/content_cvpr_2017/html/Pohlen_Full-Resolution_Residual_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hiwonjoon/tf-frrn) | 31 | +| [Learning Detection With Diverse Proposals](http://openaccess.thecvf.com/content_cvpr_2017/html/Azadi_Learning_Detection_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/azadis/LDDP) | 31 | +| [LCNN: Lookup-Based Convolutional Neural Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Bagherinezhad_LCNN_Lookup-Based_Convolutional_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hessamb/lcnn) | 31 | +| [Towards Accurate Multi-Person Pose Estimation in the Wild](http://openaccess.thecvf.com/content_cvpr_2017/html/Papandreou_Towards_Accurate_Multi-Person_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hackiey/keypoints) | 30 | +| [Real-Time Neural Style Transfer for Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Real-Time_Neural_Style_CVPR_2017_paper.html) | CVPR | [code](https://github.com/curaai00/RT-StyleTransfer-forVideo) | 30 | +| [Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training](http://openaccess.thecvf.com/content_iccv_2017/html/Shetty_Speaking_the_Same_ICCV_2017_paper.html) | ICCV | [code](https://github.com/rakshithShetty/captionGAN) | 30 | +| [Deep Co-Occurrence Feature Learning for Visual Object Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Shih_Deep_Co-Occurrence_Feature_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yafangshih/Deep-COOC) | 29 | +| [Joint distribution optimal transportation for domain adaptation](http://papers.nips.cc/paper/6963-joint-distribution-optimal-transportation-for-domain-adaptation.pdf) | NIPS | [code](https://github.com/rflamary/JDOT) | 29 | +| [Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields](http://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Realtime_Multi-Person_2D_CVPR_2017_paper.html) | CVPR | [code](https://github.com/PoseAIChallenger/mxnet_pose_for_AI_challenger) | 29 | +| [SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization](http://proceedings.mlr.press/v70/kim17b.html) | ICML | [code](https://github.com/dalgu90/splitnet-wrn) | 29 | +| [The Statistical Recurrent Unit](http://proceedings.mlr.press/v70/oliva17a.html) | ICML | [code](https://github.com/DLHacks/SRU) | 29 | +| [A Unified Approach of Multi-Scale Deep and Hand-Crafted Features for Defocus Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Park_A_Unified_Approach_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zzangjinsun/DHDE_CVPR17) | 28 | +| [Learning Spread-Out Local Feature Descriptors](http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Learning_Spread-Out_Local_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ColumbiaDVMM/Spread-out_Local_Feature_Descriptor) | 28 | +| [Event-Based Visual Inertial Odometry](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Event-Based_Visual_Inertial_CVPR_2017_paper.html) | CVPR | [code](https://github.com/daniilidis-group/event_feature_tracking) | 27 | +| [DropoutNet: Addressing Cold Start in Recommender Systems](http://papers.nips.cc/paper/7081-dropoutnet-addressing-cold-start-in-recommender-systems.pdf) | NIPS | [code](https://github.com/layer6ai-labs/DropoutNet) | 27 | +| [Phrase Localization and Visual Relationship Detection With Comprehensive Image-Language Cues](http://openaccess.thecvf.com/content_iccv_2017/html/Plummer_Phrase_Localization_and_ICCV_2017_paper.html) | ICCV | [code](https://github.com/BryanPlummer/pl-clc) | 27 | +| [Harvesting Multiple Views for Marker-Less 3D Human Pose Annotations](http://openaccess.thecvf.com/content_cvpr_2017/html/Pavlakos_Harvesting_Multiple_Views_CVPR_2017_paper.html) | CVPR | [code](https://github.com/geopavlakos/harvesting) | 27 | +| [Deep 360 Pilot: Learning a Deep Agent for Piloting Through 360deg Sports Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Deep_360_Pilot_CVPR_2017_paper.html) | CVPR | [code](https://github.com/eborboihuc/Deep360Pilot-CVPR17) | 27 | +| [Neural Message Passing for Quantum Chemistry](http://proceedings.mlr.press/v70/gilmer17a.html) | ICML | [code](https://github.com/brain-research/mpnn) | 27 | +| [State-Frequency Memory Recurrent Neural Networks](http://proceedings.mlr.press/v70/hu17c.html) | ICML | [code](https://github.com/hhkunming/State-Frequency-Memory-Recurrent-Neural-Networks) | 27 | +| [DeepCD: Learning Deep Complementary Descriptors for Patch Representations](http://openaccess.thecvf.com/content_iccv_2017/html/Yang_DeepCD_Learning_Deep_ICCV_2017_paper.html) | ICCV | [code](https://github.com/shamangary/DeepCD) | 26 | +| [Contrastive Learning for Image Captioning](http://papers.nips.cc/paper/6691-contrastive-learning-for-image-captioning.pdf) | NIPS | [code](https://github.com/doubledaibo/clcaption_nips2017) | 26 | +| [Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure](http://papers.nips.cc/paper/6760-stochastic-optimization-with-variance-reduction-for-infinite-datasets-with-finite-sum-structure.pdf) | NIPS | [code](https://github.com/albietz/stochs) | 26 | +| [Learning High Dynamic Range From Outdoor Panoramas](http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Learning_High_Dynamic_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jacenfox/ldr2hdr-public) | 26 | +| [Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors](http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_SpeedAccuracy_Trade-Offs_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/rayanelleuch/Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors) | 26 | +| [Learning to Detect Salient Objects With Image-Level Supervision](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Learning_to_Detect_CVPR_2017_paper.html) | CVPR | [code](https://github.com/scott89/WSS) | 26 | +| [Improved Variational Autoencoders for Text Modeling using Dilated Convolutions](http://proceedings.mlr.press/v70/yang17d.html) | ICML | [code](https://github.com/ryokamoi/dcnn_textvae) | 26 | +| [Interspecies Knowledge Transfer for Facial Keypoint Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Rashid_Interspecies_Knowledge_Transfer_CVPR_2017_paper.html) | CVPR | [code](https://github.com/menorashid/animal_human_kp) | 25 | +| [YASS: Yet Another Spike Sorter](http://papers.nips.cc/paper/6989-yass-yet-another-spike-sorter.pdf) | NIPS | [code](https://github.com/paninski-lab/yass) | 25 | +| [Open Set Domain Adaptation](http://openaccess.thecvf.com/content_iccv_2017/html/Busto_Open_Set_Domain_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Heliot7/open-set-da) | 25 | +| [Domain-Adaptive Deep Network Compression](http://openaccess.thecvf.com/content_iccv_2017/html/Masana_Domain-Adaptive_Deep_Network_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mmasana/DALR) | 24 | +| [Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization](http://openaccess.thecvf.com/content_iccv_2017/html/Coskun_Long_Short-Term_Memory_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Seleucia/lstmkf_ICCV2017) | 24 | +| [Temporal Context Network for Activity Localization in Videos](http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Temporal_Context_Network_ICCV_2017_paper.html) | ICCV | [code](https://github.com/vdavid70619/TCN) | 24 | +| [Incremental Learning of Object Detectors Without Catastrophic Forgetting](http://openaccess.thecvf.com/content_iccv_2017/html/Shmelkov_Incremental_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/kshmelkov/incremental_detectors) | 24 | +| [Dense Captioning With Joint Inference and Visual Context](http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Dense_Captioning_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/linjieyangsc/densecap) | 24 | +| [Universal Adversarial Perturbations](http://openaccess.thecvf.com/content_cvpr_2017/html/Moosavi-Dezfooli_Universal_Adversarial_Perturbations_CVPR_2017_paper.html) | CVPR | [code](https://github.com/val-iisc/fast-feature-fool) | 24 | +| [Asymmetric Tri-training for Unsupervised Domain Adaptation](http://proceedings.mlr.press/v70/saito17a.html) | ICML | [code](https://github.com/vtddggg/ATDA) | 24 | +| [Reducing Reparameterization Gradient Variance](http://papers.nips.cc/paper/6961-reducing-reparameterization-gradient-variance.pdf) | NIPS | [code](https://github.com/andymiller/ReducedVarianceReparamGradients) | 24 | +| [Exploiting Saliency for Object Segmentation From Image Level Labels](http://openaccess.thecvf.com/content_cvpr_2017/html/Oh_Exploiting_Saliency_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/coallaoh/GuidedLabelling) | 24 | +| [A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering](http://papers.nips.cc/paper/6734-a-dirichlet-mixture-model-of-hawkes-processes-for-event-sequence-clustering.pdf) | NIPS | [code](https://github.com/HongtengXu/Hawkes-Process-Toolkit) | 24 | +| [Shading Annotations in the Wild](http://openaccess.thecvf.com/content_cvpr_2017/html/Kovacs_Shading_Annotations_in_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kovibalu/saw_release) | 24 | +| [Straight to Shapes: Real-Time Detection of Encoded Shapes](http://openaccess.thecvf.com/content_cvpr_2017/html/Jetley_Straight_to_Shapes_CVPR_2017_paper.html) | CVPR | [code](https://github.com/torrvision/straighttoshapes) | 23 | +| [Dual Discriminator Generative Adversarial Nets](http://papers.nips.cc/paper/6860-dual-discriminator-generative-adversarial-nets.pdf) | NIPS | [code](https://github.com/tund/D2GAN) | 23 | +| [Zero-Order Reverse Filtering](http://openaccess.thecvf.com/content_iccv_2017/html/Tao_Zero-Order_Reverse_Filtering_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jiangsutx/DeFilter) | 23 | +| [Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net](http://papers.nips.cc/paper/7026-variational-walkback-learning-a-transition-operator-as-a-stochastic-recurrent-net.pdf) | NIPS | [code](https://github.com/anirudh9119/walkback_nips17) | 23 | +| [Learning Spherical Convolution for Fast Features from 360° Imagery](http://papers.nips.cc/paper/6656-learning-spherical-convolution-for-fast-features-from-360-imagery.pdf) | NIPS | [code](https://github.com/sammy-su/Spherical-Convolution) | 22 | +| [Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier](http://proceedings.mlr.press/v70/futoma17a.html) | ICML | [code](https://github.com/jfutoma/MGP-RNN) | 22 | +| [Deep Cross-Modal Hashing](http://openaccess.thecvf.com/content_cvpr_2017/html/Jiang_Deep_Cross-Modal_Hashing_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jiangqy/DCMH-CVPR2017) | 22 | +| [When Unsupervised Domain Adaptation Meets Tensor Representations](http://openaccess.thecvf.com/content_iccv_2017/html/Lu_When_Unsupervised_Domain_ICCV_2017_paper.html) | ICCV | [code](https://github.com/poppinace/TAISL) | 22 | +| [Image Super-Resolution Using Dense Skip Connections](http://openaccess.thecvf.com/content_iccv_2017/html/Tong_Image_Super-Resolution_Using_ICCV_2017_paper.html) | ICCV | [code](https://github.com/kweisamx/TensorFlow-SR-DenseNet) | 22 | +| [Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Multimodal_Transfer_A_CVPR_2017_paper.html) | CVPR | [code](https://github.com/fullfanta/multimodal_transfer) | 22 | +| [STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling](http://openaccess.thecvf.com/content_cvpr_2017/html/He_STD2P_RGBD_Semantic_CVPR_2017_paper.html) | CVPR | [code](https://github.com/SSAW14/STD2P) | 22 | +| [Learning Continuous Semantic Representations of Symbolic Expressions](http://proceedings.mlr.press/v70/allamanis17a.html) | ICML | [code](https://github.com/mast-group/eqnet) | 22 | +| [Deep Growing Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Wang_Deep_Growing_Learning_ICCV_2017_paper.html) | ICCV | [code](https://github.com/QData/deep2Read) | 21 | +| [Combined Group and Exclusive Sparsity for Deep Neural Networks](http://proceedings.mlr.press/v70/yoon17a.html) | ICML | [code](https://github.com/jaehong-yoon93/CGES) | 21 | +| [Hash Embeddings for Efficient Word Representations](http://papers.nips.cc/paper/7078-hash-embeddings-for-efficient-word-representations.pdf) | NIPS | [code](https://github.com/dsv77/hashembedding/) | 21 | +| [Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM](http://papers.nips.cc/paper/6850-accuracy-first-selecting-a-differential-privacy-level-for-accuracy-constrained-erm.pdf) | NIPS | [code](https://github.com/steven7woo/Accuracy-First-Differential-Privacy) | 21 | +| [Disentangled Representation Learning GAN for Pose-Invariant Face Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Tran_Disentangled_Representation_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zhangjunh/DR-GAN-by-pytorch) | 21 | +| [Learning to Pivot with Adversarial Networks](http://papers.nips.cc/paper/6699-learning-to-pivot-with-adversarial-networks.pdf) | NIPS | [code](https://github.com/glouppe/paper-learning-to-pivot) | 21 | +| [Learning Dynamic Siamese Network for Visual Object Tracking](http://openaccess.thecvf.com/content_iccv_2017/html/Guo_Learning_Dynamic_Siamese_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tsingqguo/DSiam) | 21 | +| [POSEidon: Face-From-Depth for Driver Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Borghi_POSEidon_Face-From-Depth_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/gdubrg/POSEidon-Biwi) | 20 | +| [Deep Metric Learning via Facility Location](http://openaccess.thecvf.com/content_cvpr_2017/html/Song_Deep_Metric_Learning_CVPR_2017_paper.html) | CVPR | [code](https://github.com/CongWeilin/cluster-loss-tensorflow) | 20 | +| [Automatic Spatially-Aware Fashion Concept Discovery](http://openaccess.thecvf.com/content_iccv_2017/html/Han_Automatic_Spatially-Aware_Fashion_ICCV_2017_paper.html) | ICCV | [code](https://github.com/xthan/fashion-200k) | 20 | +| [The Numerics of GANs](http://papers.nips.cc/paper/6779-the-numerics-of-gans.pdf) | NIPS | [code](https://github.com/LMescheder/TheNumericsOfGANs) | 20 | +| [From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur](http://openaccess.thecvf.com/content_cvpr_2017/html/Gong_From_Motion_Blur_CVPR_2017_paper.html) | CVPR | [code](https://github.com/donggong1/motion-flow-syn) | 20 | +| [Unpaired Image-To-Image Translation Using Cycle-Consistent Adversarial Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Unpaired_Image-To-Image_Translation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/adepierre/Caffe_CycleGAN) | 20 | +| [Zero-Inflated Exponential Family Embeddings](http://proceedings.mlr.press/v70/liu17a.html) | ICML | [code](https://github.com/blei-lab/zero-inflated-embedding) | 20 | +| [InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations](http://papers.nips.cc/paper/6971-infogail-interpretable-imitation-learning-from-visual-demonstrations.pdf) | NIPS | [code](https://github.com/ermongroup/infogail) | 20 | +| [Weakly-Supervised Learning of Visual Relations](http://openaccess.thecvf.com/content_iccv_2017/html/Peyre_Weakly-Supervised_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jpeyre/unrel) | 20 | +| [Multi-Label Image Recognition by Recurrently Discovering Attentional Regions](http://openaccess.thecvf.com/content_iccv_2017/html/Wang_Multi-Label_Image_Recognition_ICCV_2017_paper.html) | ICCV | [code](https://github.com/James-Yip/AttentionImageClass) | 20 | +| [Scene Parsing With Global Context Embedding](http://openaccess.thecvf.com/content_iccv_2017/html/Hung_Scene_Parsing_With_ICCV_2017_paper.html) | ICCV | [code](https://github.com/hfslyc/GCPNet) | 20 | +| [Context Selection for Embedding Models](http://papers.nips.cc/paper/7067-context-selection-for-embedding-models.pdf) | NIPS | [code](https://github.com/blei-lab/context-selection-embedding) | 20 | +| [Deep Mean-Shift Priors for Image Restoration](http://papers.nips.cc/paper/6678-deep-mean-shift-priors-for-image-restoration.pdf) | NIPS | [code](https://github.com/siavashBigdeli/DMSP) | 20 | +| [Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Skeleton_Key_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/feiyu1990/Skeleton-key) | 20 | +| [Fully-Adaptive Feature Sharing in Multi-Task Networks With Applications in Person Attribute Classification](http://openaccess.thecvf.com/content_cvpr_2017/html/Lu_Fully-Adaptive_Feature_Sharing_CVPR_2017_paper.html) | CVPR | [code](https://github.com/luyongxi/deep_share) | 19 | +| [Learning Compact Geometric Features](http://openaccess.thecvf.com/content_iccv_2017/html/Khoury_Learning_Compact_Geometric_ICCV_2017_paper.html) | ICCV | [code](https://github.com/marckhoury/CGF) | 19 | +| [Structured Generative Adversarial Networks](http://papers.nips.cc/paper/6979-structured-generative-adversarial-networks.pdf) | NIPS | [code](https://github.com/thudzj/StructuredGAN) | 19 | +| [Joint Gap Detection and Inpainting of Line Drawings](http://openaccess.thecvf.com/content_cvpr_2017/html/Sasaki_Joint_Gap_Detection_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kaidlc/CVPR2017_linedrawings) | 19 | +| [Chained Multi-Stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection](http://openaccess.thecvf.com/content_iccv_2017/html/Zolfaghari_Chained_Multi-Stream_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mzolfaghari/chained-multistream-networks) | 19 | +| [Adversarial Feature Matching for Text Generation](http://proceedings.mlr.press/v70/zhang17b.html) | ICML | [code](https://github.com/Jeff-HOU/UROP-Adversarial-Feature-Matching-for-Text-Generation) | 18 | +| [BIER - Boosting Independent Embeddings Robustly](http://openaccess.thecvf.com/content_iccv_2017/html/Opitz_BIER_-_Boosting_ICCV_2017_paper.html) | ICCV | [code](https://github.com/mop/bier) | 18 | +| [Predictive-Corrective Networks for Action Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Dave_Predictive-Corrective_Networks_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/achalddave/predictive-corrective) | 18 | +| [Stochastic Generative Hashing](http://proceedings.mlr.press/v70/dai17a.html) | ICML | [code](https://github.com/doubling/Stochastic_Generative_Hashing) | 18 | +| [A Bayesian Data Augmentation Approach for Learning Deep Models](http://papers.nips.cc/paper/6872-a-bayesian-data-augmentation-approach-for-learning-deep-models.pdf) | NIPS | [code](https://github.com/toantm/keras-bda) | 18 | +| [Attentive Semantic Video Generation Using Captions](http://openaccess.thecvf.com/content_iccv_2017/html/Marwah_Attentive_Semantic_Video_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Singularity42/cap2vid) | 18 | +| [MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_MDNet_A_Semantically_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zizhaozhang/mdnet-cvpr2017) | 18 | +| [Deep Unsupervised Similarity Learning Using Partially Ordered Sets](http://openaccess.thecvf.com/content_cvpr_2017/html/Bautista_Deep_Unsupervised_Similarity_CVPR_2017_paper.html) | CVPR | [code](https://github.com/asanakoy/deep_unsupervised_posets) | 17 | +| [DualNet: Learn Complementary Features for Image Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Hou_DualNet_Learn_Complementary_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ustc-vim/dualnet) | 17 | +| [Neural system identification for large populations separating “what” and “where”](http://papers.nips.cc/paper/6942-neural-system-identification-for-large-populations-separating-what-and-where.pdf) | NIPS | [code](https://github.com/david-klindt/NIPS2017) | 17 | +| [FALKON: An Optimal Large Scale Kernel Method](http://papers.nips.cc/paper/6978-falkon-an-optimal-large-scale-kernel-method.pdf) | NIPS | [code](https://github.com/LCSL/FALKON_paper) | 17 | +| [Deep Future Gaze: Gaze Anticipation on Egocentric Videos Using Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Deep_Future_Gaze_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Mengmi/deepfuturegaze_gan) | 17 | +| [Deep Learning with Topological Signatures](http://papers.nips.cc/paper/6761-deep-learning-with-topological-signatures.pdf) | NIPS | [code](https://github.com/c-hofer/nips2017) | 17 | +| [Streaming Sparse Gaussian Process Approximations](http://papers.nips.cc/paper/6922-streaming-sparse-gaussian-process-approximations.pdf) | NIPS | [code](https://github.com/thangbui/streaming_sparse_gp) | 17 | +| [RPAN: An End-To-End Recurrent Pose-Attention Network for Action Recognition in Videos](http://openaccess.thecvf.com/content_iccv_2017/html/Du_RPAN_An_End-To-End_ICCV_2017_paper.html) | ICCV | [code](https://github.com/agethen/RPAN) | 17 | +| [Awesome Typography: Statistics-Based Text Effects Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Awesome_Typography_Statistics-Based_CVPR_2017_paper.html) | CVPR | [code](https://github.com/williamyang1991/Text-Effects-Transfer) | 17 | +| [RoomNet: End-To-End Room Layout Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Lee_RoomNet_End-To-End_Room_ICCV_2017_paper.html) | ICCV | [code](https://github.com/GitBoSun/roomnet) | 17 | +| [Deep Spatial-Semantic Attention for Fine-Grained Sketch-Based Image Retrieval](http://openaccess.thecvf.com/content_iccv_2017/html/Song_Deep_Spatial-Semantic_Attention_ICCV_2017_paper.html) | ICCV | [code](https://github.com/yuchuochuo1023/Deep_SBIR_tf) | 16 | +| [Deep Supervised Discrete Hashing](http://papers.nips.cc/paper/6842-deep-supervised-discrete-hashing.pdf) | NIPS | [code](https://github.com/liqi-casia/DSDH-HashingCode) | 16 | +| [Few-Shot Learning Through an Information Retrieval Lens](http://papers.nips.cc/paper/6820-few-shot-learning-through-an-information-retrieval-lens.pdf) | NIPS | [code](https://github.com/eleniTriantafillou/few_shot_mAP_public) | 16 | +| [Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach](http://papers.nips.cc/paper/7023-estimating-accuracy-from-unlabeled-data-a-probabilistic-logic-approach.pdf) | NIPS | [code](https://github.com/eaplatanios/makina) | 16 | +| [Learning to Push the Limits of Efficient FFT-Based Image Deconvolution](http://openaccess.thecvf.com/content_iccv_2017/html/Kruse_Learning_to_Push_ICCV_2017_paper.html) | ICCV | [code](https://github.com/uschmidt83/fourier-deconvolution-network) | 16 | +| [Federated Multi-Task Learning](http://papers.nips.cc/paper/7029-federated-multi-task-learning.pdf) | NIPS | [code](https://github.com/gingsmith/fmtl) | 16 | +| [Label Distribution Learning Forests](http://papers.nips.cc/paper/6685-label-distribution-learning-forests.pdf) | NIPS | [code](https://github.com/shenwei1231/caffe-LDLForests) | 16 | +| [Deep Multitask Architecture for Integrated 2D and 3D Human Sensing](http://openaccess.thecvf.com/content_cvpr_2017/html/Popa_Deep_Multitask_Architecture_CVPR_2017_paper.html) | CVPR | [code](https://github.com/alinionutpopa/dmhs) | 16 | +| [Estimating Mutual Information for Discrete-Continuous Mixtures](http://papers.nips.cc/paper/7180-estimating-mutual-information-for-discrete-continuous-mixtures.pdf) | NIPS | [code](https://github.com/wgao9/mixed_KSG) | 16 | +| [Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes](http://openaccess.thecvf.com/content_cvpr_2017/html/Golestaneh_Spatially-Varying_Blur_Detection_CVPR_2017_paper.html) | CVPR | [code](https://github.com/isalirezag/HiFST) | 16 | +| [StyleBank: An Explicit Representation for Neural Image Style Transfer](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_StyleBank_An_Explicit_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jxcodetw/Stylebank) | 16 | +| [Surface Normals in the Wild](http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Surface_Normals_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/umich-vl/surface_normals) | 15 | +| [Automatic Discovery of the Statistical Types of Variables in a Dataset](http://proceedings.mlr.press/v70/valera17a.html) | ICML | [code](https://github.com/ivaleraM/DataTypes) | 15 | +| [Learning Diverse Image Colorization](http://openaccess.thecvf.com/content_cvpr_2017/html/Deshpande_Learning_Diverse_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/aditya12agd5/divcolor) | 15 | +| [Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems](http://openaccess.thecvf.com/content_iccv_2017/html/Meinhardt_Learning_Proximal_Operators_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tum-vision/learn_prox_ops) | 15 | +| [Non-Local Deep Features for Salient Object Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Luo_Non-Local_Deep_Features_CVPR_2017_paper.html) | CVPR | [code](https://github.com/AceCoooool/NLFD-pytorch) | 15 | +| [Structure-Measure: A New Way to Evaluate Foreground Maps](http://openaccess.thecvf.com/content_iccv_2017/html/Fan_Structure-Measure_A_New_ICCV_2017_paper.html) | ICCV | [code](https://github.com/DengPingFan/S-measure) | 15 | +| [Shallow Updates for Deep Reinforcement Learning](http://papers.nips.cc/paper/6906-shallow-updates-for-deep-reinforcement-learning.pdf) | NIPS | [code](https://github.com/Shallow-Updates-for-Deep-RL/Shallow_Updates_for_Deep_RL) | 15 | +| [Wasserstein Generative Adversarial Networks](http://proceedings.mlr.press/v70/arjovsky17a.html) | ICML | [code](https://github.com/luslab/scRNAseq-WGAN-GP) | 15 | +| [Recurrent 3D Pose Sequence Machines](http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Recurrent_3D_Pose_CVPR_2017_paper.html) | CVPR | [code](https://github.com/MudeLin/RPSM) | 15 | +| [Variational Dropout Sparsifies Deep Neural Networks](http://proceedings.mlr.press/v70/molchanov17a.html) | ICML | [code](https://github.com/soskek/variational_dropout_sparsifies_dnn) | 15 | +| [Captioning Images With Diverse Objects](http://openaccess.thecvf.com/content_cvpr_2017/html/Venugopalan_Captioning_Images_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/vsubhashini/noc) | 15 | +| [Off-policy evaluation for slate recommendation](http://papers.nips.cc/paper/6954-off-policy-evaluation-for-slate-recommendation.pdf) | NIPS | [code](https://github.com/adith387/slates_semisynth_expts) | 15 | +| [Attributes2Classname: A Discriminative Model for Attribute-Based Unsupervised Zero-Shot Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Demirel_Attributes2Classname_A_Discriminative_ICCV_2017_paper.html) | ICCV | [code](https://github.com/berkandemirel/attributes2classname) | 14 | +| [Benchmarking Denoising Algorithms With Real Photographs](http://openaccess.thecvf.com/content_cvpr_2017/html/Plotz_Benchmarking_Denoising_Algorithms_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lbasek/image-denoising-benchmark) | 14 | +| [Neural Aggregation Network for Video Face Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Neural_Aggregation_Network_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jinyanxu/Neural-Aggregation-Network-for-Video-Face-Recognition) | 14 | +| [Learned Contextual Feature Reweighting for Image Geo-Localization](http://openaccess.thecvf.com/content_cvpr_2017/html/Kim_Learned_Contextual_Feature_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hyojinie/crn) | 14 | +| [Streaming Weak Submodularity: Interpreting Neural Networks on the Fly](http://papers.nips.cc/paper/6993-streaming-weak-submodularity-interpreting-neural-networks-on-the-fly.pdf) | NIPS | [code](https://github.com/eelenberg/streak) | 14 | +| [CVAE-GAN: Fine-Grained Image Generation Through Asymmetric Training](http://openaccess.thecvf.com/content_iccv_2017/html/Bao_CVAE-GAN_Fine-Grained_Image_ICCV_2017_paper.html) | ICCV | [code](https://github.com/yanzhicong/VAE-GAN) | 14 | +| [VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation](http://openaccess.thecvf.com/content_iccv_2017/html/Gan_VQS_Linking_Segmentations_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Cold-Winter/vqs) | 14 | +| [Spherical convolutions and their application in molecular modelling](http://papers.nips.cc/paper/6935-spherical-convolutions-and-their-application-in-molecular-modelling.pdf) | NIPS | [code](https://github.com/deepfold/NIPS2017) | 14 | +| [Multi-Information Source Optimization](http://papers.nips.cc/paper/7016-multi-information-source-optimization.pdf) | NIPS | [code](https://github.com/deepfold/NIPS2017) | 14 | +| [Convolutional Neural Network Architecture for Geometric Matching](http://openaccess.thecvf.com/content_cvpr_2017/html/Rocco_Convolutional_Neural_Network_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hjweide/convnet-for-geometric-matching) | 14 | +| [Neural Face Editing With Intrinsic Image Disentangling](http://openaccess.thecvf.com/content_cvpr_2017/html/Shu_Neural_Face_Editing_CVPR_2017_paper.html) | CVPR | [code](https://github.com/zhixinshu/NeuralFaceEditing) | 14 | +| [Realistic Dynamic Facial Textures From a Single Image Using GANs](http://openaccess.thecvf.com/content_iccv_2017/html/Olszewski_Realistic_Dynamic_Facial_ICCV_2017_paper.html) | ICCV | [code](https://github.com/leehomyc/ICCV-2017-Paper) | 14 | +| [Predictive State Recurrent Neural Networks](http://papers.nips.cc/paper/7186-predictive-state-recurrent-neural-networks.pdf) | NIPS | [code](https://github.com/cmdowney/psrnn) | 13 | +| [Deep TextSpotter: An End-To-End Trainable Scene Text Localization and Recognition Framework](http://openaccess.thecvf.com/content_iccv_2017/html/Busta_Deep_TextSpotter_An_ICCV_2017_paper.html) | ICCV | [code](https://github.com/VeitL/OCR) | 13 | +| [ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events](http://papers.nips.cc/paper/6932-extremeweather-a-large-scale-climate-dataset-for-semi-supervised-detection-localization-and-understanding-of-extreme-weather-events.pdf) | NIPS | [code](https://github.com/eracah/hur-detect) | 13 | +| [Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs](http://papers.nips.cc/paper/6614-hunt-for-the-unique-stable-sparse-and-fast-feature-learning-on-graphs.pdf) | NIPS | [code](https://github.com/vermaMachineLearning/FGSD) | 13 | +| [Consensus Convolutional Sparse Coding](http://openaccess.thecvf.com/content_iccv_2017/html/Choudhury_Consensus_Convolutional_Sparse_ICCV_2017_paper.html) | ICCV | [code](https://github.com/vccimaging/CCSC_code_ICCV2017) | 13 | +| [Weakly Supervised Affordance Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Sawatzky_Weakly_Supervised_Affordance_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ykztawas/Weakly-Supervised-Affordance-Detection) | 13 | +| [Joint Learning of Object and Action Detectors](http://openaccess.thecvf.com/content_iccv_2017/html/Kalogeiton_Joint_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/vkalogeiton/joint-object-action-learning) | 13 | +| [Light Field Blind Motion Deblurring](http://openaccess.thecvf.com/content_cvpr_2017/html/Srinivasan_Light_Field_Blind_CVPR_2017_paper.html) | CVPR | [code](https://github.com/pratulsrinivasan/Light_Field_Blind_Motion_Deblurring) | 13 | +| [Asynchronous Stochastic Gradient Descent with Delay Compensation](http://proceedings.mlr.press/v70/zheng17b.html) | ICML | [code](https://github.com/Microsoft/Delayed-Compensation-Asynchronous-Stochastic-Gradient-Descent-for-Multiverso) | 13 | +| [Unrolled Memory Inner-Products: An Abstract GPU Operator for Efficient Vision-Related Computations](http://openaccess.thecvf.com/content_iccv_2017/html/Lin_Unrolled_Memory_Inner-Products_ICCV_2017_paper.html) | ICCV | [code](https://github.com/johnjohnlin/UMI) | 12 | +| [Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification](http://papers.nips.cc/paper/7125-maximizing-subset-accuracy-with-recurrent-neural-networks-in-multi-label-classification.pdf) | NIPS | [code](https://github.com/JinseokNam/mlc2seq) | 12 | +| [Self-Organized Text Detection With Minimal Post-Processing via Border Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Wu_Self-Organized_Text_Detection_ICCV_2017_paper.html) | ICCV | [code](https://github.com/saicoco/tf-sotd) | 12 | +| [Coordinated Multi-Agent Imitation Learning](http://proceedings.mlr.press/v70/le17a.html) | ICML | [code](https://github.com/hoangminhle/MultiAgent-ImitationLearning) | 12 | +| [Gradient descent GAN optimization is locally stable](http://papers.nips.cc/paper/7142-gradient-descent-gan-optimization-is-locally-stable.pdf) | NIPS | [code](https://github.com/locuslab/gradient_regularized_gan) | 12 | +| [Removing Rain From Single Images via a Deep Detail Network](http://openaccess.thecvf.com/content_cvpr_2017/html/Fu_Removing_Rain_From_CVPR_2017_paper.html) | CVPR | [code](https://github.com/XMU-smartdsp/Removing_Rain) | 12 | +| [Convexified Convolutional Neural Networks](http://proceedings.mlr.press/v70/zhang17f.html) | ICML | [code](https://github.com/zhangyuc/CCNN) | 12 | +| [Multigrid Neural Architectures](http://openaccess.thecvf.com/content_cvpr_2017/html/Ke_Multigrid_Neural_Architectures_CVPR_2017_paper.html) | CVPR | [code](https://github.com/buttomnutstoast/Multigrid-Neural-Architectures) | 12 | +| [VegFru: A Domain-Specific Dataset for Fine-Grained Visual Categorization](http://openaccess.thecvf.com/content_iccv_2017/html/Hou_VegFru_A_Domain-Specific_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ustc-vim/vegfru) | 12 | +| [Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin](http://papers.nips.cc/paper/7255-attend-and-predict-understanding-gene-regulation-by-selective-attention-on-chromatin.pdf) | NIPS | [code](https://github.com/QData/AttentiveChrome) | 12 | +| [Differential Angular Imaging for Material Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Xue_Differential_Angular_Imaging_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jiaxue1993/DAIN) | 12 | +| [A Multilayer-Based Framework for Online Background Subtraction With Freely Moving Cameras](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_A_Multilayer-Based_Framework_ICCV_2017_paper.html) | ICCV | [code](https://github.com/EthanZhu90/MultilayerBSMC_ICCV17) | 11 | +| [Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation](http://papers.nips.cc/paper/6821-formal-guarantees-on-the-robustness-of-a-classifier-against-adversarial-manipulation.pdf) | NIPS | [code](https://github.com/max-andr/cross-lipschitz) | 11 | +| [Max-value Entropy Search for Efficient Bayesian Optimization](http://proceedings.mlr.press/v70/wang17e.html) | ICML | [code](https://github.com/zi-w/Max-value-Entropy-Search) | 11 | +| [Higher-Order Integration of Hierarchical Convolutional Activations for Fine-Grained Visual Categorization](http://openaccess.thecvf.com/content_iccv_2017/html/Cai_Higher-Order_Integration_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cssjcai/hihca) | 11 | +| [Generalized Deep Image to Image Regression](http://openaccess.thecvf.com/content_cvpr_2017/html/Santhanam_Generalized_Deep_Image_CVPR_2017_paper.html) | CVPR | [code](https://github.com/venkai/RBDN) | 11 | +| [Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective](http://openaccess.thecvf.com/content_iccv_2017/html/Oh_Adversarial_Image_Perturbation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/coallaoh/AIP) | 11 | +| [Predicting Human Activities Using Stochastic Grammar](http://openaccess.thecvf.com/content_iccv_2017/html/Qi_Predicting_Human_Activities_ICCV_2017_paper.html) | ICCV | [code](https://github.com/SiyuanQi/grammar-activity-prediction) | 11 | +| [DESIRE: Distant Future Prediction in Dynamic Scenes With Interacting Agents](http://openaccess.thecvf.com/content_cvpr_2017/html/Lee_DESIRE_Distant_Future_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yadrimz/DESIRE) | 11 | +| [Fisher GAN](http://papers.nips.cc/paper/6845-fisher-gan.pdf) | NIPS | [code](https://github.com/tomsercu/FisherGAN) | 11 | +| [High-Order Attention Models for Visual Question Answering](http://papers.nips.cc/paper/6957-high-order-attention-models-for-visual-question-answering.pdf) | NIPS | [code](https://github.com/idansc/HighOrderAtten) | 11 | +| [IM2CAD](http://openaccess.thecvf.com/content_cvpr_2017/html/Izadinia_IM2CAD_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yyong119/IM2CAD) | 11 | +| [On Fairness and Calibration](http://papers.nips.cc/paper/7151-on-fairness-and-calibration.pdf) | NIPS | [code](https://github.com/gpleiss/equalized_odds_and_calibration) | 11 | +| [DeepPermNet: Visual Permutation Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Santa_Cruz_DeepPermNet_Visual_Permutation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/rfsantacruz/deep-perm-net) | 10 | +| [f-GANs in an Information Geometric Nutshell](http://papers.nips.cc/paper/6649-f-gans-in-an-information-geometric-nutshell.pdf) | NIPS | [code](https://github.com/qulizhen/fgan_info_geometric) | 10 | +| [Revisiting IM2GPS in the Deep Learning Era](http://openaccess.thecvf.com/content_iccv_2017/html/Vo_Revisiting_IM2GPS_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/lugiavn/revisiting-im2gps) | 10 | +| [Attentional Correlation Filter Network for Adaptive Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2017/html/Choi_Attentional_Correlation_Filter_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jongwon20000/ACFN) | 10 | +| [Learning Cross-Modal Deep Representations for Robust Pedestrian Detection](http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Learning_Cross-Modal_Deep_CVPR_2017_paper.html) | CVPR | [code](https://github.com/danxuhk/CMT-CNN) | 10 | +| [Confident Multiple Choice Learning](http://proceedings.mlr.press/v70/lee17b.html) | ICML | [code](https://github.com/chhwang/cmcl) | 10 | +| [Curriculum Dropout](http://openaccess.thecvf.com/content_iccv_2017/html/Morerio_Curriculum_Dropout_ICCV_2017_paper.html) | ICCV | [code](https://github.com/pmorerio/curriculum-dropout) | 9 | +| [Cognitive Mapping and Planning for Visual Navigation](http://openaccess.thecvf.com/content_cvpr_2017/html/Gupta_Cognitive_Mapping_and_CVPR_2017_paper.html) | CVPR | [code](https://github.com/agiantwhale/cognitive-mapping-agent) | 9 | +| [Optimized Pre-Processing for Discrimination Prevention](http://papers.nips.cc/paper/6988-optimized-pre-processing-for-discrimination-prevention.pdf) | NIPS | [code](https://github.com/fair-preprocessing/nips2017) | 9 | +| [Learning Motion Patterns in Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Tokmakov_Learning_Motion_Patterns_CVPR_2017_paper.html) | CVPR | [code](https://github.com/pirahansiah/opencv) | 9 | +| [Scalable Log Determinants for Gaussian Process Kernel Learning](http://papers.nips.cc/paper/7212-scalable-log-determinants-for-gaussian-process-kernel-learning.pdf) | NIPS | [code](https://github.com/kd383/GPML_SLD) | 9 | +| [A Hierarchical Approach for Generating Descriptive Image Paragraphs](http://openaccess.thecvf.com/content_cvpr_2017/html/Krause_A_Hierarchical_Approach_CVPR_2017_paper.html) | CVPR | [code](https://github.com/InnerPeace-Wu/im2p-tensorflow) | 9 | +| [Deep Crisp Boundaries](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Deep_Crisp_Boundaries_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Wangyupei/CED) | 9 | +| [Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization](http://papers.nips.cc/paper/6611-breaking-the-nonsmooth-barrier-a-scalable-parallel-method-for-composite-optimization.pdf) | NIPS | [code](https://github.com/fabianp/ProxASAGA) | 9 | +| [Practical Data-Dependent Metric Compression with Provable Guarantees](http://papers.nips.cc/paper/6855-practical-data-dependent-metric-compression-with-provable-guarantees.pdf) | NIPS | [code](https://github.com/talwagner/quadsketch) | 9 | +| [Do Deep Neural Networks Suffer from Crowding?](http://papers.nips.cc/paper/7146-do-deep-neural-networks-suffer-from-crowding.pdf) | NIPS | [code](https://github.com/CBMM/eccentricity) | 9 | +| [A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting](http://openaccess.thecvf.com/content_cvpr_2017/html/Queau_A_Non-Convex_Variational_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yqueau/robust_ps) | 9 | +| [End-To-End Learning of Geometry and Context for Deep Stereo Regression](http://openaccess.thecvf.com/content_iccv_2017/html/Kendall_End-To-End_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/liuruijin17/RickLiuGC) | 9 | +| [From Bayesian Sparsity to Gated Recurrent Nets](http://papers.nips.cc/paper/7139-from-bayesian-sparsity-to-gated-recurrent-nets.pdf) | NIPS | [code](https://github.com/hehaodele/SBL-LSTM-Net) | 8 | +| [Regret Minimization in MDPs with Options without Prior Knowledge](http://papers.nips.cc/paper/6909-regret-minimization-in-mdps-with-options-without-prior-knowledge.pdf) | NIPS | [code](https://github.com/RonanFR/UCRL) | 8 | +| [Following Gaze in Video](http://openaccess.thecvf.com/content_iccv_2017/html/Recasens_Following_Gaze_in_ICCV_2017_paper.html) | ICCV | [code](https://github.com/recasens/Gaze-Following) | 8 | +| [Model-Powered Conditional Independence Test](http://papers.nips.cc/paper/6888-model-powered-conditional-independence-test.pdf) | NIPS | [code](https://github.com/rajatsen91/CCIT) | 8 | +| [Cost efficient gradient boosting](http://papers.nips.cc/paper/6753-cost-efficient-gradient-boosting.pdf) | NIPS | [code](https://github.com/svenpeter42/LightGBM-CEGB) | 8 | +| [Reflectance Adaptive Filtering Improves Intrinsic Image Estimation](http://openaccess.thecvf.com/content_cvpr_2017/html/Nestmeyer_Reflectance_Adaptive_Filtering_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tnestmeyer/reflectance-filtering) | 8 | +| [DeepNav: Learning to Navigate Large Cities](http://openaccess.thecvf.com/content_cvpr_2017/html/Brahmbhatt_DeepNav_Learning_to_CVPR_2017_paper.html) | CVPR | [code](https://github.com/samarth-robo/deepnav_cvpr17) | 8 | +| [Look, Listen and Learn](http://openaccess.thecvf.com/content_iccv_2017/html/Arandjelovic_Look_Listen_and_ICCV_2017_paper.html) | ICCV | [code](https://github.com/Kajiyu/LLLNet) | 8 | +| [Attention-Aware Face Hallucination via Deep Reinforcement Learning](http://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Attention-Aware_Face_Hallucination_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ykshi/facehallucination) | 8 | +| [Plan, Attend, Generate: Planning for Sequence-to-Sequence Models](http://papers.nips.cc/paper/7131-plan-attend-generate-planning-for-sequence-to-sequence-models.pdf) | NIPS | [code](https://github.com/Dutil/PAG) | 8 | +| [Introspective Neural Networks for Generative Modeling](http://openaccess.thecvf.com/content_iccv_2017/html/Lazarow_Introspective_Neural_Networks_ICCV_2017_paper.html) | ICCV | [code](https://github.com/intermilan/inng) | 8 | +| [Affinity Clustering: Hierarchical Clustering at Scale](http://papers.nips.cc/paper/7262-affinity-clustering-hierarchical-clustering-at-scale.pdf) | NIPS | [code](https://github.com/MahsaDerakhshan/AffinityClustering) | 8 | +| [Gaze Embeddings for Zero-Shot Image Classification](http://openaccess.thecvf.com/content_cvpr_2017/html/Karessli_Gaze_Embeddings_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Noura-kr/CVPR17) | 8 | +| [Input Switched Affine Networks: An RNN Architecture Designed for Interpretability](http://proceedings.mlr.press/v70/foerster17a.html) | ICML | [code](https://github.com/philipperemy/tensorflow-isan-rnn) | 8 | +| [Online multiclass boosting](http://papers.nips.cc/paper/6693-online-multiclass-boosting.pdf) | NIPS | [code](https://github.com/yhjung88/OnlineBoostingWithVFDT) | 8 | +| [Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images](http://openaccess.thecvf.com/content_iccv_2017/html/Orekondy_Towards_a_Visual_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tribhuvanesh/vpa) | 8 | +| [SubUNets: End-To-End Hand Shape and Continuous Sign Language Recognition](http://openaccess.thecvf.com/content_iccv_2017/html/Camgoz_SubUNets_End-To-End_Hand_ICCV_2017_paper.html) | ICCV | [code](https://github.com/neccam/SubUNets) | 7 | +| [Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition](http://papers.nips.cc/paper/6713-learning-koopman-invariant-subspaces-for-dynamic-mode-decomposition.pdf) | NIPS | [code](https://github.com/thetak11/learning-kis) | 7 | +| [Unsupervised Monocular Depth Estimation With Left-Right Consistency](http://openaccess.thecvf.com/content_cvpr_2017/html/Godard_Unsupervised_Monocular_Depth_CVPR_2017_paper.html) | CVPR | [code](https://github.com/yukitsuji/monodepth_chainer) | 7 | +| [Personalized Image Aesthetics](http://openaccess.thecvf.com/content_iccv_2017/html/Ren_Personalized_Image_Aesthetics_ICCV_2017_paper.html) | ICCV | [code](https://github.com/alanspike/personalizedImageAesthetics) | 7 | +| [Reasoning About Fine-Grained Attribute Phrases Using Reference Games](http://openaccess.thecvf.com/content_iccv_2017/html/Su_Reasoning_About_Fine-Grained_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jongchyisu/attribute_phrases) | 7 | +| [Lost Relatives of the Gumbel Trick](http://proceedings.mlr.press/v70/balog17a.html) | ICML | [code](https://github.com/matejbalog/gumbel-relatives) | 7 | +| [Weakly Supervised Learning of Deep Metrics for Stereo Reconstruction](http://openaccess.thecvf.com/content_iccv_2017/html/Tulyakov_Weakly_Supervised_Learning_ICCV_2017_paper.html) | ICCV | [code](https://github.com/tlkvstepan/mc-cnn-ws) | 7 | +| [Centered Weight Normalization in Accelerating Training of Deep Neural Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Centered_Weight_Normalization_ICCV_2017_paper.html) | ICCV | [code](https://github.com/huangleiBuaa/CenteredWN) | 6 | +| [Scalable Planning with Tensorflow for Hybrid Nonlinear Domains](http://papers.nips.cc/paper/7207-scalable-planning-with-tensorflow-for-hybrid-nonlinear-domains.pdf) | NIPS | [code](https://github.com/wuga214/TOOLBOX-Learning-and-Planning-through-Backpropagation) | 6 | +| [Convex Global 3D Registration With Lagrangian Duality](http://openaccess.thecvf.com/content_cvpr_2017/html/Briales_Convex_Global_3D_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jbriales/CVPR17) | 6 | +| [Building a Regular Decision Boundary With Deep Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Oyallon_Building_a_Regular_CVPR_2017_paper.html) | CVPR | [code](https://github.com/edouardoyallon/deep_separation_contraction) | 6 | +| [Learning Spatial Regularization With Image-Level Supervisions for Multi-Label Image Classification](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Learning_Spatial_Regularization_CVPR_2017_paper.html) | CVPR | [code](https://github.com/Enjia/Spatial-Regularization-Network-in-Tensorflow) | 6 | +| [Forecasting Human Dynamics From Static Images](http://openaccess.thecvf.com/content_cvpr_2017/html/Chao_Forecasting_Human_Dynamics_CVPR_2017_paper.html) | CVPR | [code](https://github.com/ywchao/skeleton2d3d) | 6 | +| [AOD-Net: All-In-One Dehazing Network](http://openaccess.thecvf.com/content_iccv_2017/html/Li_AOD-Net_All-In-One_Dehazing_ICCV_2017_paper.html) | ICCV | [code](https://github.com/weber0522bb/AODnet-by-pytorch) | 6 | +| [K-Medoids For K-Means Seeding](http://papers.nips.cc/paper/7104-k-medoids-for-k-means-seeding.pdf) | NIPS | [code](https://github.com/idiap/zentas) | 6 | +| [Diverse Image Annotation](http://openaccess.thecvf.com/content_cvpr_2017/html/Wu_Diverse_Image_Annotation_CVPR_2017_paper.html) | CVPR | [code](https://github.com/wubaoyuan/DIA) | 6 | +| [Practical Hash Functions for Similarity Estimation and Dimensionality Reduction](http://papers.nips.cc/paper/7239-practical-hash-functions-for-similarity-estimation-and-dimensionality-reduction.pdf) | NIPS | [code](https://github.com/zera/Nips_MT) | 6 | +| [Deep Adaptive Image Clustering](http://openaccess.thecvf.com/content_iccv_2017/html/Chang_Deep_Adaptive_Image_ICCV_2017_paper.html) | ICCV | [code](https://github.com/HongtaoYang/DAC-tensorflow) | 6 | +| [Robust Adversarial Reinforcement Learning](http://proceedings.mlr.press/v70/pinto17a.html) | ICML | [code](https://github.com/Jekyll1021/RARL) | 6 | +| [Improving Training of Deep Neural Networks via Singular Value Bounding](http://openaccess.thecvf.com/content_cvpr_2017/html/Jia_Improving_Training_of_CVPR_2017_paper.html) | CVPR | [code](https://github.com/kui-jia/svb) | 6 | +| [Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems](http://papers.nips.cc/paper/6838-analyzing-hidden-representations-in-end-to-end-automatic-speech-recognition-systems.pdf) | NIPS | [code](https://github.com/boknilev/asr-repr-analysis) | 6 | +| [Tensor Belief Propagation](http://proceedings.mlr.press/v70/wrigley17a.html) | ICML | [code](https://github.com/akxlr/tbp) | 6 | +| [Sparse convolutional coding for neuronal assembly detection](http://papers.nips.cc/paper/6958-sparse-convolutional-coding-for-neuronal-assembly-detection.pdf) | NIPS | [code](https://github.com/sccfnad/Sparse-convolutional-coding-for-neuronal-assembly-detection) | 6 | +| [Unsupervised Pixel-Level Domain Adaptation With Generative Adversarial Networks](http://openaccess.thecvf.com/content_cvpr_2017/html/Bousmalis_Unsupervised_Pixel-Level_Domain_CVPR_2017_paper.html) | CVPR | [code](https://github.com/rhythm92/Unsupervised-Pixel-Level-Domain-Adaptation-with-GAN) | 6 | +| [Bayesian inference on random simple graphs with power law degree distributions](http://proceedings.mlr.press/v70/lee17a.html) | ICML | [code](https://github.com/juho-lee/powerlawgraph) | 6 | +| [Tensor Biclustering](http://papers.nips.cc/paper/6730-tensor-biclustering.pdf) | NIPS | [code](https://github.com/SoheilFeizi/Tensor-Biclustering) | 6 | +| [Riemannian approach to batch normalization](http://papers.nips.cc/paper/7107-riemannian-approach-to-batch-normalization.pdf) | NIPS | [code](https://github.com/MinhyungCho/riemannian-batch-normalization) | 6 | +| [Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings](http://openaccess.thecvf.com/content_iccv_2017/html/Thewlis_Unsupervised_Learning_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/alldbi/Factorized-Spatial-Embeddings) | 6 | +| [Rolling-Shutter-Aware Differential SfM and Image Rectification](http://openaccess.thecvf.com/content_iccv_2017/html/Zhuang_Rolling-Shutter-Aware_Differential_SfM_ICCV_2017_paper.html) | ICCV | [code](https://github.com/ThomasZiegler/RS-aware-differential-SfM) | 5 | +| [Active Decision Boundary Annotation With Deep Generative Models](http://openaccess.thecvf.com/content_iccv_2017/html/Huijser_Active_Decision_Boundary_ICCV_2017_paper.html) | ICCV | [code](https://github.com/MiriamHu/ActiveBoundary) | 5 | +| [Object Co-Skeletonization With Co-Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Jerripothula_Object_Co-Skeletonization_With_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jkoteswarrao/Object-Co-skeletonization-with-Co-segmentation) | 5 | +| [Discover and Learn New Objects From Documentaries](http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Discover_and_Learn_CVPR_2017_paper.html) | CVPR | [code](https://github.com/hellock/documentary-learning) | 5 | +| [Understanding Black-box Predictions via Influence Functions](http://proceedings.mlr.press/v70/koh17a.html) | ICML | [code](https://github.com/eolecvk/InfluenceFunctions) | 5 | +| [Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach](http://openaccess.thecvf.com/content_cvpr_2017/html/Patrini_Making_Deep_Neural_CVPR_2017_paper.html) | CVPR | [code](https://github.com/GarrettLee/label_noise_correction) | 5 | +| [Decoupling "when to update" from "how to update"](http://papers.nips.cc/paper/6697-decoupling-when-to-update-from-how-to-update.pdf) | NIPS | [code](https://github.com/emalach/UpdateByDisagreement) | 5 | +| [MarioQA: Answering Questions by Watching Gameplay Videos](http://openaccess.thecvf.com/content_iccv_2017/html/Mun_MarioQA_Answering_Questions_ICCV_2017_paper.html) | ICCV | [code](https://github.com/JonghwanMun/MarioQA) | 5 | +| [Differentially private Bayesian learning on distributed data](http://papers.nips.cc/paper/6915-differentially-private-bayesian-learning-on-distributed-data.pdf) | NIPS | [code](https://github.com/DPBayes/dca-nips2017) | 5 | +| [Grad-CAM: Visual Explanations From Deep Networks via Gradient-Based Localization](http://openaccess.thecvf.com/content_iccv_2017/html/Selvaraju_Grad-CAM_Visual_Explanations_ICCV_2017_paper.html) | ICCV | [code](https://github.com/cydonia999/Grad-CAM-in-TensorFlow) | 5 | +| [Question Asking as Program Generation](http://papers.nips.cc/paper/6705-question-asking-as-program-generation.pdf) | NIPS | [code](https://github.com/anselmrothe/question_dataset) | 5 | +| [Conic Scan-and-Cover algorithms for nonparametric topic modeling](http://papers.nips.cc/paper/6977-conic-scan-and-cover-algorithms-for-nonparametric-topic-modeling.pdf) | NIPS | [code](https://github.com/moonfolk/Geometric-Topic-Modeling) | 5 | +| [Lip Reading Sentences in the Wild](http://openaccess.thecvf.com/content_cvpr_2017/html/Chung_Lip_Reading_Sentences_CVPR_2017_paper.html) | CVPR | [code](https://github.com/lsrock1/WLSNet_pytorch) | 5 | +| [ROAM: A Rich Object Appearance Model With Application to Rotoscoping](http://openaccess.thecvf.com/content_cvpr_2017/html/Miksik_ROAM_A_Rich_CVPR_2017_paper.html) | CVPR | [code](https://github.com/omiksik/roam) | 5 | +| [NeuralFDR: Learning Discovery Thresholds from Hypothesis Features](http://papers.nips.cc/paper/6752-neuralfdr-learning-discovery-thresholds-from-hypothesis-features.pdf) | NIPS | [code](https://github.com/fxia22/NeuralFDR) | 5 | +| [Viraliency: Pooling Local Virality](http://openaccess.thecvf.com/content_cvpr_2017/html/Alameda-Pineda_Viraliency_Pooling_Local_CVPR_2017_paper.html) | CVPR | [code](https://github.com/xavirema/lena_pooling) | 5 | +| [Learning Algorithms for Active Learning](http://proceedings.mlr.press/v70/bachman17a.html) | ICML | [code](https://github.com/vtphan/Code4Brownies) | 5 | +| [Point to Set Similarity Based Deep Feature Learning for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Point_to_Set_CVPR_2017_paper.html) | CVPR | [code](https://github.com/samaonline/Point-to-Set-Similarity-Based-Deep-Feature-Learning-for-Person-Re-identification) | 5 | +| [Click Here: Human-Localized Keypoints as Guidance for Viewpoint Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Szeto_Click_Here_Human-Localized_ICCV_2017_paper.html) | ICCV | [code](https://github.com/rszeto/click-here-cnn) | 5 | +| [The World of Fast Moving Objects](http://openaccess.thecvf.com/content_cvpr_2017/html/Rozumnyi_The_World_of_CVPR_2017_paper.html) | CVPR | [code](https://github.com/qixuanHou/Mapping-My-Break) | 5 | +| [Cross-Modality Binary Code Learning via Fusion Similarity Hashing](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Cross-Modality_Binary_Code_CVPR_2017_paper.html) | CVPR | [code](https://github.com/LynnHongLiu/FSH) | 5 | +| [Testing and Learning on Distributions with Symmetric Noise Invariance](http://papers.nips.cc/paper/6733-testing-and-learning-on-distributions-with-symmetric-noise-invariance.pdf) | NIPS | [code](https://github.com/hcllaw/phase_learn) | 5 | +| [Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference](http://papers.nips.cc/paper/7268-sticking-the-landing-simple-lower-variance-gradient-estimators-for-variational-inference.pdf) | NIPS | [code](https://github.com/geoffroeder/iwae) | 5 | +| [Diving into the shallows: a computational perspective on large-scale shallow learning](http://papers.nips.cc/paper/6968-diving-into-the-shallows-a-computational-perspective-on-large-scale-shallow-learning.pdf) | NIPS | [code](https://github.com/EigenPro/EigenPro-tensorflow) | 5 | +| [Rotation Equivariant Vector Field Networks](http://openaccess.thecvf.com/content_iccv_2017/html/Marcos_Rotation_Equivariant_Vector_ICCV_2017_paper.html) | ICCV | [code](https://github.com/dmarcosg/RotEqNet) | 5 | +| [Recursive Sampling for the Nystrom Method](http://papers.nips.cc/paper/6973-recursive-sampling-for-the-nystrom-method.pdf) | NIPS | [code](https://github.com/cnmusco/recursive-nystrom) | 5 | +| [Learning From Video and Text via Large-Scale Discriminative Clustering](http://openaccess.thecvf.com/content_iccv_2017/html/Miech_Learning_From_Video_ICCV_2017_paper.html) | ICCV | [code](https://github.com/antoine77340/iccv17learning) | 5 | +| [Global optimization of Lipschitz functions](http://proceedings.mlr.press/v70/malherbe17a.html) | ICML | [code](https://github.com/Sycor4x/lipo) | 5 | +| [Device Placement Optimization with Reinforcement Learning](http://proceedings.mlr.press/v70/mirhoseini17a.html) | ICML | [code](https://github.com/indrajeet95/Device-Placement-Optimization-with-Reinforcement-Learning) | 4 | +| [Alternating Direction Graph Matching](http://openaccess.thecvf.com/content_cvpr_2017/html/Le-Huu_Alternating_Direction_Graph_CVPR_2017_paper.html) | CVPR | [code](https://github.com/netw0rkf10w/adgm) | 4 | +| [MEC: Memory-efficient Convolution for Deep Neural Network](http://proceedings.mlr.press/v70/cho17a.html) | ICML | [code](https://github.com/CSshengxy/MEC) | 4 | +| [Expert Gate: Lifelong Learning With a Network of Experts](http://openaccess.thecvf.com/content_cvpr_2017/html/Aljundi_Expert_Gate_Lifelong_CVPR_2017_paper.html) | CVPR | [code](https://github.com/rahafaljundi/Expert-Gate) | 4 | +| [A Simple yet Effective Baseline for 3D Human Pose Estimation](http://openaccess.thecvf.com/content_iccv_2017/html/Martinez_A_Simple_yet_ICCV_2017_paper.html) | ICCV | [code](https://github.com/nulledge/bilinear) | 4 | +| [On Structured Prediction Theory with Calibrated Convex Surrogate Losses](http://papers.nips.cc/paper/6634-on-structured-prediction-theory-with-calibrated-convex-surrogate-losses.pdf) | NIPS | [code](https://github.com/aosokin/consistentSurrogates_derivations) | 4 | +| [Sub-sampled Cubic Regularization for Non-convex Optimization](http://proceedings.mlr.press/v70/kohler17a.html) | ICML | [code](https://github.com/dalab/subsampled_cubic_regularization) | 4 | +| [Generalized Semantic Preserving Hashing for N-Label Cross-Modal Retrieval](http://openaccess.thecvf.com/content_cvpr_2017/html/Mandal_Generalized_Semantic_Preserving_CVPR_2017_paper.html) | CVPR | [code](https://github.com/devraj89/Generalized-Semantic-Preserving-Hashing-for-N-Label-Cross-Modal-Retrieval) | 4 | +| [Bottleneck Conditional Density Estimation](http://proceedings.mlr.press/v70/shu17a.html) | ICML | [code](https://github.com/RuiShu/bcde) | 4 | +| [Learning Cooperative Visual Dialog Agents With Deep Reinforcement Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Das_Learning_Cooperative_Visual_ICCV_2017_paper.html) | ICCV | [code](https://github.com/schopra8/Cooperative_Vis_Diag_RL) | 4 | +| [Multi-way Interacting Regression via Factorization Machines](http://papers.nips.cc/paper/6853-multi-way-interacting-regression-via-factorization-machines.pdf) | NIPS | [code](https://github.com/moonfolk/MiFM) | 4 | +| [Joint Discovery of Object States and Manipulation Actions](http://openaccess.thecvf.com/content_iccv_2017/html/Alayrac_Joint_Discovery_of_ICCV_2017_paper.html) | ICCV | [code](https://github.com/jalayrac/object-states-action) | 4 | +| [Predicting Salient Face in Multiple-Face Videos](http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Predicting_Salient_Face_CVPR_2017_paper.html) | CVPR | [code](https://github.com/tonysy/salient-face-in-MUVFET) | 4 | +| [From Red Wine to Red Tomato: Composition With Context](http://openaccess.thecvf.com/content_cvpr_2017/html/Misra_From_Red_Wine_CVPR_2017_paper.html) | CVPR | [code](https://github.com/imisra/composing_cvpr17) | 4 | +| [Encoder Based Lifelong Learning](http://openaccess.thecvf.com/content_iccv_2017/html/Rannen_Encoder_Based_Lifelong_ICCV_2017_paper.html) | ICCV | [code](https://github.com/rahafaljundi/Encoder-Based-Lifelong-learning) | 4 | +| [Deep Recurrent Neural Network-Based Identification of Precursor microRNAs](http://papers.nips.cc/paper/6882-deep-recurrent-neural-network-based-identification-of-precursor-micrornas.pdf) | NIPS | [code](https://github.com/eleventh83/deepMiRGene) | 4 | +| [Guarantees for Greedy Maximization of Non-submodular Functions with Applications](http://proceedings.mlr.press/v70/bian17a.html) | ICML | [code](https://github.com/bianan/non-submodular-max) | 4 | +| [Pose-Aware Person Recognition](http://openaccess.thecvf.com/content_cvpr_2017/html/Kumar_Pose-Aware_Person_Recognition_CVPR_2017_paper.html) | CVPR | [code](https://github.com/vijaykumar01/person_recognition) | 4 | +| [Zero-Shot Recognition Using Dual Visual-Semantic Mapping Paths](http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Zero-Shot_Recognition_Using_CVPR_2017_paper.html) | CVPR | [code](https://github.com/YanaLee/Zero-Shot-Recognition-using-Dual-Visual-Semantic-Mapping-Paths) | 4 | +| [Asynchronous Distributed Variational Gaussian Processes for Regression](nan) | ICML | [code](https://github.com/hao-peng/ADVGP) | 3 | +| [Saliency Pattern Detection by Ranking Structured Trees](http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Saliency_Pattern_Detection_ICCV_2017_paper.html) | ICCV | [code](https://github.com/zhulei2016/RST-saliency) | 3 | +| [Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System](http://papers.nips.cc/paper/6849-toward-goal-driven-neural-network-models-for-the-rodent-whisker-trigeminal-system.pdf) | NIPS | [code](https://github.com/neuroailab/whisker_model) | 3 | +| [Learning Non-Maximum Suppression](http://openaccess.thecvf.com/content_cvpr_2017/html/Hosang_Learning_Non-Maximum_Suppression_CVPR_2017_paper.html) | CVPR | [code](https://github.com/XingchenYu/pedestrian_detection_iosapp) | 3 | +| [Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC](http://proceedings.mlr.press/v70/cong17a.html) | ICML | [code](https://github.com/mingyuanzhou/DeepLDA_TLASGR_MCMC) | 3 | +| [Discriminative Bimodal Networks for Visual Localization and Detection With Natural Language Queries](http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Discriminative_Bimodal_Networks_CVPR_2017_paper.html) | CVPR | [code](https://github.com/YutingZhang/dbnet-caffe-matlab) | 3 | +| [AdaNet: Adaptive Structural Learning of Artificial Neural Networks](http://proceedings.mlr.press/v70/cortes17a.html) | ICML | [code](https://github.com/davidabek1/adanet) | 3 | +| [Large Margin Object Tracking With Circulant Feature Maps](http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Large_Margin_Object_CVPR_2017_paper.html) | CVPR | [code](https://github.com/sallymmx/LMCF) | 3 | +| [Compatible Reward Inverse Reinforcement Learning](http://papers.nips.cc/paper/6800-compatible-reward-inverse-reinforcement-learning.pdf) | NIPS | [code](https://github.com/albertometelli/crirl) | 3 | +| [Adversarial Surrogate Losses for Ordinal Regression](http://papers.nips.cc/paper/6659-adversarial-surrogate-losses-for-ordinal-regression.pdf) | NIPS | [code](https://github.com/rizalzaf/adversarial-ordinal) | 3 | +| [Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms](http://papers.nips.cc/paper/6652-continuous-dr-submodular-maximization-structure-and-algorithms.pdf) | NIPS | [code](https://github.com/bianan) | 3 | +| [Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning](http://papers.nips.cc/paper/7154-unifying-pac-and-regret-uniform-pac-bounds-for-episodic-reinforcement-learning.pdf) | NIPS | [code](https://github.com/chrodan/FiniteEpisodicRL.jl) | 3 | +| [A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control](http://papers.nips.cc/paper/7177-a-framework-for-multi-armedbandit-testing-with-online-fdr-control.pdf) | NIPS | [code](https://github.com/fanny-yang/MABFDR) | 3 | +| [Counting Everyday Objects in Everyday Scenes](http://openaccess.thecvf.com/content_cvpr_2017/html/Chattopadhyay_Counting_Everyday_Objects_CVPR_2017_paper.html) | CVPR | [code](https://github.com/prithv1/cvpr2017_counting) | 3 | +| [Loss Max-Pooling for Semantic Image Segmentation](http://openaccess.thecvf.com/content_cvpr_2017/html/Bulo_Loss_Max-Pooling_for_CVPR_2017_paper.html) | CVPR | [code](https://github.com/jjkke88/LMP) | 3 | +| [Aesthetic Critiques Generation for Photos](http://openaccess.thecvf.com/content_iccv_2017/html/Chang_Aesthetic_Critiques_Generation_ICCV_2017_paper.html) | ICCV | [code](https://github.com/kunghunglu/DeepPhotoCritic-ICCV17) | 3 | +| [Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems](http://papers.nips.cc/paper/6798-expectation-propagation-with-stochastic-kinetic-model-in-complex-interaction-systems.pdf) | NIPS | [code](https://github.com/lefangcs/Expectation-Propagation-with-Stochastic-Kinetic-Model-in-Complex-Interaction-Systems) | 3 | +| [Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs](http://papers.nips.cc/paper/7049-near-optimal-edge-evaluation-in-explicit-generalized-binomial-graphs.pdf) | NIPS | [code](https://github.com/sanjibac/matlab_learning_collision_checking) | 3 |
↥ back to top @@ -1314,115 +1326,115 @@ Use [this](https://github.com/zziz/pwc/issues/11) thread to request us your favo ## 2016 | Title | Conf | Code | Stars | |:--------|:--------:|:--------:|:--------:| -| [R-FCN: Object Detection via Region-based Fully Convolutional Networks](https://papers.nips.cc/paper/6465-r-fcn-object-detection-via-region-based-fully-convolutional-networks.pdf) | NIPS | [code](https://github.com/facebookresearch/Detectron) | 18356 | -| [Image Style Transfer Using Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Gatys_Image_Style_Transfer_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jcjohnson/neural-style) | 16435 | -| [Deep Residual Learning for Image Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/He_Deep_Residual_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/KaimingHe/deep-residual-networks) | 4468 | -| [Convolutional Pose Machines](http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Convolutional_Pose_Machines_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation) | 3260 | -| [Synthetic Data for Text Localisation in Natural Images](http://openaccess.thecvf.com/content_cvpr_2016/html/Gupta_Synthetic_Data_for_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ankush-me/SynthText) | 787 | -| [Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis](http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Combining_Markov_Random_CVPR_2016_paper.html) | CVPR | [code](https://github.com/chuanli11/CNNMRF) | 731 | -| [Instance-Aware Semantic Segmentation via Multi-Task Network Cascades](http://openaccess.thecvf.com/content_cvpr_2016/html/Dai_Instance-Aware_Semantic_Segmentation_CVPR_2016_paper.html) | CVPR | [code](https://github.com/daijifeng001/MNC) | 433 | -| [Learning Multi-Domain Convolutional Neural Networks for Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2016/html/Nam_Learning_Multi-Domain_Convolutional_CVPR_2016_paper.html) | CVPR | [code](https://github.com/HyeonseobNam/MDNet) | 350 | -| [Convolutional Two-Stream Network Fusion for Video Action Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/Feichtenhofer_Convolutional_Two-Stream_Network_CVPR_2016_paper.html) | CVPR | [code](https://github.com/feichtenhofer/twostreamfusion) | 342 | -| [Learning Deep Features for Discriminative Localization](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhou_Learning_Deep_Features_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jazzsaxmafia/Weakly_detector) | 323 | -| [Deep Metric Learning via Lifted Structured Feature Embedding](http://openaccess.thecvf.com/content_cvpr_2016/html/Song_Deep_Metric_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/rksltnl/Deep-Metric-Learning-CVPR16) | 251 | -| [Learning Deep Representations of Fine-Grained Visual Descriptions](http://openaccess.thecvf.com/content_cvpr_2016/html/Reed_Learning_Deep_Representations_CVPR_2016_paper.html) | CVPR | [code](https://github.com/reedscot/cvpr2016) | 229 | -| [Eye Tracking for Everyone](http://openaccess.thecvf.com/content_cvpr_2016/html/Krafka_Eye_Tracking_for_CVPR_2016_paper.html) | CVPR | [code](https://github.com/CSAILVision/GazeCapture) | 223 | -| [NetVLAD: CNN Architecture for Weakly Supervised Place Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/Arandjelovic_NetVLAD_CNN_Architecture_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Relja/netvlad) | 204 | -| [Staple: Complementary Learners for Real-Time Tracking](http://openaccess.thecvf.com/content_cvpr_2016/html/Bertinetto_Staple_Complementary_Learners_CVPR_2016_paper.html) | CVPR | [code](https://github.com/bertinetto/staple) | 183 | -| [Joint Unsupervised Learning of Deep Representations and Image Clusters](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Joint_Unsupervised_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jwyang/JULE.torch) | 182 | -| [Accurate Image Super-Resolution Using Very Deep Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Kim_Accurate_Image_Super-Resolution_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Jongchan/tensorflow-vdsr) | 182 | -| [Temporal Action Localization in Untrimmed Videos via Multi-Stage CNNs](http://openaccess.thecvf.com/content_cvpr_2016/html/Shou_Temporal_Action_Localization_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zhengshou/scnn) | 167 | -| [LocNet: Improving Localization Accuracy for Object Detection](http://openaccess.thecvf.com/content_cvpr_2016/html/Gidaris_LocNet_Improving_Localization_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gidariss/LocNet) | 155 | -| [Shallow and Deep Convolutional Networks for Saliency Prediction](http://openaccess.thecvf.com/content_cvpr_2016/html/Pan_Shallow_and_Deep_CVPR_2016_paper.html) | CVPR | [code](https://github.com/imatge-upc/saliency-2016-cvpr) | 153 | -| [Compact Bilinear Pooling](http://openaccess.thecvf.com/content_cvpr_2016/html/Gao_Compact_Bilinear_Pooling_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gy20073/compact_bilinear_pooling) | 148 | -| [Learning Compact Binary Descriptors With Unsupervised Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Lin_Learning_Compact_Binary_CVPR_2016_paper.html) | CVPR | [code](https://github.com/kevinlin311tw/cvpr16-deepbit) | 144 | -| [Dynamic Image Networks for Action Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/Bilen_Dynamic_Image_Networks_CVPR_2016_paper.html) | CVPR | [code](https://github.com/hbilen/dynamic-image-nets) | 133 | -| [Rethinking the Inception Architecture for Computer Vision](http://openaccess.thecvf.com/content_cvpr_2016/html/Szegedy_Rethinking_the_Inception_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Moodstocks/inception-v3.torch) | 130 | -| [Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images](http://openaccess.thecvf.com/content_cvpr_2016/html/Song_Deep_Sliding_Shapes_CVPR_2016_paper.html) | CVPR | [code](https://github.com/shurans/DeepSlidingShape) | 126 | -| [Context Encoders: Feature Learning by Inpainting](http://openaccess.thecvf.com/content_cvpr_2016/html/Pathak_Context_Encoders_Feature_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jazzsaxmafia/Inpainting) | 124 | -| [TI-Pooling: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Laptev_TI-Pooling_Transformation-Invariant_Pooling_CVPR_2016_paper.html) | CVPR | [code](https://github.com/dlaptev/TI-pooling) | 109 | -| [Weakly Supervised Deep Detection Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Bilen_Weakly_Supervised_Deep_CVPR_2016_paper.html) | CVPR | [code](https://github.com/hbilen/WSDDN) | 103 | -| [Natural Language Object Retrieval](http://openaccess.thecvf.com/content_cvpr_2016/html/Hu_Natural_Language_Object_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ronghanghu/natural-language-object-retrieval) | 100 | -| [Deeply-Recursive Convolutional Network for Image Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2016/html/Kim_Deeply-Recursive_Convolutional_Network_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jiny2001/deeply-recursive-cnn-tf) | 96 | -| [Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network](http://openaccess.thecvf.com/content_cvpr_2016/html/Shi_Real-Time_Single_Image_CVPR_2016_paper.html) | CVPR | [code](https://github.com/leftthomas/ESPCN) | 92 | -| [Image Question Answering Using Convolutional Neural Network With Dynamic Parameter Prediction](http://openaccess.thecvf.com/content_cvpr_2016/html/Noh_Image_Question_Answering_CVPR_2016_paper.html) | CVPR | [code](https://github.com/HyeonwooNoh/DPPnet) | 88 | -| [Recurrent Convolutional Network for Video-Based Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2016/html/McLaughlin_Recurrent_Convolutional_Network_CVPR_2016_paper.html) | CVPR | [code](https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID) | 82 | -| [A Comparative Study for Single Image Blind Deblurring](http://openaccess.thecvf.com/content_cvpr_2016/html/Lai_A_Comparative_Study_CVPR_2016_paper.html) | CVPR | [code](https://github.com/phoenix104104/cvpr16_deblur_study) | 82 | -| [Neural Module Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Andreas_Neural_Module_Networks_CVPR_2016_paper.html) | CVPR | [code](https://github.com/HarshTrivedi/nmn-pytorch) | 81 | -| [Stacked Attention Networks for Image Question Answering](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Stacked_Attention_Networks_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zcyang/imageqa-san) | 78 | -| [Progressive Prioritized Multi-View Stereo](http://openaccess.thecvf.com/content_cvpr_2016/html/Locher_Progressive_Prioritized_Multi-View_CVPR_2016_paper.html) | CVPR | [code](https://github.com/alexlocher/hpmvs) | 73 | -| [Marr Revisited: 2D-3D Alignment via Surface Normal Prediction](http://openaccess.thecvf.com/content_cvpr_2016/html/Bansal_Marr_Revisited_2D-3D_CVPR_2016_paper.html) | CVPR | [code](https://github.com/aayushbansal/MarrRevisited) | 72 | -| [A Hierarchical Deep Temporal Model for Group Activity Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/Ibrahim_A_Hierarchical_Deep_CVPR_2016_paper.html) | CVPR | [code](https://github.com/mostafa-saad/deep-activity-rec) | 71 | -| [Towards Open Set Deep Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Bendale_Towards_Open_Set_CVPR_2016_paper.html) | CVPR | [code](https://github.com/abhijitbendale/OSDN) | 71 | -| [Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs](http://openaccess.thecvf.com/content_cvpr_2016/html/Ge_Robust_3D_Hand_CVPR_2016_paper.html) | CVPR | [code](https://github.com/geliuhao/CVPR2016_HandPoseEstimation) | 70 | -| [Bilateral Space Video Segmentation](http://openaccess.thecvf.com/content_cvpr_2016/html/Maerki_Bilateral_Space_Video_CVPR_2016_paper.html) | CVPR | [code](https://github.com/owang/BilateralVideoSegmentation) | 63 | -| [Deep Compositional Captioning: Describing Novel Object Categories Without Paired Training Data](http://openaccess.thecvf.com/content_cvpr_2016/html/Hendricks_Deep_Compositional_Captioning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/LisaAnne/DCC) | 57 | -| [Efficient 3D Room Shape Recovery From a Single Panorama](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Efficient_3D_Room_CVPR_2016_paper.html) | CVPR | [code](https://github.com/YANG-H/Panoramix) | 55 | -| [Non-Local Image Dehazing](http://openaccess.thecvf.com/content_cvpr_2016/html/Berman_Non-Local_Image_Dehazing_CVPR_2016_paper.html) | CVPR | [code](https://github.com/danaberman/non-local-dehazing) | 50 | -| [Video Segmentation via Object Flow](http://openaccess.thecvf.com/content_cvpr_2016/html/Tsai_Video_Segmentation_via_CVPR_2016_paper.html) | CVPR | [code](https://github.com/wasidennis/ObjectFlow) | 50 | -| [Deep Supervised Hashing for Fast Image Retrieval](http://openaccess.thecvf.com/content_cvpr_2016/html/Liu_Deep_Supervised_Hashing_CVPR_2016_paper.html) | CVPR | [code](https://github.com/yg33717/DSH_tensorflow) | 50 | -| [Deep Region and Multi-Label Learning for Facial Action Unit Detection](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhao_Deep_Region_and_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zkl20061823/DRML) | 43 | -| [CRAFT Objects From Images](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_CRAFT_Objects_From_CVPR_2016_paper.html) | CVPR | [code](https://github.com/byangderek/CRAFT) | 41 | -| [Slicing Convolutional Neural Network for Crowd Video Understanding](http://openaccess.thecvf.com/content_cvpr_2016/html/Shao_Slicing_Convolutional_Neural_CVPR_2016_paper.html) | CVPR | [code](https://github.com/amandajshao/Slicing-CNN) | 40 | -| [Sketch Me That Shoe](http://openaccess.thecvf.com/content_cvpr_2016/html/Yu_Sketch_Me_That_CVPR_2016_paper.html) | CVPR | [code](https://github.com/seuliufeng/DeepSBIR) | 39 | -| [Image Captioning With Semantic Attention](http://openaccess.thecvf.com/content_cvpr_2016/html/You_Image_Captioning_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/chapternewscu/image-captioning-with-semantic-attention) | 35 | -| [Deep Saliency With Encoded Low Level Distance Map and High Level Features](http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Deep_Saliency_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gylee1103/SaliencyELD) | 34 | -| [A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation](http://openaccess.thecvf.com/content_cvpr_2016/html/Perazzi_A_Benchmark_Dataset_CVPR_2016_paper.html) | CVPR | [code](https://github.com/davisvideochallenge/davis-matlab) | 33 | -| [A Dual-Source Approach for 3D Pose Estimation From a Single Image](http://openaccess.thecvf.com/content_cvpr_2016/html/Yasin_A_Dual-Source_Approach_CVPR_2016_paper.html) | CVPR | [code](https://github.com/iqbalu/3D_Pose_Estimation_CVPR2016) | 32 | -| [Learning Local Image Descriptors With Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions](http://openaccess.thecvf.com/content_cvpr_2016/html/G_Learning_Local_Image_CVPR_2016_paper.html) | CVPR | [code](https://github.com/vijaykbg/deep-patchmatch) | 30 | -| [Ordinal Regression With Multiple Output CNN for Age Estimation](http://openaccess.thecvf.com/content_cvpr_2016/html/Niu_Ordinal_Regression_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/luoyetx/OrdinalRegression) | 30 | -| [Structured Feature Learning for Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2016/html/Chu_Structured_Feature_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/chuxiaoselena/StructuredFeature) | 29 | -| [Unsupervised Learning of Edges](http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Unsupervised_Learning_of_CVPR_2016_paper.html) | CVPR | [code](https://github.com/happyharrycn/unsupervised_edges) | 29 | -| [PatchBatch: A Batch Augmented Loss for Optical Flow](http://openaccess.thecvf.com/content_cvpr_2016/html/Gadot_PatchBatch_A_Batch_CVPR_2016_paper.html) | CVPR | [code](https://github.com/DediGadot/PatchBatch) | 27 | -| [Dense Human Body Correspondences Using Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Dense_Human_Body_CVPR_2016_paper.html) | CVPR | [code](https://github.com/halimacc/DenseHumanBodyCorrespondences) | 27 | -| [Actionness Estimation Using Hybrid Fully Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Actionness_Estimation_Using_CVPR_2016_paper.html) | CVPR | [code](https://github.com/wanglimin/Actionness-Estimation) | 26 | -| [You Only Look Once: Unified, Real-Time Object Detection](http://openaccess.thecvf.com/content_cvpr_2016/html/Redmon_You_Only_Look_CVPR_2016_paper.html) | CVPR | [code](https://github.com/andersy005/keras-yolo) | 26 | -| [Fast Training of Triplet-Based Deep Binary Embedding Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhuang_Fast_Training_of_CVPR_2016_paper.html) | CVPR | [code](https://github.com/xwzy/Triplet-deep-hash-pytorch) | 25 | -| [Recurrent Attention Models for Depth-Based Person Identification](http://openaccess.thecvf.com/content_cvpr_2016/html/Haque_Recurrent_Attention_Models_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ahaque/ram_person_id) | 24 | -| [Detecting Vanishing Points Using Global Image Context in a Non-Manhattan World](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhai_Detecting_Vanishing_Points_CVPR_2016_paper.html) | CVPR | [code](https://github.com/viibridges/gc-horizon-detector) | 22 | -| [First Person Action Recognition Using Deep Learned Descriptors](http://openaccess.thecvf.com/content_cvpr_2016/html/Singh_First_Person_Action_CVPR_2016_paper.html) | CVPR | [code](https://github.com/suriyasingh/EgoConvNet) | 21 | -| [Proposal Flow](http://openaccess.thecvf.com/content_cvpr_2016/html/Ham_Proposal_Flow_CVPR_2016_paper.html) | CVPR | [code](https://github.com/bsham/ProposalFlow) | 20 | -| [Scale-Aware Alignment of Hierarchical Image Segmentation](http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Scale-Aware_Alignment_of_CVPR_2016_paper.html) | CVPR | [code](https://github.com/yuhuayc/align-hier) | 20 | -| [Quantized Convolutional Neural Networks for Mobile Devices](http://openaccess.thecvf.com/content_cvpr_2016/html/Wu_Quantized_Convolutional_Neural_CVPR_2016_paper.html) | CVPR | [code](https://github.com/OluwoleOyetoke/Computer_Vision_Using_TensorFlowLite) | 20 | -| [Semantic Segmentation With Boundary Neural Fields](http://openaccess.thecvf.com/content_cvpr_2016/html/Bertasius_Semantic_Segmentation_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gberta/BNF_globalization) | 19 | -| [Single-Image Crowd Counting via Multi-Column Convolutional Neural Network](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Single-Image_Crowd_Counting_CVPR_2016_paper.html) | CVPR | [code](https://github.com/uestcchicken/crowd-counting-MCNN) | 19 | -| [Accumulated Stability Voting: A Robust Descriptor From Descriptors of Multiple Scales](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Accumulated_Stability_Voting_CVPR_2016_paper.html) | CVPR | [code](https://github.com/shamangary/ASV) | 19 | -| [Structure From Motion With Objects](http://openaccess.thecvf.com/content_cvpr_2016/html/Crocco_Structure_From_Motion_CVPR_2016_paper.html) | CVPR | [code](https://github.com/danylaksono/Android-SfM-client) | 17 | -| [Bottom-Up and Top-Down Reasoning With Hierarchical Rectified Gaussians](http://openaccess.thecvf.com/content_cvpr_2016/html/Hu_Bottom-Up_and_Top-Down_CVPR_2016_paper.html) | CVPR | [code](https://github.com/peiyunh/rg-mpii) | 16 | -| [Semantic Filtering](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Semantic_Filtering_CVPR_2016_paper.html) | CVPR | [code](https://github.com/shenshen-hungry/Semantic-CNN) | 16 | -| [Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network](http://openaccess.thecvf.com/content_cvpr_2016/html/Molchanov_Online_Detection_and_CVPR_2016_paper.html) | CVPR | [code](https://github.com/breadbread1984/R3DCNN) | 16 | -| [ReconNet: Non-Iterative Reconstruction of Images From Compressively Sensed Measurements](http://openaccess.thecvf.com/content_cvpr_2016/html/Kulkarni_ReconNet_Non-Iterative_Reconstruction_CVPR_2016_paper.html) | CVPR | [code](https://github.com/KuldeepKulkarni/ReconNet) | 15 | -| [Interactive Segmentation on RGBD Images via Cue Selection](http://openaccess.thecvf.com/content_cvpr_2016/html/Feng_Interactive_Segmentation_on_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ZVsion/rgbd_image_segmentation) | 14 | -| [Object Contour Detection With a Fully Convolutional Encoder-Decoder Network](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Object_Contour_Detection_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Raj-08/tensorflow-object-contour-detection) | 14 | -| [Automatic Content-Aware Color and Tone Stylization](http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Automatic_Content-Aware_Color_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jinyu121/ACACTS) | 12 | -| [Similarity Learning With Spatial Constraints for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Similarity_Learning_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/dapengchen123/SCSP) | 11 | -| [Personalizing Human Video Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2016/html/Charles_Personalizing_Human_Video_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jjcharles/personalized_pose) | 10 | -| [Visually Indicated Sounds](http://openaccess.thecvf.com/content_cvpr_2016/html/Owens_Visually_Indicated_Sounds_CVPR_2016_paper.html) | CVPR | [code](https://github.com/kanchen-usc/VIG) | 9 | -| [Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification](http://openaccess.thecvf.com/content_cvpr_2016/html/Hou_Patch-Based_Convolutional_Neural_CVPR_2016_paper.html) | CVPR | [code](https://github.com/cheersyouran/cancer-detector) | 9 | -| [Region Ranking SVM for Image Classification](http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Region_Ranking_SVM_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zijunwei/Region-Ranking-SVM) | 8 | -| [Pairwise Matching Through Max-Weight Bipartite Belief Propagation](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Pairwise_Matching_Through_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zzhang1987/HungarianBP) | 8 | -| [Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled](http://openaccess.thecvf.com/content_cvpr_2016/html/Koller_Deep_Hand_How_CVPR_2016_paper.html) | CVPR | [code](https://github.com/neccam/TF-DeepHand) | 8 | -| [Cross-Stitch Networks for Multi-Task Learning](http://openaccess.thecvf.com/content_cvpr_2016/html/Misra_Cross-Stitch_Networks_for_CVPR_2016_paper.html) | CVPR | [code](https://github.com/helloyide/Cross-stitch-Networks-for-Multi-task-Learning) | 8 | -| [Learning a Discriminative Null Space for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Learning_a_Discriminative_CVPR_2016_paper.html) | CVPR | [code](https://github.com/lzrobots/NullSpace_ReID) | 8 | -| [Efficient Deep Learning for Stereo Matching](http://openaccess.thecvf.com/content_cvpr_2016/html/Luo_Efficient_Deep_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/haojeng-wang/dl_stereo_matching) | 7 | -| [Globally Optimal Manhattan Frame Estimation in Real-Time](http://openaccess.thecvf.com/content_cvpr_2016/html/Joo_Globally_Optimal_Manhattan_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Kyungdon/mf_estimation) | 7 | -| [Where to Look: Focus Regions for Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2016/html/Shih_Where_to_Look_CVPR_2016_paper.html) | CVPR | [code](https://github.com/kevjshih/wtl_vqa) | 7 | -| [Detecting Migrating Birds at Night](http://openaccess.thecvf.com/content_cvpr_2016/html/Huang_Detecting_Migrating_Birds_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jbhuang0604/BirdDetection) | 7 | -| [Unsupervised Learning From Narrated Instruction Videos](http://openaccess.thecvf.com/content_cvpr_2016/html/Alayrac_Unsupervised_Learning_From_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jalayrac/instructionVideos) | 7 | -| [Efficient and Robust Color Consistency for Community Photo Collections](http://openaccess.thecvf.com/content_cvpr_2016/html/Park_Efficient_and_Robust_CVPR_2016_paper.html) | CVPR | [code](https://github.com/syncle/photo_consistency) | 7 | -| [Recurrent Attentional Networks for Saliency Detection](http://openaccess.thecvf.com/content_cvpr_2016/html/Kuen_Recurrent_Attentional_Networks_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zhangxiaoning666/PAGR) | 7 | -| [3D Shape Attributes](http://openaccess.thecvf.com/content_cvpr_2016/html/Fouhey_3D_Shape_Attributes_CVPR_2016_paper.html) | CVPR | [code](https://github.com/petermalcolm/estimate3DStep) | 6 | -| [Beyond Local Search: Tracking Objects Everywhere With Instance-Specific Proposals](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhu_Beyond_Local_Search_CVPR_2016_paper.html) | CVPR | [code](https://github.com/GaoCode/EBT) | 5 | -| [Functional Faces: Groupwise Dense Correspondence Using Functional Maps](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Functional_Faces_Groupwise_CVPR_2016_paper.html) | CVPR | [code](https://github.com/cazhang/funcFaces) | 5 | -| [Visual Tracking Using Attention-Modulated Disintegration and Integration](http://openaccess.thecvf.com/content_cvpr_2016/html/Choi_Visual_Tracking_Using_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jongwon20000/SCT) | 5 | -| [Improving Human Action Recognition by Non-Action Classification](http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Improving_Human_Action_CVPR_2016_paper.html) | CVPR | [code](https://github.com/yangwangx/NonActionShot) | 4 | -| [Prior-Less Compressible Structure From Motion](http://openaccess.thecvf.com/content_cvpr_2016/html/Kong_Prior-Less_Compressible_Structure_CVPR_2016_paper.html) | CVPR | [code](https://github.com/kongchen1992/compressible-sfm) | 4 | -| [DenseCap: Fully Convolutional Localization Networks for Dense Captioning](http://openaccess.thecvf.com/content_cvpr_2016/html/Johnson_DenseCap_Fully_Convolutional_CVPR_2016_paper.html) | CVPR | [code](https://github.com/rampage644/densecap-tensorflow) | 4 | -| [Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization](http://openaccess.thecvf.com/content_cvpr_2016/html/Lu_Tensor_Robust_Principal_CVPR_2016_paper.html) | CVPR | [code](https://github.com/canyilu/Tensor-Robust-Principal-Component-Analysis-TRPCA) | 4 | -| [Force From Motion: Decoding Physical Sensation in a First Person Video](http://openaccess.thecvf.com/content_cvpr_2016/html/Park_Force_From_Motion_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jyhjinghwang/Force_from_Motion_Gravity_Models) | 3 | -| [Context-Aware Gaussian Fields for Non-Rigid Point Set Registration](http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Context-Aware_Gaussian_Fields_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gwang-cv/CA-LapGF-Demo) | 3 | -| [Using Spatial Order to Boost the Elimination of Incorrect Feature Matches](http://openaccess.thecvf.com/content_cvpr_2016/html/Talker_Using_Spatial_Order_CVPR_2016_paper.html) | CVPR | [code](https://github.com/liortalker/SpatialOrder) | 3 | -| [Fast Algorithms for Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Lavin_Fast_Algorithms_for_CVPR_2016_paper.html) | CVPR | [code](https://github.com/istoony/winograd-convolutional-nn) | 3 | +| [R-FCN: Object Detection via Region-based Fully Convolutional Networks](https://papers.nips.cc/paper/6465-r-fcn-object-detection-via-region-based-fully-convolutional-networks.pdf) | NIPS | [code](https://github.com/facebookresearch/Detectron) | 18356 | +| [Image Style Transfer Using Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Gatys_Image_Style_Transfer_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jcjohnson/neural-style) | 16435 | +| [Deep Residual Learning for Image Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/He_Deep_Residual_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/KaimingHe/deep-residual-networks) | 4468 | +| [Convolutional Pose Machines](http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Convolutional_Pose_Machines_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation) | 3260 | +| [Synthetic Data for Text Localisation in Natural Images](http://openaccess.thecvf.com/content_cvpr_2016/html/Gupta_Synthetic_Data_for_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ankush-me/SynthText) | 787 | +| [Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis](http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Combining_Markov_Random_CVPR_2016_paper.html) | CVPR | [code](https://github.com/chuanli11/CNNMRF) | 731 | +| [Instance-Aware Semantic Segmentation via Multi-Task Network Cascades](http://openaccess.thecvf.com/content_cvpr_2016/html/Dai_Instance-Aware_Semantic_Segmentation_CVPR_2016_paper.html) | CVPR | [code](https://github.com/daijifeng001/MNC) | 433 | +| [Learning Multi-Domain Convolutional Neural Networks for Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2016/html/Nam_Learning_Multi-Domain_Convolutional_CVPR_2016_paper.html) | CVPR | [code](https://github.com/HyeonseobNam/MDNet) | 350 | +| [Convolutional Two-Stream Network Fusion for Video Action Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/Feichtenhofer_Convolutional_Two-Stream_Network_CVPR_2016_paper.html) | CVPR | [code](https://github.com/feichtenhofer/twostreamfusion) | 342 | +| [Learning Deep Features for Discriminative Localization](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhou_Learning_Deep_Features_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jazzsaxmafia/Weakly_detector) | 323 | +| [Deep Metric Learning via Lifted Structured Feature Embedding](http://openaccess.thecvf.com/content_cvpr_2016/html/Song_Deep_Metric_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/rksltnl/Deep-Metric-Learning-CVPR16) | 251 | +| [Learning Deep Representations of Fine-Grained Visual Descriptions](http://openaccess.thecvf.com/content_cvpr_2016/html/Reed_Learning_Deep_Representations_CVPR_2016_paper.html) | CVPR | [code](https://github.com/reedscot/cvpr2016) | 229 | +| [Eye Tracking for Everyone](http://openaccess.thecvf.com/content_cvpr_2016/html/Krafka_Eye_Tracking_for_CVPR_2016_paper.html) | CVPR | [code](https://github.com/CSAILVision/GazeCapture) | 223 | +| [NetVLAD: CNN Architecture for Weakly Supervised Place Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/Arandjelovic_NetVLAD_CNN_Architecture_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Relja/netvlad) | 204 | +| [Staple: Complementary Learners for Real-Time Tracking](http://openaccess.thecvf.com/content_cvpr_2016/html/Bertinetto_Staple_Complementary_Learners_CVPR_2016_paper.html) | CVPR | [code](https://github.com/bertinetto/staple) | 183 | +| [Joint Unsupervised Learning of Deep Representations and Image Clusters](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Joint_Unsupervised_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jwyang/JULE.torch) | 182 | +| [Accurate Image Super-Resolution Using Very Deep Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Kim_Accurate_Image_Super-Resolution_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Jongchan/tensorflow-vdsr) | 182 | +| [Temporal Action Localization in Untrimmed Videos via Multi-Stage CNNs](http://openaccess.thecvf.com/content_cvpr_2016/html/Shou_Temporal_Action_Localization_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zhengshou/scnn) | 167 | +| [LocNet: Improving Localization Accuracy for Object Detection](http://openaccess.thecvf.com/content_cvpr_2016/html/Gidaris_LocNet_Improving_Localization_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gidariss/LocNet) | 155 | +| [Shallow and Deep Convolutional Networks for Saliency Prediction](http://openaccess.thecvf.com/content_cvpr_2016/html/Pan_Shallow_and_Deep_CVPR_2016_paper.html) | CVPR | [code](https://github.com/imatge-upc/saliency-2016-cvpr) | 153 | +| [Compact Bilinear Pooling](http://openaccess.thecvf.com/content_cvpr_2016/html/Gao_Compact_Bilinear_Pooling_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gy20073/compact_bilinear_pooling) | 148 | +| [Learning Compact Binary Descriptors With Unsupervised Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Lin_Learning_Compact_Binary_CVPR_2016_paper.html) | CVPR | [code](https://github.com/kevinlin311tw/cvpr16-deepbit) | 144 | +| [Dynamic Image Networks for Action Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/Bilen_Dynamic_Image_Networks_CVPR_2016_paper.html) | CVPR | [code](https://github.com/hbilen/dynamic-image-nets) | 133 | +| [Rethinking the Inception Architecture for Computer Vision](http://openaccess.thecvf.com/content_cvpr_2016/html/Szegedy_Rethinking_the_Inception_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Moodstocks/inception-v3.torch) | 130 | +| [Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images](http://openaccess.thecvf.com/content_cvpr_2016/html/Song_Deep_Sliding_Shapes_CVPR_2016_paper.html) | CVPR | [code](https://github.com/shurans/DeepSlidingShape) | 126 | +| [Context Encoders: Feature Learning by Inpainting](http://openaccess.thecvf.com/content_cvpr_2016/html/Pathak_Context_Encoders_Feature_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jazzsaxmafia/Inpainting) | 124 | +| [TI-Pooling: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Laptev_TI-Pooling_Transformation-Invariant_Pooling_CVPR_2016_paper.html) | CVPR | [code](https://github.com/dlaptev/TI-pooling) | 109 | +| [Weakly Supervised Deep Detection Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Bilen_Weakly_Supervised_Deep_CVPR_2016_paper.html) | CVPR | [code](https://github.com/hbilen/WSDDN) | 103 | +| [Natural Language Object Retrieval](http://openaccess.thecvf.com/content_cvpr_2016/html/Hu_Natural_Language_Object_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ronghanghu/natural-language-object-retrieval) | 100 | +| [Deeply-Recursive Convolutional Network for Image Super-Resolution](http://openaccess.thecvf.com/content_cvpr_2016/html/Kim_Deeply-Recursive_Convolutional_Network_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jiny2001/deeply-recursive-cnn-tf) | 96 | +| [Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network](http://openaccess.thecvf.com/content_cvpr_2016/html/Shi_Real-Time_Single_Image_CVPR_2016_paper.html) | CVPR | [code](https://github.com/leftthomas/ESPCN) | 92 | +| [Image Question Answering Using Convolutional Neural Network With Dynamic Parameter Prediction](http://openaccess.thecvf.com/content_cvpr_2016/html/Noh_Image_Question_Answering_CVPR_2016_paper.html) | CVPR | [code](https://github.com/HyeonwooNoh/DPPnet) | 88 | +| [Recurrent Convolutional Network for Video-Based Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2016/html/McLaughlin_Recurrent_Convolutional_Network_CVPR_2016_paper.html) | CVPR | [code](https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID) | 82 | +| [A Comparative Study for Single Image Blind Deblurring](http://openaccess.thecvf.com/content_cvpr_2016/html/Lai_A_Comparative_Study_CVPR_2016_paper.html) | CVPR | [code](https://github.com/phoenix104104/cvpr16_deblur_study) | 82 | +| [Neural Module Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Andreas_Neural_Module_Networks_CVPR_2016_paper.html) | CVPR | [code](https://github.com/HarshTrivedi/nmn-pytorch) | 81 | +| [Stacked Attention Networks for Image Question Answering](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Stacked_Attention_Networks_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zcyang/imageqa-san) | 78 | +| [Progressive Prioritized Multi-View Stereo](http://openaccess.thecvf.com/content_cvpr_2016/html/Locher_Progressive_Prioritized_Multi-View_CVPR_2016_paper.html) | CVPR | [code](https://github.com/alexlocher/hpmvs) | 73 | +| [Marr Revisited: 2D-3D Alignment via Surface Normal Prediction](http://openaccess.thecvf.com/content_cvpr_2016/html/Bansal_Marr_Revisited_2D-3D_CVPR_2016_paper.html) | CVPR | [code](https://github.com/aayushbansal/MarrRevisited) | 72 | +| [A Hierarchical Deep Temporal Model for Group Activity Recognition](http://openaccess.thecvf.com/content_cvpr_2016/html/Ibrahim_A_Hierarchical_Deep_CVPR_2016_paper.html) | CVPR | [code](https://github.com/mostafa-saad/deep-activity-rec) | 71 | +| [Towards Open Set Deep Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Bendale_Towards_Open_Set_CVPR_2016_paper.html) | CVPR | [code](https://github.com/abhijitbendale/OSDN) | 71 | +| [Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs](http://openaccess.thecvf.com/content_cvpr_2016/html/Ge_Robust_3D_Hand_CVPR_2016_paper.html) | CVPR | [code](https://github.com/geliuhao/CVPR2016_HandPoseEstimation) | 70 | +| [Bilateral Space Video Segmentation](http://openaccess.thecvf.com/content_cvpr_2016/html/Maerki_Bilateral_Space_Video_CVPR_2016_paper.html) | CVPR | [code](https://github.com/owang/BilateralVideoSegmentation) | 63 | +| [Deep Compositional Captioning: Describing Novel Object Categories Without Paired Training Data](http://openaccess.thecvf.com/content_cvpr_2016/html/Hendricks_Deep_Compositional_Captioning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/LisaAnne/DCC) | 57 | +| [Efficient 3D Room Shape Recovery From a Single Panorama](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Efficient_3D_Room_CVPR_2016_paper.html) | CVPR | [code](https://github.com/YANG-H/Panoramix) | 55 | +| [Non-Local Image Dehazing](http://openaccess.thecvf.com/content_cvpr_2016/html/Berman_Non-Local_Image_Dehazing_CVPR_2016_paper.html) | CVPR | [code](https://github.com/danaberman/non-local-dehazing) | 50 | +| [Video Segmentation via Object Flow](http://openaccess.thecvf.com/content_cvpr_2016/html/Tsai_Video_Segmentation_via_CVPR_2016_paper.html) | CVPR | [code](https://github.com/wasidennis/ObjectFlow) | 50 | +| [Deep Supervised Hashing for Fast Image Retrieval](http://openaccess.thecvf.com/content_cvpr_2016/html/Liu_Deep_Supervised_Hashing_CVPR_2016_paper.html) | CVPR | [code](https://github.com/yg33717/DSH_tensorflow) | 50 | +| [Deep Region and Multi-Label Learning for Facial Action Unit Detection](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhao_Deep_Region_and_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zkl20061823/DRML) | 43 | +| [CRAFT Objects From Images](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_CRAFT_Objects_From_CVPR_2016_paper.html) | CVPR | [code](https://github.com/byangderek/CRAFT) | 41 | +| [Slicing Convolutional Neural Network for Crowd Video Understanding](http://openaccess.thecvf.com/content_cvpr_2016/html/Shao_Slicing_Convolutional_Neural_CVPR_2016_paper.html) | CVPR | [code](https://github.com/amandajshao/Slicing-CNN) | 40 | +| [Sketch Me That Shoe](http://openaccess.thecvf.com/content_cvpr_2016/html/Yu_Sketch_Me_That_CVPR_2016_paper.html) | CVPR | [code](https://github.com/seuliufeng/DeepSBIR) | 39 | +| [Image Captioning With Semantic Attention](http://openaccess.thecvf.com/content_cvpr_2016/html/You_Image_Captioning_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/chapternewscu/image-captioning-with-semantic-attention) | 35 | +| [Deep Saliency With Encoded Low Level Distance Map and High Level Features](http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Deep_Saliency_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gylee1103/SaliencyELD) | 34 | +| [A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation](http://openaccess.thecvf.com/content_cvpr_2016/html/Perazzi_A_Benchmark_Dataset_CVPR_2016_paper.html) | CVPR | [code](https://github.com/davisvideochallenge/davis-matlab) | 33 | +| [A Dual-Source Approach for 3D Pose Estimation From a Single Image](http://openaccess.thecvf.com/content_cvpr_2016/html/Yasin_A_Dual-Source_Approach_CVPR_2016_paper.html) | CVPR | [code](https://github.com/iqbalu/3D_Pose_Estimation_CVPR2016) | 32 | +| [Learning Local Image Descriptors With Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions](http://openaccess.thecvf.com/content_cvpr_2016/html/G_Learning_Local_Image_CVPR_2016_paper.html) | CVPR | [code](https://github.com/vijaykbg/deep-patchmatch) | 30 | +| [Ordinal Regression With Multiple Output CNN for Age Estimation](http://openaccess.thecvf.com/content_cvpr_2016/html/Niu_Ordinal_Regression_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/luoyetx/OrdinalRegression) | 30 | +| [Structured Feature Learning for Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2016/html/Chu_Structured_Feature_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/chuxiaoselena/StructuredFeature) | 29 | +| [Unsupervised Learning of Edges](http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Unsupervised_Learning_of_CVPR_2016_paper.html) | CVPR | [code](https://github.com/happyharrycn/unsupervised_edges) | 29 | +| [PatchBatch: A Batch Augmented Loss for Optical Flow](http://openaccess.thecvf.com/content_cvpr_2016/html/Gadot_PatchBatch_A_Batch_CVPR_2016_paper.html) | CVPR | [code](https://github.com/DediGadot/PatchBatch) | 27 | +| [Dense Human Body Correspondences Using Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Dense_Human_Body_CVPR_2016_paper.html) | CVPR | [code](https://github.com/halimacc/DenseHumanBodyCorrespondences) | 27 | +| [Actionness Estimation Using Hybrid Fully Convolutional Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Actionness_Estimation_Using_CVPR_2016_paper.html) | CVPR | [code](https://github.com/wanglimin/Actionness-Estimation) | 26 | +| [You Only Look Once: Unified, Real-Time Object Detection](http://openaccess.thecvf.com/content_cvpr_2016/html/Redmon_You_Only_Look_CVPR_2016_paper.html) | CVPR | [code](https://github.com/andersy005/keras-yolo) | 26 | +| [Fast Training of Triplet-Based Deep Binary Embedding Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhuang_Fast_Training_of_CVPR_2016_paper.html) | CVPR | [code](https://github.com/xwzy/Triplet-deep-hash-pytorch) | 25 | +| [Recurrent Attention Models for Depth-Based Person Identification](http://openaccess.thecvf.com/content_cvpr_2016/html/Haque_Recurrent_Attention_Models_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ahaque/ram_person_id) | 24 | +| [Detecting Vanishing Points Using Global Image Context in a Non-Manhattan World](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhai_Detecting_Vanishing_Points_CVPR_2016_paper.html) | CVPR | [code](https://github.com/viibridges/gc-horizon-detector) | 22 | +| [First Person Action Recognition Using Deep Learned Descriptors](http://openaccess.thecvf.com/content_cvpr_2016/html/Singh_First_Person_Action_CVPR_2016_paper.html) | CVPR | [code](https://github.com/suriyasingh/EgoConvNet) | 21 | +| [Proposal Flow](http://openaccess.thecvf.com/content_cvpr_2016/html/Ham_Proposal_Flow_CVPR_2016_paper.html) | CVPR | [code](https://github.com/bsham/ProposalFlow) | 20 | +| [Scale-Aware Alignment of Hierarchical Image Segmentation](http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Scale-Aware_Alignment_of_CVPR_2016_paper.html) | CVPR | [code](https://github.com/yuhuayc/align-hier) | 20 | +| [Quantized Convolutional Neural Networks for Mobile Devices](http://openaccess.thecvf.com/content_cvpr_2016/html/Wu_Quantized_Convolutional_Neural_CVPR_2016_paper.html) | CVPR | [code](https://github.com/OluwoleOyetoke/Computer_Vision_Using_TensorFlowLite) | 20 | +| [Semantic Segmentation With Boundary Neural Fields](http://openaccess.thecvf.com/content_cvpr_2016/html/Bertasius_Semantic_Segmentation_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gberta/BNF_globalization) | 19 | +| [Single-Image Crowd Counting via Multi-Column Convolutional Neural Network](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Single-Image_Crowd_Counting_CVPR_2016_paper.html) | CVPR | [code](https://github.com/uestcchicken/crowd-counting-MCNN) | 19 | +| [Accumulated Stability Voting: A Robust Descriptor From Descriptors of Multiple Scales](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Accumulated_Stability_Voting_CVPR_2016_paper.html) | CVPR | [code](https://github.com/shamangary/ASV) | 19 | +| [Structure From Motion With Objects](http://openaccess.thecvf.com/content_cvpr_2016/html/Crocco_Structure_From_Motion_CVPR_2016_paper.html) | CVPR | [code](https://github.com/danylaksono/Android-SfM-client) | 17 | +| [Bottom-Up and Top-Down Reasoning With Hierarchical Rectified Gaussians](http://openaccess.thecvf.com/content_cvpr_2016/html/Hu_Bottom-Up_and_Top-Down_CVPR_2016_paper.html) | CVPR | [code](https://github.com/peiyunh/rg-mpii) | 16 | +| [Semantic Filtering](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Semantic_Filtering_CVPR_2016_paper.html) | CVPR | [code](https://github.com/shenshen-hungry/Semantic-CNN) | 16 | +| [Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network](http://openaccess.thecvf.com/content_cvpr_2016/html/Molchanov_Online_Detection_and_CVPR_2016_paper.html) | CVPR | [code](https://github.com/breadbread1984/R3DCNN) | 16 | +| [ReconNet: Non-Iterative Reconstruction of Images From Compressively Sensed Measurements](http://openaccess.thecvf.com/content_cvpr_2016/html/Kulkarni_ReconNet_Non-Iterative_Reconstruction_CVPR_2016_paper.html) | CVPR | [code](https://github.com/KuldeepKulkarni/ReconNet) | 15 | +| [Interactive Segmentation on RGBD Images via Cue Selection](http://openaccess.thecvf.com/content_cvpr_2016/html/Feng_Interactive_Segmentation_on_CVPR_2016_paper.html) | CVPR | [code](https://github.com/ZVsion/rgbd_image_segmentation) | 14 | +| [Object Contour Detection With a Fully Convolutional Encoder-Decoder Network](http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Object_Contour_Detection_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Raj-08/tensorflow-object-contour-detection) | 14 | +| [Automatic Content-Aware Color and Tone Stylization](http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Automatic_Content-Aware_Color_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jinyu121/ACACTS) | 12 | +| [Similarity Learning With Spatial Constraints for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Similarity_Learning_With_CVPR_2016_paper.html) | CVPR | [code](https://github.com/dapengchen123/SCSP) | 11 | +| [Personalizing Human Video Pose Estimation](http://openaccess.thecvf.com/content_cvpr_2016/html/Charles_Personalizing_Human_Video_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jjcharles/personalized_pose) | 10 | +| [Visually Indicated Sounds](http://openaccess.thecvf.com/content_cvpr_2016/html/Owens_Visually_Indicated_Sounds_CVPR_2016_paper.html) | CVPR | [code](https://github.com/kanchen-usc/VIG) | 9 | +| [Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification](http://openaccess.thecvf.com/content_cvpr_2016/html/Hou_Patch-Based_Convolutional_Neural_CVPR_2016_paper.html) | CVPR | [code](https://github.com/cheersyouran/cancer-detector) | 9 | +| [Region Ranking SVM for Image Classification](http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Region_Ranking_SVM_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zijunwei/Region-Ranking-SVM) | 8 | +| [Pairwise Matching Through Max-Weight Bipartite Belief Propagation](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Pairwise_Matching_Through_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zzhang1987/HungarianBP) | 8 | +| [Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled](http://openaccess.thecvf.com/content_cvpr_2016/html/Koller_Deep_Hand_How_CVPR_2016_paper.html) | CVPR | [code](https://github.com/neccam/TF-DeepHand) | 8 | +| [Cross-Stitch Networks for Multi-Task Learning](http://openaccess.thecvf.com/content_cvpr_2016/html/Misra_Cross-Stitch_Networks_for_CVPR_2016_paper.html) | CVPR | [code](https://github.com/helloyide/Cross-stitch-Networks-for-Multi-task-Learning) | 8 | +| [Learning a Discriminative Null Space for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Learning_a_Discriminative_CVPR_2016_paper.html) | CVPR | [code](https://github.com/lzrobots/NullSpace_ReID) | 8 | +| [Efficient Deep Learning for Stereo Matching](http://openaccess.thecvf.com/content_cvpr_2016/html/Luo_Efficient_Deep_Learning_CVPR_2016_paper.html) | CVPR | [code](https://github.com/haojeng-wang/dl_stereo_matching) | 7 | +| [Globally Optimal Manhattan Frame Estimation in Real-Time](http://openaccess.thecvf.com/content_cvpr_2016/html/Joo_Globally_Optimal_Manhattan_CVPR_2016_paper.html) | CVPR | [code](https://github.com/Kyungdon/mf_estimation) | 7 | +| [Where to Look: Focus Regions for Visual Question Answering](http://openaccess.thecvf.com/content_cvpr_2016/html/Shih_Where_to_Look_CVPR_2016_paper.html) | CVPR | [code](https://github.com/kevjshih/wtl_vqa) | 7 | +| [Detecting Migrating Birds at Night](http://openaccess.thecvf.com/content_cvpr_2016/html/Huang_Detecting_Migrating_Birds_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jbhuang0604/BirdDetection) | 7 | +| [Unsupervised Learning From Narrated Instruction Videos](http://openaccess.thecvf.com/content_cvpr_2016/html/Alayrac_Unsupervised_Learning_From_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jalayrac/instructionVideos) | 7 | +| [Efficient and Robust Color Consistency for Community Photo Collections](http://openaccess.thecvf.com/content_cvpr_2016/html/Park_Efficient_and_Robust_CVPR_2016_paper.html) | CVPR | [code](https://github.com/syncle/photo_consistency) | 7 | +| [Recurrent Attentional Networks for Saliency Detection](http://openaccess.thecvf.com/content_cvpr_2016/html/Kuen_Recurrent_Attentional_Networks_CVPR_2016_paper.html) | CVPR | [code](https://github.com/zhangxiaoning666/PAGR) | 7 | +| [3D Shape Attributes](http://openaccess.thecvf.com/content_cvpr_2016/html/Fouhey_3D_Shape_Attributes_CVPR_2016_paper.html) | CVPR | [code](https://github.com/petermalcolm/estimate3DStep) | 6 | +| [Beyond Local Search: Tracking Objects Everywhere With Instance-Specific Proposals](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhu_Beyond_Local_Search_CVPR_2016_paper.html) | CVPR | [code](https://github.com/GaoCode/EBT) | 5 | +| [Functional Faces: Groupwise Dense Correspondence Using Functional Maps](http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Functional_Faces_Groupwise_CVPR_2016_paper.html) | CVPR | [code](https://github.com/cazhang/funcFaces) | 5 | +| [Visual Tracking Using Attention-Modulated Disintegration and Integration](http://openaccess.thecvf.com/content_cvpr_2016/html/Choi_Visual_Tracking_Using_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jongwon20000/SCT) | 5 | +| [Improving Human Action Recognition by Non-Action Classification](http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Improving_Human_Action_CVPR_2016_paper.html) | CVPR | [code](https://github.com/yangwangx/NonActionShot) | 4 | +| [Prior-Less Compressible Structure From Motion](http://openaccess.thecvf.com/content_cvpr_2016/html/Kong_Prior-Less_Compressible_Structure_CVPR_2016_paper.html) | CVPR | [code](https://github.com/kongchen1992/compressible-sfm) | 4 | +| [DenseCap: Fully Convolutional Localization Networks for Dense Captioning](http://openaccess.thecvf.com/content_cvpr_2016/html/Johnson_DenseCap_Fully_Convolutional_CVPR_2016_paper.html) | CVPR | [code](https://github.com/rampage644/densecap-tensorflow) | 4 | +| [Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization](http://openaccess.thecvf.com/content_cvpr_2016/html/Lu_Tensor_Robust_Principal_CVPR_2016_paper.html) | CVPR | [code](https://github.com/canyilu/Tensor-Robust-Principal-Component-Analysis-TRPCA) | 4 | +| [Force From Motion: Decoding Physical Sensation in a First Person Video](http://openaccess.thecvf.com/content_cvpr_2016/html/Park_Force_From_Motion_CVPR_2016_paper.html) | CVPR | [code](https://github.com/jyhjinghwang/Force_from_Motion_Gravity_Models) | 3 | +| [Context-Aware Gaussian Fields for Non-Rigid Point Set Registration](http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Context-Aware_Gaussian_Fields_CVPR_2016_paper.html) | CVPR | [code](https://github.com/gwang-cv/CA-LapGF-Demo) | 3 | +| [Using Spatial Order to Boost the Elimination of Incorrect Feature Matches](http://openaccess.thecvf.com/content_cvpr_2016/html/Talker_Using_Spatial_Order_CVPR_2016_paper.html) | CVPR | [code](https://github.com/liortalker/SpatialOrder) | 3 | +| [Fast Algorithms for Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2016/html/Lavin_Fast_Algorithms_for_CVPR_2016_paper.html) | CVPR | [code](https://github.com/istoony/winograd-convolutional-nn) | 3 |
↥ back to top @@ -1431,115 +1443,115 @@ Use [this](https://github.com/zziz/pwc/issues/11) thread to request us your favo ## 2015 | Title | Conf | Code | Stars | |:--------|:--------:|:--------:|:--------:| -| [Faster R-CNN: Towards Real-Time Object Detectionwith Region Proposal Networks](https://papers.nips.cc/paper/5638-faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks.pdf) | NIPS | [code](https://github.com/facebookresearch/Detectron) | 18356 | -| [Fast R-CNN](http://openaccess.thecvf.com/content_iccv_2015/html/Girshick_Fast_R-CNN_ICCV_2015_paper.html) | ICCV | [code](https://github.com/facebookresearch/Detectron) | 18356 | -| [Conditional Random Fields as Recurrent Neural Networks](http://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Conditional_Random_Fields_ICCV_2015_paper.html) | ICCV | [code](https://github.com/torrvision/crfasrnn) | 1189 | -| [Fully Convolutional Networks for Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2015/html/Long_Fully_Convolutional_Networks_2015_CVPR_paper.html) | CVPR | [code](https://github.com/shekkizh/FCN.tensorflow) | 911 | -| [Learning to Track: Online Multi-Object Tracking by Decision Making](http://openaccess.thecvf.com/content_iccv_2015/html/Xiang_Learning_to_Track_ICCV_2015_paper.html) | ICCV | [code](https://github.com/yuxng/MDP_Tracking) | 308 | -| [Learning to Compare Image Patches via Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2015/html/Zagoruyko_Learning_to_Compare_2015_CVPR_paper.html) | CVPR | [code](https://github.com/szagoruyko/cvpr15deepcompare) | 300 | -| [Learning Deconvolution Network for Semantic Segmentation](http://openaccess.thecvf.com/content_iccv_2015/html/Noh_Learning_Deconvolution_Network_ICCV_2015_paper.html) | ICCV | [code](https://github.com/HyeonwooNoh/DeconvNet) | 296 | -| [Single Image Super-Resolution From Transformed Self-Exemplars](http://openaccess.thecvf.com/content_cvpr_2015/html/Huang_Single_Image_Super-Resolution_2015_CVPR_paper.html) | CVPR | [code](https://github.com/jbhuang0604/SelfExSR) | 289 | -| [Sequence to Sequence - Video to Text](http://openaccess.thecvf.com/content_iccv_2015/html/Venugopalan_Sequence_to_Sequence_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jazzsaxmafia/video_to_sequence) | 239 | -| [Deep Colorization](http://openaccess.thecvf.com/content_iccv_2015/html/Cheng_Deep_Colorization_ICCV_2015_paper.html) | ICCV | [code](https://github.com/richzhang/colorization-pytorch) | 198 | -| [Deep Neural Decision Forests](http://openaccess.thecvf.com/content_iccv_2015/html/Kontschieder_Deep_Neural_Decision_ICCV_2015_paper.html) | ICCV | [code](https://github.com/chrischoy/fully-differentiable-deep-ndf-tf) | 192 | -| [Hierarchical Convolutional Features for Visual Tracking](http://openaccess.thecvf.com/content_iccv_2015/html/Ma_Hierarchical_Convolutional_Features_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jbhuang0604/CF2) | 179 | -| [Render for CNN: Viewpoint Estimation in Images Using CNNs Trained With Rendered 3D Model Views](http://openaccess.thecvf.com/content_iccv_2015/html/Su_Render_for_CNN_ICCV_2015_paper.html) | ICCV | [code](https://github.com/ShapeNet/RenderForCNN) | 176 | -| [Realtime Edge-Based Visual Odometry for a Monocular Camera](http://openaccess.thecvf.com/content_iccv_2015/html/Tarrio_Realtime_Edge-Based_Visual_ICCV_2015_paper.html) | ICCV | [code](https://github.com/JuanTarrio/rebvo) | 175 | -| [Understanding Deep Image Representations by Inverting Them](http://openaccess.thecvf.com/content_cvpr_2015/html/Mahendran_Understanding_Deep_Image_2015_CVPR_paper.html) | CVPR | [code](https://github.com/aravindhm/deep-goggle) | 154 | -| [Context-Aware CNNs for Person Head Detection](http://openaccess.thecvf.com/content_iccv_2015/html/Vu_Context-Aware_CNNs_for_ICCV_2015_paper.html) | ICCV | [code](https://github.com/aosokin/cnn_head_detection) | 153 | -| [Show and Tell: A Neural Image Caption Generator](http://openaccess.thecvf.com/content_cvpr_2015/html/Vinyals_Show_and_Tell_2015_CVPR_paper.html) | CVPR | [code](https://github.com/KranthiGV/Pretrained-Show-and-Tell-model) | 141 | -| [Face Alignment by Coarse-to-Fine Shape Searching](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html) | CVPR | [code](https://github.com/zhusz/CVPR15-CFSS) | 140 | -| [An Improved Deep Learning Architecture for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2015/html/Ahmed_An_Improved_Deep_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Ning-Ding/Implementation-CVPR2015-CNN-for-ReID) | 127 | -| [FaceNet: A Unified Embedding for Face Recognition and Clustering](http://openaccess.thecvf.com/content_cvpr_2015/html/Schroff_FaceNet_A_Unified_2015_CVPR_paper.html) | CVPR | [code](https://github.com/liorshk/facenet_pytorch) | 124 | -| [Depth-Based Hand Pose Estimation: Data, Methods, and Challenges](http://openaccess.thecvf.com/content_iccv_2015/html/Supancic_Depth-Based_Hand_Pose_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jsupancic/deep_hand_pose) | 121 | -| [DynamicFusion: Reconstruction and Tracking of Non-Rigid Scenes in Real-Time](http://openaccess.thecvf.com/content_cvpr_2015/html/Newcombe_DynamicFusion_Reconstruction_and_2015_CVPR_paper.html) | CVPR | [code](https://github.com/mihaibujanca/dynamicfusion) | 118 | -| [Massively Parallel Multiview Stereopsis by Surface Normal Diffusion](http://openaccess.thecvf.com/content_iccv_2015/html/Galliani_Massively_Parallel_Multiview_ICCV_2015_paper.html) | ICCV | [code](https://github.com/kysucix/gipuma) | 105 | -| [Learning to Propose Objects](http://openaccess.thecvf.com/content_cvpr_2015/html/Krahenbuhl_Learning_to_Propose_2015_CVPR_paper.html) | CVPR | [code](https://github.com/philkr/lpo) | 91 | -| [Learning Spatially Regularized Correlation Filters for Visual Tracking](http://openaccess.thecvf.com/content_iccv_2015/html/Danelljan_Learning_Spatially_Regularized_ICCV_2015_paper.html) | ICCV | [code](https://github.com/lifeng9472/STRCF) | 86 | -| [A Convolutional Neural Network Cascade for Face Detection](http://openaccess.thecvf.com/content_cvpr_2015/html/Li_A_Convolutional_Neural_2015_CVPR_paper.html) | CVPR | [code](https://github.com/mks0601/A-Convolutional-Neural-Network-Cascade-for-Face-Detection) | 85 | -| [Discriminative Learning of Deep Convolutional Feature Point Descriptors](http://openaccess.thecvf.com/content_iccv_2015/html/Simo-Serra_Discriminative_Learning_of_ICCV_2015_paper.html) | ICCV | [code](https://github.com/etrulls/deepdesc-release) | 77 | -| [Unsupervised Visual Representation Learning by Context Prediction](http://openaccess.thecvf.com/content_iccv_2015/html/Doersch_Unsupervised_Visual_Representation_ICCV_2015_paper.html) | ICCV | [code](https://github.com/cdoersch/deepcontext) | 73 | -| [Deep Neural Networks Are Easily Fooled: High Confidence Predictions for Unrecognizable Images](http://openaccess.thecvf.com/content_cvpr_2015/html/Nguyen_Deep_Neural_Networks_2015_CVPR_paper.html) | CVPR | [code](https://github.com/abhijitbendale/OSDN) | 71 | -| [Deep Filter Banks for Texture Recognition and Segmentation](http://openaccess.thecvf.com/content_cvpr_2015/html/Cimpoi_Deep_Filter_Banks_2015_CVPR_paper.html) | CVPR | [code](https://github.com/mcimpoi/deep-fbanks) | 68 | -| [Saliency Detection by Multi-Context Deep Learning](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhao_Saliency_Detection_by_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Robert0812/deepsaldet) | 66 | -| [Multi-Objective Convolutional Learning for Face Labeling](http://openaccess.thecvf.com/content_cvpr_2015/html/Liu_Multi-Objective_Convolutional_Learning_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Liusifei/Face_Parsing_2016) | 55 | -| [Finding Action Tubes](http://openaccess.thecvf.com/content_cvpr_2015/html/Gkioxari_Finding_Action_Tubes_2015_CVPR_paper.html) | CVPR | [code](https://github.com/gkioxari/ActionTubes) | 51 | -| [Category-Specific Object Reconstruction From a Single Image](http://openaccess.thecvf.com/content_cvpr_2015/html/Kar_Category-Specific_Object_Reconstruction_2015_CVPR_paper.html) | CVPR | [code](https://github.com/akar43/CategoryShapes) | 48 | -| [Convolutional Color Constancy](http://openaccess.thecvf.com/content_iccv_2015/html/Barron_Convolutional_Color_Constancy_ICCV_2015_paper.html) | ICCV | [code](https://github.com/yuanming-hu/fc4) | 47 | -| [Face Flow](http://openaccess.thecvf.com/content_iccv_2015/html/Snape_Face_Flow_ICCV_2015_paper.html) | ICCV | [code](https://github.com/shashanktyagi/HyperFace-TensorFlow-implementation) | 45 | -| [P-CNN: Pose-Based CNN Features for Action Recognition](http://openaccess.thecvf.com/content_iccv_2015/html/Cheron_P-CNN_Pose-Based_CNN_ICCV_2015_paper.html) | ICCV | [code](https://github.com/gcheron/P-CNN) | 45 | -| [Learning From Massive Noisy Labeled Data for Image Classification](http://openaccess.thecvf.com/content_cvpr_2015/html/Xiao_Learning_From_Massive_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Cysu/noisy_label) | 45 | -| [Image Specificity](http://openaccess.thecvf.com/content_cvpr_2015/html/Jas_Image_Specificity_2015_CVPR_paper.html) | CVPR | [code](https://github.com/burliEnterprises/tensorflow-image-classifier) | 40 | -| [Predicting Depth, Surface Normals and Semantic Labels With a Common Multi-Scale Convolutional Architecture](http://openaccess.thecvf.com/content_iccv_2015/html/Eigen_Predicting_Depth_Surface_ICCV_2015_paper.html) | ICCV | [code](https://github.com/Rostifar/NYUDepthNet) | 35 | -| [Neural Activation Constellations: Unsupervised Part Model Discovery With Convolutional Networks](http://openaccess.thecvf.com/content_iccv_2015/html/Simon_Neural_Activation_Constellations_ICCV_2015_paper.html) | ICCV | [code](https://github.com/cvjena/part_constellation_models) | 35 | -| [VQA: Visual Question Answering](http://openaccess.thecvf.com/content_iccv_2015/html/Antol_VQA_Visual_Question_ICCV_2015_paper.html) | ICCV | [code](https://github.com/imatge-upc/vqa-2016-cvprw) | 35 | -| [Mid-Level Deep Pattern Mining](http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Mid-Level_Deep_Pattern_2015_CVPR_paper.html) | CVPR | [code](https://github.com/yaoliUoA/MDPM) | 34 | -| [PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization](http://openaccess.thecvf.com/content_iccv_2015/html/Kendall_PoseNet_A_Convolutional_ICCV_2015_paper.html) | ICCV | [code](https://github.com/futurely/deep-camera-relocalization) | 34 | -| [Parsimonious Labeling](http://openaccess.thecvf.com/content_iccv_2015/html/Dokania_Parsimonious_Labeling_ICCV_2015_paper.html) | ICCV | [code](https://github.com/aimerykong/Pixel-Attentional-Gating) | 33 | -| [Car That Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models](http://openaccess.thecvf.com/content_iccv_2015/html/Jain_Car_That_Knows_ICCV_2015_paper.html) | ICCV | [code](https://github.com/asheshjain399/ICCV2015_Brain4Cars) | 33 | -| [Recurrent Convolutional Neural Network for Object Recognition](http://openaccess.thecvf.com/content_cvpr_2015/html/Liang_Recurrent_Convolutional_Neural_2015_CVPR_paper.html) | CVPR | [code](https://github.com/JimLee4530/RCNN) | 32 | -| [TILDE: A Temporally Invariant Learned DEtector](http://openaccess.thecvf.com/content_cvpr_2015/html/Verdie_TILDE_A_Temporally_2015_CVPR_paper.html) | CVPR | [code](https://github.com/kmyid/TILDE) | 30 | -| [In Defense of Color-Based Model-Free Tracking](http://openaccess.thecvf.com/content_cvpr_2015/html/Possegger_In_Defense_of_2015_CVPR_paper.html) | CVPR | [code](https://github.com/foolwood/DAT) | 30 | -| [Fast Bilateral-Space Stereo for Synthetic Defocus](http://openaccess.thecvf.com/content_cvpr_2015/html/Barron_Fast_Bilateral-Space_Stereo_2015_CVPR_paper.html) | CVPR | [code](https://github.com/tvandenzegel/fast_bilateral_space_stereo) | 29 | -| [Phase-Based Frame Interpolation for Video](http://openaccess.thecvf.com/content_cvpr_2015/html/Meyer_Phase-Based_Frame_Interpolation_2015_CVPR_paper.html) | CVPR | [code](https://github.com/owang/PhaseBasedInterpolation) | 28 | -| [Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhu_Understanding_Tools_Task-Oriented_2015_CVPR_paper.html) | CVPR | [code](https://github.com/xiaozhuchacha/Kinect2Toolbox) | 27 | -| [Deeply Learned Attributes for Crowded Scene Understanding](http://openaccess.thecvf.com/content_cvpr_2015/html/Shao_Deeply_Learned_Attributes_2015_CVPR_paper.html) | CVPR | [code](https://github.com/amandajshao/www_deep_crowd) | 27 | -| [Unconstrained 3D Face Reconstruction](http://openaccess.thecvf.com/content_cvpr_2015/html/Roth_Unconstrained_3D_Face_2015_CVPR_paper.html) | CVPR | [code](https://github.com/NJUPole/CVPR2015-Unconstrained-3D-Face-Reconstruction) | 26 | -| [Viewpoints and Keypoints](http://openaccess.thecvf.com/content_cvpr_2015/html/Tulsiani_Viewpoints_and_Keypoints_2015_CVPR_paper.html) | CVPR | [code](https://github.com/shubhtuls/ViewpointsAndKeypoints) | 25 | -| [Holistically-Nested Edge Detection](http://openaccess.thecvf.com/content_iccv_2015/html/Xie_Holistically-Nested_Edge_Detection_ICCV_2015_paper.html) | ICCV | [code](https://github.com/s9xie/hed_release-deprecated) | 25 | -| [Going Deeper With Convolutions](http://openaccess.thecvf.com/content_cvpr_2015/html/Szegedy_Going_Deeper_With_2015_CVPR_paper.html) | CVPR | [code](https://github.com/nutszebra/googlenet) | 25 | -| [Reconstructing the World* in Six Days *(As Captured by the Yahoo 100 Million Image Dataset)](http://openaccess.thecvf.com/content_cvpr_2015/html/Heinly_Reconstructing_the_World_2015_CVPR_paper.html) | CVPR | [code](https://github.com/jheinly/streaming_connected_component_discovery) | 25 | -| [Data-Driven 3D Voxel Patterns for Object Category Recognition](http://openaccess.thecvf.com/content_cvpr_2015/html/Xiang_Data-Driven_3D_Voxel_2015_CVPR_paper.html) | CVPR | [code](https://github.com/yuxng/3DVP) | 24 | -| [L0TV: A New Method for Image Restoration in the Presence of Impulse Noise](http://openaccess.thecvf.com/content_cvpr_2015/html/Yuan_L0TV_A_New_2015_CVPR_paper.html) | CVPR | [code](https://github.com/peisuke/L0TV) | 22 | -| [Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Beyond_Frontal_Faces_2015_CVPR_paper.html) | CVPR | [code](https://github.com/sciencefans/Beyond-Frontal-Faces) | 21 | -| [Understanding Deep Features With Computer-Generated Imagery](http://openaccess.thecvf.com/content_iccv_2015/html/Aubry_Understanding_Deep_Features_ICCV_2015_paper.html) | ICCV | [code](https://github.com/mathieuaubry/features_analysis) | 19 | -| [HICO: A Benchmark for Recognizing Human-Object Interactions in Images](http://openaccess.thecvf.com/content_iccv_2015/html/Chao_HICO_A_Benchmark_ICCV_2015_paper.html) | ICCV | [code](https://github.com/ywchao/hico_benchmark) | 18 | -| [Structured Feature Selection](http://openaccess.thecvf.com/content_iccv_2015/html/Gao_Structured_Feature_Selection_ICCV_2015_paper.html) | ICCV | [code](https://github.com/csliangdu/FSASL) | 17 | -| [Learning Large-Scale Automatic Image Colorization](http://openaccess.thecvf.com/content_iccv_2015/html/Deshpande_Learning_Large-Scale_Automatic_ICCV_2015_paper.html) | ICCV | [code](https://github.com/aditya12agd5/iccv15_lscolorization) | 17 | -| [Semantic Component Analysis](http://openaccess.thecvf.com/content_iccv_2015/html/Murdock_Semantic_Component_Analysis_ICCV_2015_paper.html) | ICCV | [code](https://github.com/aubry74/visual-word2vec) | 17 | -| [Simultaneous Feature Learning and Hash Coding With Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2015/html/Lai_Simultaneous_Feature_Learning_2015_CVPR_paper.html) | CVPR | [code](https://github.com/HYPJUDY/caffe-dnnh) | 16 | -| [3D Object Reconstruction From Hand-Object Interactions](http://openaccess.thecvf.com/content_iccv_2015/html/Tzionas_3D_Object_Reconstruction_ICCV_2015_paper.html) | ICCV | [code](https://github.com/dimtziwnas/InHandScanningICCV15_Reconstruction) | 15 | -| [Learning Temporal Embeddings for Complex Video Analysis](http://openaccess.thecvf.com/content_iccv_2015/html/Ramanathan_Learning_Temporal_Embeddings_ICCV_2015_paper.html) | ICCV | [code](https://github.com/eevignesh/videovector) | 14 | -| [Learning to See by Moving](http://openaccess.thecvf.com/content_iccv_2015/html/Agrawal_Learning_to_See_ICCV_2015_paper.html) | ICCV | [code](https://github.com/pulkitag/learning-to-see-by-moving) | 14 | -| [Reflection Removal Using Ghosting Cues](http://openaccess.thecvf.com/content_cvpr_2015/html/Shih_Reflection_Removal_Using_2015_CVPR_paper.html) | CVPR | [code](https://github.com/thongnguyendev/single_image) | 14 | -| [Where to Buy It: Matching Street Clothing Photos in Online Shops](http://openaccess.thecvf.com/content_iccv_2015/html/Kiapour_Where_to_Buy_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jfuentescpp/where_to_buy_it) | 14 | -| [Oriented Edge Forests for Boundary Detection](http://openaccess.thecvf.com/content_cvpr_2015/html/Hallman_Oriented_Edge_Forests_2015_CVPR_paper.html) | CVPR | [code](https://github.com/samhallman/oef) | 13 | -| [A Large-Scale Car Dataset for Fine-Grained Categorization and Verification](http://openaccess.thecvf.com/content_cvpr_2015/html/Yang_A_Large-Scale_Car_2015_CVPR_paper.html) | CVPR | [code](https://github.com/bogger/caffe-multigpu) | 11 | -| [Appearance-Based Gaze Estimation in the Wild](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Appearance-Based_Gaze_Estimation_2015_CVPR_paper.html) | CVPR | [code](https://github.com/trakaros/MPIIGaze) | 10 | -| [Learning a Descriptor-Specific 3D Keypoint Detector](http://openaccess.thecvf.com/content_iccv_2015/html/Salti_Learning_a_Descriptor-Specific_ICCV_2015_paper.html) | ICCV | [code](https://github.com/CVLAB-Unibo/Keypoint-Learning) | 10 | -| [Robust Image Filtering Using Joint Static and Dynamic Guidance](http://openaccess.thecvf.com/content_cvpr_2015/html/Ham_Robust_Image_Filtering_2015_CVPR_paper.html) | CVPR | [code](https://github.com/bsham/SDFilter) | 10 | -| [Partial Person Re-Identification](http://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Partial_Person_Re-Identification_ICCV_2015_paper.html) | ICCV | [code](https://github.com/lingxiao-he/Deep-Spatial-Feature-Reconstruction-for-Partial-Person-Re-identification) | 9 | -| [High Quality Structure From Small Motion for Rolling Shutter Cameras](http://openaccess.thecvf.com/content_iccv_2015/html/Im_High_Quality_Structure_ICCV_2015_paper.html) | ICCV | [code](https://github.com/sunghoonim/SfSM) | 9 | -| [Boosting Object Proposals: From Pascal to COCO](http://openaccess.thecvf.com/content_iccv_2015/html/Pont-Tuset_Boosting_Object_Proposals_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jponttuset/BOP) | 8 | -| [Convolutional Channel Features](http://openaccess.thecvf.com/content_iccv_2015/html/Yang_Convolutional_Channel_Features_ICCV_2015_paper.html) | ICCV | [code](https://github.com/byangderek/CCF) | 8 | -| [Live Repetition Counting](http://openaccess.thecvf.com/content_iccv_2015/html/Levy_Live_Repetition_Counting_ICCV_2015_paper.html) | ICCV | [code](https://github.com/tomrunia/DeepRepICCV2015) | 8 | -| [Unsupervised Learning of Visual Representations Using Videos](http://openaccess.thecvf.com/content_iccv_2015/html/Wang_Unsupervised_Learning_of_ICCV_2015_paper.html) | ICCV | [code](https://github.com/coreylynch/unsupervised-triplet-embedding) | 8 | -| [Supervised Discrete Hashing](http://openaccess.thecvf.com/content_cvpr_2015/html/Shen_Supervised_Discrete_Hashing_2015_CVPR_paper.html) | CVPR | [code](https://github.com/goukoutaki/FSDH) | 7 | -| [Multi-View Convolutional Neural Networks for 3D Shape Recognition](http://openaccess.thecvf.com/content_iccv_2015/html/Su_Multi-View_Convolutional_Neural_ICCV_2015_paper.html) | ICCV | [code](https://github.com/shawnxu1318/MVCNN-Multi-View-Convolutional-Neural-Networks) | 7 | -| [Simpler Non-Parametric Methods Provide as Good or Better Results to Multiple-Instance Learning](http://openaccess.thecvf.com/content_iccv_2015/html/Venkatesan_Simpler_Non-Parametric_Methods_ICCV_2015_paper.html) | ICCV | [code](https://github.com/ragavvenkatesan/np-mil) | 7 | -| [Finding Distractors In Images](http://openaccess.thecvf.com/content_cvpr_2015/html/Fried_Finding_Distractors_In_2015_CVPR_paper.html) | CVPR | [code](https://github.com/ohadf/distractors) | 7 | -| [Piecewise Flat Embedding for Image Segmentation](http://openaccess.thecvf.com/content_iccv_2015/html/Yu_Piecewise_Flat_Embedding_ICCV_2015_paper.html) | ICCV | [code](https://github.com/chaoweifang/PFE) | 7 | -| [Long-Term Correlation Tracking](http://openaccess.thecvf.com/content_cvpr_2015/html/Ma_Long-Term_Correlation_Tracking_2015_CVPR_paper.html) | CVPR | [code](https://github.com/malreddysid/long-term-correlation-tracking) | 6 | -| [Towards Open World Recognition](http://openaccess.thecvf.com/content_cvpr_2015/html/Bendale_Towards_Open_World_2015_CVPR_paper.html) | CVPR | [code](https://github.com/abhijitbendale/OWR) | 6 | -| [Pooled Motion Features for First-Person Videos](http://openaccess.thecvf.com/content_cvpr_2015/html/Ryoo_Pooled_Motion_Features_2015_CVPR_paper.html) | CVPR | [code](https://github.com/USCDataScience/hadoop-pot) | 6 | -| [Simultaneous Deep Transfer Across Domains and Tasks](http://openaccess.thecvf.com/content_iccv_2015/html/Tzeng_Simultaneous_Deep_Transfer_ICCV_2015_paper.html) | ICCV | [code](https://github.com/mahfujau/domain_adaptation_iccv15) | 6 | -| [What Makes an Object Memorable?](http://openaccess.thecvf.com/content_iccv_2015/html/Dubey_What_Makes_an_ICCV_2015_paper.html) | ICCV | [code](https://github.com/qixuanHou/Mapping-My-Break) | 5 | -| [Mining Semantic Affordances of Visual Object Categories](http://openaccess.thecvf.com/content_cvpr_2015/html/Chao_Mining_Semantic_Affordances_2015_CVPR_paper.html) | CVPR | [code](https://github.com/ywchao/semantic_affordance) | 5 | -| [Dense Semantic Correspondence Where Every Pixel is a Classifier](http://openaccess.thecvf.com/content_iccv_2015/html/Bristow_Dense_Semantic_Correspondence_ICCV_2015_paper.html) | ICCV | [code](https://github.com/hbristow/epic) | 5 | -| [Segment Graph Based Image Filtering: Fast Structure-Preserving Smoothing](http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Segment_Graph_Based_ICCV_2015_paper.html) | ICCV | [code](https://github.com/feihuzhang/SGF) | 5 | -| [Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization](http://openaccess.thecvf.com/content_cvpr_2015/html/Oh_Fast_Randomized_Singular_2015_CVPR_paper.html) | CVPR | [code](https://github.com/HlG4399/FRSVT) | 5 | -| [Unsupervised Generation of a Viewpoint Annotated Car Dataset From Videos](http://openaccess.thecvf.com/content_iccv_2015/html/Sedaghat_Unsupervised_Generation_of_ICCV_2015_paper.html) | ICCV | [code](https://github.com/lmb-freiburg/unsup-car-dataset) | 5 | -| [Multi-Label Cross-Modal Retrieval](http://openaccess.thecvf.com/content_iccv_2015/html/Ranjan_Multi-Label_Cross-Modal_Retrieval_ICCV_2015_paper.html) | ICCV | [code](https://github.com/Viresh-R/ml-CCA) | 4 | -| [Superdifferential Cuts for Binary Energies](http://openaccess.thecvf.com/content_cvpr_2015/html/Taniai_Superdifferential_Cuts_for_2015_CVPR_paper.html) | CVPR | [code](https://github.com/t-taniai/SDC_CVPR2015) | 4 | -| [Pose Induction for Novel Object Categories](http://openaccess.thecvf.com/content_iccv_2015/html/Tulsiani_Pose_Induction_for_ICCV_2015_paper.html) | ICCV | [code](https://github.com/shubhtuls/poseInduction) | 4 | -| [Efficient Minimal-Surface Regularization of Perspective Depth Maps in Variational Stereo](http://openaccess.thecvf.com/content_cvpr_2015/html/Graber_Efficient_Minimal-Surface_Regularization_2015_CVPR_paper.html) | CVPR | [code](https://github.com/VLOGroup/surface-area-regularization) | 4 | -| [Low-Rank Matrix Factorization Under General Mixture Noise Distributions](http://openaccess.thecvf.com/content_iccv_2015/html/Cao_Low-Rank_Matrix_Factorization_ICCV_2015_paper.html) | ICCV | [code](https://github.com/xiangyongcao/PMoEP) | 4 | -| [Robust Saliency Detection via Regularized Random Walks Ranking](http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Robust_Saliency_Detection_2015_CVPR_paper.html) | CVPR | [code](https://github.com/yuanyc06/rr) | 3 | -| [Simultaneous Video Defogging and Stereo Reconstruction](http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Simultaneous_Video_Defogging_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Lashuk1729/DIP-Project-Video-Dehazing) | 3 | -| [Hyperspectral Super-Resolution by Coupled Spectral Unmixing](http://openaccess.thecvf.com/content_iccv_2015/html/Lanaras_Hyperspectral_Super-Resolution_by_ICCV_2015_paper.html) | ICCV | [code](https://github.com/lanha/SupResPALM) | 3 | -| [Oriented Object Proposals](http://openaccess.thecvf.com/content_iccv_2015/html/He_Oriented_Object_Proposals_ICCV_2015_paper.html) | ICCV | [code](https://github.com/frutuozo29/WebServiceRESTFul) | 3 | -| [kNN Hashing With Factorized Neighborhood Representation](http://openaccess.thecvf.com/content_iccv_2015/html/Ding_kNN_Hashing_With_ICCV_2015_paper.html) | ICCV | [code](https://github.com/dooook/kNN-hashing) | 3 | -| [Minimum Barrier Salient Object Detection at 80 FPS](http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Minimum_Barrier_Salient_ICCV_2015_paper.html) | ICCV | [code](https://github.com/coderSkyChen/MBS_Cplus_c-) | 3 | +| [Faster R-CNN: Towards Real-Time Object Detectionwith Region Proposal Networks](https://papers.nips.cc/paper/5638-faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks.pdf) | NIPS | [code](https://github.com/facebookresearch/Detectron) | 18356 | +| [Fast R-CNN](http://openaccess.thecvf.com/content_iccv_2015/html/Girshick_Fast_R-CNN_ICCV_2015_paper.html) | ICCV | [code](https://github.com/facebookresearch/Detectron) | 18356 | +| [Conditional Random Fields as Recurrent Neural Networks](http://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Conditional_Random_Fields_ICCV_2015_paper.html) | ICCV | [code](https://github.com/torrvision/crfasrnn) | 1189 | +| [Fully Convolutional Networks for Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2015/html/Long_Fully_Convolutional_Networks_2015_CVPR_paper.html) | CVPR | [code](https://github.com/shekkizh/FCN.tensorflow) | 911 | +| [Learning to Track: Online Multi-Object Tracking by Decision Making](http://openaccess.thecvf.com/content_iccv_2015/html/Xiang_Learning_to_Track_ICCV_2015_paper.html) | ICCV | [code](https://github.com/yuxng/MDP_Tracking) | 308 | +| [Learning to Compare Image Patches via Convolutional Neural Networks](http://openaccess.thecvf.com/content_cvpr_2015/html/Zagoruyko_Learning_to_Compare_2015_CVPR_paper.html) | CVPR | [code](https://github.com/szagoruyko/cvpr15deepcompare) | 300 | +| [Learning Deconvolution Network for Semantic Segmentation](http://openaccess.thecvf.com/content_iccv_2015/html/Noh_Learning_Deconvolution_Network_ICCV_2015_paper.html) | ICCV | [code](https://github.com/HyeonwooNoh/DeconvNet) | 296 | +| [Single Image Super-Resolution From Transformed Self-Exemplars](http://openaccess.thecvf.com/content_cvpr_2015/html/Huang_Single_Image_Super-Resolution_2015_CVPR_paper.html) | CVPR | [code](https://github.com/jbhuang0604/SelfExSR) | 289 | +| [Sequence to Sequence - Video to Text](http://openaccess.thecvf.com/content_iccv_2015/html/Venugopalan_Sequence_to_Sequence_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jazzsaxmafia/video_to_sequence) | 239 | +| [Deep Colorization](http://openaccess.thecvf.com/content_iccv_2015/html/Cheng_Deep_Colorization_ICCV_2015_paper.html) | ICCV | [code](https://github.com/richzhang/colorization-pytorch) | 198 | +| [Deep Neural Decision Forests](http://openaccess.thecvf.com/content_iccv_2015/html/Kontschieder_Deep_Neural_Decision_ICCV_2015_paper.html) | ICCV | [code](https://github.com/chrischoy/fully-differentiable-deep-ndf-tf) | 192 | +| [Hierarchical Convolutional Features for Visual Tracking](http://openaccess.thecvf.com/content_iccv_2015/html/Ma_Hierarchical_Convolutional_Features_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jbhuang0604/CF2) | 179 | +| [Render for CNN: Viewpoint Estimation in Images Using CNNs Trained With Rendered 3D Model Views](http://openaccess.thecvf.com/content_iccv_2015/html/Su_Render_for_CNN_ICCV_2015_paper.html) | ICCV | [code](https://github.com/ShapeNet/RenderForCNN) | 176 | +| [Realtime Edge-Based Visual Odometry for a Monocular Camera](http://openaccess.thecvf.com/content_iccv_2015/html/Tarrio_Realtime_Edge-Based_Visual_ICCV_2015_paper.html) | ICCV | [code](https://github.com/JuanTarrio/rebvo) | 175 | +| [Understanding Deep Image Representations by Inverting Them](http://openaccess.thecvf.com/content_cvpr_2015/html/Mahendran_Understanding_Deep_Image_2015_CVPR_paper.html) | CVPR | [code](https://github.com/aravindhm/deep-goggle) | 154 | +| [Context-Aware CNNs for Person Head Detection](http://openaccess.thecvf.com/content_iccv_2015/html/Vu_Context-Aware_CNNs_for_ICCV_2015_paper.html) | ICCV | [code](https://github.com/aosokin/cnn_head_detection) | 153 | +| [Show and Tell: A Neural Image Caption Generator](http://openaccess.thecvf.com/content_cvpr_2015/html/Vinyals_Show_and_Tell_2015_CVPR_paper.html) | CVPR | [code](https://github.com/KranthiGV/Pretrained-Show-and-Tell-model) | 141 | +| [Face Alignment by Coarse-to-Fine Shape Searching](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html) | CVPR | [code](https://github.com/zhusz/CVPR15-CFSS) | 140 | +| [An Improved Deep Learning Architecture for Person Re-Identification](http://openaccess.thecvf.com/content_cvpr_2015/html/Ahmed_An_Improved_Deep_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Ning-Ding/Implementation-CVPR2015-CNN-for-ReID) | 127 | +| [FaceNet: A Unified Embedding for Face Recognition and Clustering](http://openaccess.thecvf.com/content_cvpr_2015/html/Schroff_FaceNet_A_Unified_2015_CVPR_paper.html) | CVPR | [code](https://github.com/liorshk/facenet_pytorch) | 124 | +| [Depth-Based Hand Pose Estimation: Data, Methods, and Challenges](http://openaccess.thecvf.com/content_iccv_2015/html/Supancic_Depth-Based_Hand_Pose_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jsupancic/deep_hand_pose) | 121 | +| [DynamicFusion: Reconstruction and Tracking of Non-Rigid Scenes in Real-Time](http://openaccess.thecvf.com/content_cvpr_2015/html/Newcombe_DynamicFusion_Reconstruction_and_2015_CVPR_paper.html) | CVPR | [code](https://github.com/mihaibujanca/dynamicfusion) | 118 | +| [Massively Parallel Multiview Stereopsis by Surface Normal Diffusion](http://openaccess.thecvf.com/content_iccv_2015/html/Galliani_Massively_Parallel_Multiview_ICCV_2015_paper.html) | ICCV | [code](https://github.com/kysucix/gipuma) | 105 | +| [Learning to Propose Objects](http://openaccess.thecvf.com/content_cvpr_2015/html/Krahenbuhl_Learning_to_Propose_2015_CVPR_paper.html) | CVPR | [code](https://github.com/philkr/lpo) | 91 | +| [Learning Spatially Regularized Correlation Filters for Visual Tracking](http://openaccess.thecvf.com/content_iccv_2015/html/Danelljan_Learning_Spatially_Regularized_ICCV_2015_paper.html) | ICCV | [code](https://github.com/lifeng9472/STRCF) | 86 | +| [A Convolutional Neural Network Cascade for Face Detection](http://openaccess.thecvf.com/content_cvpr_2015/html/Li_A_Convolutional_Neural_2015_CVPR_paper.html) | CVPR | [code](https://github.com/mks0601/A-Convolutional-Neural-Network-Cascade-for-Face-Detection) | 85 | +| [Discriminative Learning of Deep Convolutional Feature Point Descriptors](http://openaccess.thecvf.com/content_iccv_2015/html/Simo-Serra_Discriminative_Learning_of_ICCV_2015_paper.html) | ICCV | [code](https://github.com/etrulls/deepdesc-release) | 77 | +| [Unsupervised Visual Representation Learning by Context Prediction](http://openaccess.thecvf.com/content_iccv_2015/html/Doersch_Unsupervised_Visual_Representation_ICCV_2015_paper.html) | ICCV | [code](https://github.com/cdoersch/deepcontext) | 73 | +| [Deep Neural Networks Are Easily Fooled: High Confidence Predictions for Unrecognizable Images](http://openaccess.thecvf.com/content_cvpr_2015/html/Nguyen_Deep_Neural_Networks_2015_CVPR_paper.html) | CVPR | [code](https://github.com/abhijitbendale/OSDN) | 71 | +| [Deep Filter Banks for Texture Recognition and Segmentation](http://openaccess.thecvf.com/content_cvpr_2015/html/Cimpoi_Deep_Filter_Banks_2015_CVPR_paper.html) | CVPR | [code](https://github.com/mcimpoi/deep-fbanks) | 68 | +| [Saliency Detection by Multi-Context Deep Learning](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhao_Saliency_Detection_by_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Robert0812/deepsaldet) | 66 | +| [Multi-Objective Convolutional Learning for Face Labeling](http://openaccess.thecvf.com/content_cvpr_2015/html/Liu_Multi-Objective_Convolutional_Learning_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Liusifei/Face_Parsing_2016) | 55 | +| [Finding Action Tubes](http://openaccess.thecvf.com/content_cvpr_2015/html/Gkioxari_Finding_Action_Tubes_2015_CVPR_paper.html) | CVPR | [code](https://github.com/gkioxari/ActionTubes) | 51 | +| [Category-Specific Object Reconstruction From a Single Image](http://openaccess.thecvf.com/content_cvpr_2015/html/Kar_Category-Specific_Object_Reconstruction_2015_CVPR_paper.html) | CVPR | [code](https://github.com/akar43/CategoryShapes) | 48 | +| [Convolutional Color Constancy](http://openaccess.thecvf.com/content_iccv_2015/html/Barron_Convolutional_Color_Constancy_ICCV_2015_paper.html) | ICCV | [code](https://github.com/yuanming-hu/fc4) | 47 | +| [Face Flow](http://openaccess.thecvf.com/content_iccv_2015/html/Snape_Face_Flow_ICCV_2015_paper.html) | ICCV | [code](https://github.com/shashanktyagi/HyperFace-TensorFlow-implementation) | 45 | +| [P-CNN: Pose-Based CNN Features for Action Recognition](http://openaccess.thecvf.com/content_iccv_2015/html/Cheron_P-CNN_Pose-Based_CNN_ICCV_2015_paper.html) | ICCV | [code](https://github.com/gcheron/P-CNN) | 45 | +| [Learning From Massive Noisy Labeled Data for Image Classification](http://openaccess.thecvf.com/content_cvpr_2015/html/Xiao_Learning_From_Massive_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Cysu/noisy_label) | 45 | +| [Image Specificity](http://openaccess.thecvf.com/content_cvpr_2015/html/Jas_Image_Specificity_2015_CVPR_paper.html) | CVPR | [code](https://github.com/burliEnterprises/tensorflow-image-classifier) | 40 | +| [Predicting Depth, Surface Normals and Semantic Labels With a Common Multi-Scale Convolutional Architecture](http://openaccess.thecvf.com/content_iccv_2015/html/Eigen_Predicting_Depth_Surface_ICCV_2015_paper.html) | ICCV | [code](https://github.com/Rostifar/NYUDepthNet) | 35 | +| [Neural Activation Constellations: Unsupervised Part Model Discovery With Convolutional Networks](http://openaccess.thecvf.com/content_iccv_2015/html/Simon_Neural_Activation_Constellations_ICCV_2015_paper.html) | ICCV | [code](https://github.com/cvjena/part_constellation_models) | 35 | +| [VQA: Visual Question Answering](http://openaccess.thecvf.com/content_iccv_2015/html/Antol_VQA_Visual_Question_ICCV_2015_paper.html) | ICCV | [code](https://github.com/imatge-upc/vqa-2016-cvprw) | 35 | +| [Mid-Level Deep Pattern Mining](http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Mid-Level_Deep_Pattern_2015_CVPR_paper.html) | CVPR | [code](https://github.com/yaoliUoA/MDPM) | 34 | +| [PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization](http://openaccess.thecvf.com/content_iccv_2015/html/Kendall_PoseNet_A_Convolutional_ICCV_2015_paper.html) | ICCV | [code](https://github.com/futurely/deep-camera-relocalization) | 34 | +| [Parsimonious Labeling](http://openaccess.thecvf.com/content_iccv_2015/html/Dokania_Parsimonious_Labeling_ICCV_2015_paper.html) | ICCV | [code](https://github.com/aimerykong/Pixel-Attentional-Gating) | 33 | +| [Car That Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models](http://openaccess.thecvf.com/content_iccv_2015/html/Jain_Car_That_Knows_ICCV_2015_paper.html) | ICCV | [code](https://github.com/asheshjain399/ICCV2015_Brain4Cars) | 33 | +| [Recurrent Convolutional Neural Network for Object Recognition](http://openaccess.thecvf.com/content_cvpr_2015/html/Liang_Recurrent_Convolutional_Neural_2015_CVPR_paper.html) | CVPR | [code](https://github.com/JimLee4530/RCNN) | 32 | +| [TILDE: A Temporally Invariant Learned DEtector](http://openaccess.thecvf.com/content_cvpr_2015/html/Verdie_TILDE_A_Temporally_2015_CVPR_paper.html) | CVPR | [code](https://github.com/kmyid/TILDE) | 30 | +| [In Defense of Color-Based Model-Free Tracking](http://openaccess.thecvf.com/content_cvpr_2015/html/Possegger_In_Defense_of_2015_CVPR_paper.html) | CVPR | [code](https://github.com/foolwood/DAT) | 30 | +| [Fast Bilateral-Space Stereo for Synthetic Defocus](http://openaccess.thecvf.com/content_cvpr_2015/html/Barron_Fast_Bilateral-Space_Stereo_2015_CVPR_paper.html) | CVPR | [code](https://github.com/tvandenzegel/fast_bilateral_space_stereo) | 29 | +| [Phase-Based Frame Interpolation for Video](http://openaccess.thecvf.com/content_cvpr_2015/html/Meyer_Phase-Based_Frame_Interpolation_2015_CVPR_paper.html) | CVPR | [code](https://github.com/owang/PhaseBasedInterpolation) | 28 | +| [Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhu_Understanding_Tools_Task-Oriented_2015_CVPR_paper.html) | CVPR | [code](https://github.com/xiaozhuchacha/Kinect2Toolbox) | 27 | +| [Deeply Learned Attributes for Crowded Scene Understanding](http://openaccess.thecvf.com/content_cvpr_2015/html/Shao_Deeply_Learned_Attributes_2015_CVPR_paper.html) | CVPR | [code](https://github.com/amandajshao/www_deep_crowd) | 27 | +| [Unconstrained 3D Face Reconstruction](http://openaccess.thecvf.com/content_cvpr_2015/html/Roth_Unconstrained_3D_Face_2015_CVPR_paper.html) | CVPR | [code](https://github.com/NJUPole/CVPR2015-Unconstrained-3D-Face-Reconstruction) | 26 | +| [Viewpoints and Keypoints](http://openaccess.thecvf.com/content_cvpr_2015/html/Tulsiani_Viewpoints_and_Keypoints_2015_CVPR_paper.html) | CVPR | [code](https://github.com/shubhtuls/ViewpointsAndKeypoints) | 25 | +| [Holistically-Nested Edge Detection](http://openaccess.thecvf.com/content_iccv_2015/html/Xie_Holistically-Nested_Edge_Detection_ICCV_2015_paper.html) | ICCV | [code](https://github.com/s9xie/hed_release-deprecated) | 25 | +| [Going Deeper With Convolutions](http://openaccess.thecvf.com/content_cvpr_2015/html/Szegedy_Going_Deeper_With_2015_CVPR_paper.html) | CVPR | [code](https://github.com/nutszebra/googlenet) | 25 | +| [Reconstructing the World* in Six Days *(As Captured by the Yahoo 100 Million Image Dataset)](http://openaccess.thecvf.com/content_cvpr_2015/html/Heinly_Reconstructing_the_World_2015_CVPR_paper.html) | CVPR | [code](https://github.com/jheinly/streaming_connected_component_discovery) | 25 | +| [Data-Driven 3D Voxel Patterns for Object Category Recognition](http://openaccess.thecvf.com/content_cvpr_2015/html/Xiang_Data-Driven_3D_Voxel_2015_CVPR_paper.html) | CVPR | [code](https://github.com/yuxng/3DVP) | 24 | +| [L0TV: A New Method for Image Restoration in the Presence of Impulse Noise](http://openaccess.thecvf.com/content_cvpr_2015/html/Yuan_L0TV_A_New_2015_CVPR_paper.html) | CVPR | [code](https://github.com/peisuke/L0TV) | 22 | +| [Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Beyond_Frontal_Faces_2015_CVPR_paper.html) | CVPR | [code](https://github.com/sciencefans/Beyond-Frontal-Faces) | 21 | +| [Understanding Deep Features With Computer-Generated Imagery](http://openaccess.thecvf.com/content_iccv_2015/html/Aubry_Understanding_Deep_Features_ICCV_2015_paper.html) | ICCV | [code](https://github.com/mathieuaubry/features_analysis) | 19 | +| [HICO: A Benchmark for Recognizing Human-Object Interactions in Images](http://openaccess.thecvf.com/content_iccv_2015/html/Chao_HICO_A_Benchmark_ICCV_2015_paper.html) | ICCV | [code](https://github.com/ywchao/hico_benchmark) | 18 | +| [Structured Feature Selection](http://openaccess.thecvf.com/content_iccv_2015/html/Gao_Structured_Feature_Selection_ICCV_2015_paper.html) | ICCV | [code](https://github.com/csliangdu/FSASL) | 17 | +| [Learning Large-Scale Automatic Image Colorization](http://openaccess.thecvf.com/content_iccv_2015/html/Deshpande_Learning_Large-Scale_Automatic_ICCV_2015_paper.html) | ICCV | [code](https://github.com/aditya12agd5/iccv15_lscolorization) | 17 | +| [Semantic Component Analysis](http://openaccess.thecvf.com/content_iccv_2015/html/Murdock_Semantic_Component_Analysis_ICCV_2015_paper.html) | ICCV | [code](https://github.com/aubry74/visual-word2vec) | 17 | +| [Simultaneous Feature Learning and Hash Coding With Deep Neural Networks](http://openaccess.thecvf.com/content_cvpr_2015/html/Lai_Simultaneous_Feature_Learning_2015_CVPR_paper.html) | CVPR | [code](https://github.com/HYPJUDY/caffe-dnnh) | 16 | +| [3D Object Reconstruction From Hand-Object Interactions](http://openaccess.thecvf.com/content_iccv_2015/html/Tzionas_3D_Object_Reconstruction_ICCV_2015_paper.html) | ICCV | [code](https://github.com/dimtziwnas/InHandScanningICCV15_Reconstruction) | 15 | +| [Learning Temporal Embeddings for Complex Video Analysis](http://openaccess.thecvf.com/content_iccv_2015/html/Ramanathan_Learning_Temporal_Embeddings_ICCV_2015_paper.html) | ICCV | [code](https://github.com/eevignesh/videovector) | 14 | +| [Learning to See by Moving](http://openaccess.thecvf.com/content_iccv_2015/html/Agrawal_Learning_to_See_ICCV_2015_paper.html) | ICCV | [code](https://github.com/pulkitag/learning-to-see-by-moving) | 14 | +| [Reflection Removal Using Ghosting Cues](http://openaccess.thecvf.com/content_cvpr_2015/html/Shih_Reflection_Removal_Using_2015_CVPR_paper.html) | CVPR | [code](https://github.com/thongnguyendev/single_image) | 14 | +| [Where to Buy It: Matching Street Clothing Photos in Online Shops](http://openaccess.thecvf.com/content_iccv_2015/html/Kiapour_Where_to_Buy_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jfuentescpp/where_to_buy_it) | 14 | +| [Oriented Edge Forests for Boundary Detection](http://openaccess.thecvf.com/content_cvpr_2015/html/Hallman_Oriented_Edge_Forests_2015_CVPR_paper.html) | CVPR | [code](https://github.com/samhallman/oef) | 13 | +| [A Large-Scale Car Dataset for Fine-Grained Categorization and Verification](http://openaccess.thecvf.com/content_cvpr_2015/html/Yang_A_Large-Scale_Car_2015_CVPR_paper.html) | CVPR | [code](https://github.com/bogger/caffe-multigpu) | 11 | +| [Appearance-Based Gaze Estimation in the Wild](http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Appearance-Based_Gaze_Estimation_2015_CVPR_paper.html) | CVPR | [code](https://github.com/trakaros/MPIIGaze) | 10 | +| [Learning a Descriptor-Specific 3D Keypoint Detector](http://openaccess.thecvf.com/content_iccv_2015/html/Salti_Learning_a_Descriptor-Specific_ICCV_2015_paper.html) | ICCV | [code](https://github.com/CVLAB-Unibo/Keypoint-Learning) | 10 | +| [Robust Image Filtering Using Joint Static and Dynamic Guidance](http://openaccess.thecvf.com/content_cvpr_2015/html/Ham_Robust_Image_Filtering_2015_CVPR_paper.html) | CVPR | [code](https://github.com/bsham/SDFilter) | 10 | +| [Partial Person Re-Identification](http://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Partial_Person_Re-Identification_ICCV_2015_paper.html) | ICCV | [code](https://github.com/lingxiao-he/Deep-Spatial-Feature-Reconstruction-for-Partial-Person-Re-identification) | 9 | +| [High Quality Structure From Small Motion for Rolling Shutter Cameras](http://openaccess.thecvf.com/content_iccv_2015/html/Im_High_Quality_Structure_ICCV_2015_paper.html) | ICCV | [code](https://github.com/sunghoonim/SfSM) | 9 | +| [Boosting Object Proposals: From Pascal to COCO](http://openaccess.thecvf.com/content_iccv_2015/html/Pont-Tuset_Boosting_Object_Proposals_ICCV_2015_paper.html) | ICCV | [code](https://github.com/jponttuset/BOP) | 8 | +| [Convolutional Channel Features](http://openaccess.thecvf.com/content_iccv_2015/html/Yang_Convolutional_Channel_Features_ICCV_2015_paper.html) | ICCV | [code](https://github.com/byangderek/CCF) | 8 | +| [Live Repetition Counting](http://openaccess.thecvf.com/content_iccv_2015/html/Levy_Live_Repetition_Counting_ICCV_2015_paper.html) | ICCV | [code](https://github.com/tomrunia/DeepRepICCV2015) | 8 | +| [Unsupervised Learning of Visual Representations Using Videos](http://openaccess.thecvf.com/content_iccv_2015/html/Wang_Unsupervised_Learning_of_ICCV_2015_paper.html) | ICCV | [code](https://github.com/coreylynch/unsupervised-triplet-embedding) | 8 | +| [Supervised Discrete Hashing](http://openaccess.thecvf.com/content_cvpr_2015/html/Shen_Supervised_Discrete_Hashing_2015_CVPR_paper.html) | CVPR | [code](https://github.com/goukoutaki/FSDH) | 7 | +| [Multi-View Convolutional Neural Networks for 3D Shape Recognition](http://openaccess.thecvf.com/content_iccv_2015/html/Su_Multi-View_Convolutional_Neural_ICCV_2015_paper.html) | ICCV | [code](https://github.com/shawnxu1318/MVCNN-Multi-View-Convolutional-Neural-Networks) | 7 | +| [Simpler Non-Parametric Methods Provide as Good or Better Results to Multiple-Instance Learning](http://openaccess.thecvf.com/content_iccv_2015/html/Venkatesan_Simpler_Non-Parametric_Methods_ICCV_2015_paper.html) | ICCV | [code](https://github.com/ragavvenkatesan/np-mil) | 7 | +| [Finding Distractors In Images](http://openaccess.thecvf.com/content_cvpr_2015/html/Fried_Finding_Distractors_In_2015_CVPR_paper.html) | CVPR | [code](https://github.com/ohadf/distractors) | 7 | +| [Piecewise Flat Embedding for Image Segmentation](http://openaccess.thecvf.com/content_iccv_2015/html/Yu_Piecewise_Flat_Embedding_ICCV_2015_paper.html) | ICCV | [code](https://github.com/chaoweifang/PFE) | 7 | +| [Long-Term Correlation Tracking](http://openaccess.thecvf.com/content_cvpr_2015/html/Ma_Long-Term_Correlation_Tracking_2015_CVPR_paper.html) | CVPR | [code](https://github.com/malreddysid/long-term-correlation-tracking) | 6 | +| [Towards Open World Recognition](http://openaccess.thecvf.com/content_cvpr_2015/html/Bendale_Towards_Open_World_2015_CVPR_paper.html) | CVPR | [code](https://github.com/abhijitbendale/OWR) | 6 | +| [Pooled Motion Features for First-Person Videos](http://openaccess.thecvf.com/content_cvpr_2015/html/Ryoo_Pooled_Motion_Features_2015_CVPR_paper.html) | CVPR | [code](https://github.com/USCDataScience/hadoop-pot) | 6 | +| [Simultaneous Deep Transfer Across Domains and Tasks](http://openaccess.thecvf.com/content_iccv_2015/html/Tzeng_Simultaneous_Deep_Transfer_ICCV_2015_paper.html) | ICCV | [code](https://github.com/mahfujau/domain_adaptation_iccv15) | 6 | +| [What Makes an Object Memorable?](http://openaccess.thecvf.com/content_iccv_2015/html/Dubey_What_Makes_an_ICCV_2015_paper.html) | ICCV | [code](https://github.com/qixuanHou/Mapping-My-Break) | 5 | +| [Mining Semantic Affordances of Visual Object Categories](http://openaccess.thecvf.com/content_cvpr_2015/html/Chao_Mining_Semantic_Affordances_2015_CVPR_paper.html) | CVPR | [code](https://github.com/ywchao/semantic_affordance) | 5 | +| [Dense Semantic Correspondence Where Every Pixel is a Classifier](http://openaccess.thecvf.com/content_iccv_2015/html/Bristow_Dense_Semantic_Correspondence_ICCV_2015_paper.html) | ICCV | [code](https://github.com/hbristow/epic) | 5 | +| [Segment Graph Based Image Filtering: Fast Structure-Preserving Smoothing](http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Segment_Graph_Based_ICCV_2015_paper.html) | ICCV | [code](https://github.com/feihuzhang/SGF) | 5 | +| [Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization](http://openaccess.thecvf.com/content_cvpr_2015/html/Oh_Fast_Randomized_Singular_2015_CVPR_paper.html) | CVPR | [code](https://github.com/HlG4399/FRSVT) | 5 | +| [Unsupervised Generation of a Viewpoint Annotated Car Dataset From Videos](http://openaccess.thecvf.com/content_iccv_2015/html/Sedaghat_Unsupervised_Generation_of_ICCV_2015_paper.html) | ICCV | [code](https://github.com/lmb-freiburg/unsup-car-dataset) | 5 | +| [Multi-Label Cross-Modal Retrieval](http://openaccess.thecvf.com/content_iccv_2015/html/Ranjan_Multi-Label_Cross-Modal_Retrieval_ICCV_2015_paper.html) | ICCV | [code](https://github.com/Viresh-R/ml-CCA) | 4 | +| [Superdifferential Cuts for Binary Energies](http://openaccess.thecvf.com/content_cvpr_2015/html/Taniai_Superdifferential_Cuts_for_2015_CVPR_paper.html) | CVPR | [code](https://github.com/t-taniai/SDC_CVPR2015) | 4 | +| [Pose Induction for Novel Object Categories](http://openaccess.thecvf.com/content_iccv_2015/html/Tulsiani_Pose_Induction_for_ICCV_2015_paper.html) | ICCV | [code](https://github.com/shubhtuls/poseInduction) | 4 | +| [Efficient Minimal-Surface Regularization of Perspective Depth Maps in Variational Stereo](http://openaccess.thecvf.com/content_cvpr_2015/html/Graber_Efficient_Minimal-Surface_Regularization_2015_CVPR_paper.html) | CVPR | [code](https://github.com/VLOGroup/surface-area-regularization) | 4 | +| [Low-Rank Matrix Factorization Under General Mixture Noise Distributions](http://openaccess.thecvf.com/content_iccv_2015/html/Cao_Low-Rank_Matrix_Factorization_ICCV_2015_paper.html) | ICCV | [code](https://github.com/xiangyongcao/PMoEP) | 4 | +| [Robust Saliency Detection via Regularized Random Walks Ranking](http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Robust_Saliency_Detection_2015_CVPR_paper.html) | CVPR | [code](https://github.com/yuanyc06/rr) | 3 | +| [Simultaneous Video Defogging and Stereo Reconstruction](http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Simultaneous_Video_Defogging_2015_CVPR_paper.html) | CVPR | [code](https://github.com/Lashuk1729/DIP-Project-Video-Dehazing) | 3 | +| [Hyperspectral Super-Resolution by Coupled Spectral Unmixing](http://openaccess.thecvf.com/content_iccv_2015/html/Lanaras_Hyperspectral_Super-Resolution_by_ICCV_2015_paper.html) | ICCV | [code](https://github.com/lanha/SupResPALM) | 3 | +| [Oriented Object Proposals](http://openaccess.thecvf.com/content_iccv_2015/html/He_Oriented_Object_Proposals_ICCV_2015_paper.html) | ICCV | [code](https://github.com/frutuozo29/WebServiceRESTFul) | 3 | +| [kNN Hashing With Factorized Neighborhood Representation](http://openaccess.thecvf.com/content_iccv_2015/html/Ding_kNN_Hashing_With_ICCV_2015_paper.html) | ICCV | [code](https://github.com/dooook/kNN-hashing) | 3 | +| [Minimum Barrier Salient Object Detection at 80 FPS](http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Minimum_Barrier_Salient_ICCV_2015_paper.html) | ICCV | [code](https://github.com/coderSkyChen/MBS_Cplus_c-) | 3 |
↥ back to top @@ -1548,37 +1560,37 @@ Use [this](https://github.com/zziz/pwc/issues/11) thread to request us your favo ## 2014 | Title | Conf | Code | Stars | |:--------|:--------:|:--------:|:--------:| -| [Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2014/html/Girshick_Rich_Feature_Hierarchies_2014_CVPR_paper.html) | CVPR | [code](https://github.com/rbgirshick/rcnn) | 1681 | -| [Locally Optimized Product Quantization for Approximate Nearest Neighbor Search](http://openaccess.thecvf.com/content_cvpr_2014/html/Kalantidis_Locally_Optimized_Product_2014_CVPR_paper.html) | CVPR | [code](https://github.com/yahoo/lopq) | 437 | -| [Clothing Co-Parsing by Joint Image Segmentation and Labeling](http://openaccess.thecvf.com/content_cvpr_2014/html/Yang_Clothing_Co-Parsing_by_2014_CVPR_paper.html) | CVPR | [code](https://github.com/bearpaw/clothing-co-parsing) | 218 | -| [Multiscale Combinatorial Grouping](http://openaccess.thecvf.com/content_cvpr_2014/html/Arbelaez_Multiscale_Combinatorial_Grouping_2014_CVPR_paper.html) | CVPR | [code](https://github.com/jponttuset/mcg) | 185 | -| [Face Alignment at 3000 FPS via Regressing Local Binary Features](http://openaccess.thecvf.com/content_cvpr_2014/html/Ren_Face_Alignment_at_2014_CVPR_paper.html) | CVPR | [code](https://github.com/luoyetx/face-alignment-at-3000fps) | 164 | -| [Cross-Scale Cost Aggregation for Stereo Matching](http://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Cross-Scale_Cost_Aggregation_2014_CVPR_paper.html) | CVPR | [code](https://github.com/rookiepig/CrossScaleStereo) | 106 | -| [Transfer Joint Matching for Unsupervised Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2014/html/Long_Transfer_Joint_Matching_2014_CVPR_paper.html) | CVPR | [code](https://github.com/USTCPCS/CVPR2018_attention) | 67 | -| [Deep Learning Face Representation from Predicting 10,000 Classes](http://openaccess.thecvf.com/content_cvpr_2014/html/Sun_Deep_Learning_Face_2014_CVPR_paper.html) | CVPR | [code](https://github.com/joyhuang9473/deepid-implementation) | 62 | -| [BING: Binarized Normed Gradients for Objectness Estimation at 300fps](http://openaccess.thecvf.com/content_cvpr_2014/html/Cheng_BING_Binarized_Normed_2014_CVPR_paper.html) | CVPR | [code](https://github.com/alessandroferrari/BING-Objectness) | 44 | -| [One Millisecond Face Alignment with an Ensemble of Regression Trees](http://openaccess.thecvf.com/content_cvpr_2014/html/Kazemi_One_Millisecond_Face_2014_CVPR_paper.html) | CVPR | [code](https://github.com/jjrCN/ERT-GBDT_Face_Alignment) | 43 | -| [3D Reconstruction from Accidental Motion](http://openaccess.thecvf.com/content_cvpr_2014/html/Yu_3D_Reconstruction_from_2014_CVPR_paper.html) | CVPR | [code](https://github.com/fyu/tiny) | 42 | -| [Predicting Matchability](http://openaccess.thecvf.com/content_cvpr_2014/html/Hartmann_Predicting_Matchability_2014_CVPR_paper.html) | CVPR | [code](https://github.com/jacekm-git/BetBoy) | 38 | -| [Dense Semantic Image Segmentation with Objects and Attributes](http://openaccess.thecvf.com/content_cvpr_2014/html/Zheng_Dense_Semantic_Image_2014_CVPR_paper.html) | CVPR | [code](https://github.com/bittnt/ImageSpirit) | 28 | -| [Scene-Independent Group Profiling in Crowd](http://openaccess.thecvf.com/content_cvpr_2014/html/Shao_Scene-Independent_Group_Profiling_2014_CVPR_paper.html) | CVPR | [code](https://github.com/amandajshao/crowd_group_profile) | 28 | -| [Shrinkage Fields for Effective Image Restoration](http://openaccess.thecvf.com/content_cvpr_2014/html/Schmidt_Shrinkage_Fields_for_2014_CVPR_paper.html) | CVPR | [code](https://github.com/uschmidt83/shrinkage-fields) | 25 | -| [Adaptive Color Attributes for Real-Time Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2014/html/Danelljan_Adaptive_Color_Attributes_2014_CVPR_paper.html) | CVPR | [code](https://github.com/mostafaizz/ColorTracker) | 25 | -| [Minimal Scene Descriptions from Structure from Motion Models](http://openaccess.thecvf.com/content_cvpr_2014/html/Cao_Minimal_Scene_Descriptions_2014_CVPR_paper.html) | CVPR | [code](https://github.com/caosong/minimal_scene) | 22 | -| [Parallax-tolerant Image Stitching](http://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Parallax-tolerant_Image_Stitching_2014_CVPR_paper.html) | CVPR | [code](https://github.com/gain2217/Robust_Elastic_Warping) | 20 | -| [Learning Mid-level Filters for Person Re-identification](http://openaccess.thecvf.com/content_cvpr_2014/html/Zhao_Learning_Mid-level_Filters_2014_CVPR_paper.html) | CVPR | [code](https://github.com/Robert0812/midfilter_reid) | 20 | -| [Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow](http://openaccess.thecvf.com/content_cvpr_2014/html/Bao_Fast_Edge-Preserving_PatchMatch_2014_CVPR_paper.html) | CVPR | [code](https://github.com/linchaobao/EPPM) | 18 | -| [Product Sparse Coding](http://openaccess.thecvf.com/content_cvpr_2014/html/Ge_Product_Sparse_Coding_2014_CVPR_paper.html) | CVPR | [code](https://github.com/ksopyla/CudaDotProd) | 16 | -| [Convolutional Neural Networks for No-Reference Image Quality Assessment](http://openaccess.thecvf.com/content_cvpr_2014/html/Kang_Convolutional_Neural_Networks_2014_CVPR_paper.html) | CVPR | [code](https://github.com/lidq92/CNNIQA) | 16 | -| [Seeing 3D Chairs: Exemplar Part-based 2D-3D Alignment using a Large Dataset of CAD Models](http://openaccess.thecvf.com/content_cvpr_2014/html/Aubry_Seeing_3D_Chairs_2014_CVPR_paper.html) | CVPR | [code](https://github.com/mathieuaubry/seeing3Dchairs) | 15 | -| [StoryGraphs: Visualizing Character Interactions as a Timeline](http://openaccess.thecvf.com/content_cvpr_2014/html/Tapaswi_StoryGraphs_Visualizing_Character_2014_CVPR_paper.html) | CVPR | [code](https://github.com/makarandtapaswi/StoryGraphs_CVPR2014) | 14 | -| [Nonparametric Part Transfer for Fine-grained Recognition](http://openaccess.thecvf.com/content_cvpr_2014/html/Goring_Nonparametric_Part_Transfer_2014_CVPR_paper.html) | CVPR | [code](https://github.com/cvjena/finegrained-cvpr2014) | 13 | -| [Scalable Multitask Representation Learning for Scene Classification](http://openaccess.thecvf.com/content_cvpr_2014/html/Lapin_Scalable_Multitask_Representation_2014_CVPR_paper.html) | CVPR | [code](https://github.com/mlapin/cvpr14mtl) | 11 | -| [Investigating Haze-relevant Features in A Learning Framework for Image Dehazing](http://openaccess.thecvf.com/content_cvpr_2014/html/Tang_Investigating_Haze-relevant_Features_2014_CVPR_paper.html) | CVPR | [code](https://github.com/zlinker/haze_2014) | 7 | -| [Reconstructing PASCAL VOC](http://openaccess.thecvf.com/content_cvpr_2014/html/Vicente_Reconstructing_PASCAL_VOC_2014_CVPR_paper.html) | CVPR | [code](https://github.com/yihui-he/reconstructing-pascal-voc) | 6 | -| [Collaborative Hashing](http://openaccess.thecvf.com/content_cvpr_2014/html/Liu_Collaborative_Hashing_2014_CVPR_paper.html) | CVPR | [code](https://github.com/27359794/lsh-collab-filtering) | 6 | -| [Tell Me What You See and I will Show You Where It Is](http://openaccess.thecvf.com/content_cvpr_2014/html/Xu_Tell_Me_What_2014_CVPR_paper.html) | CVPR | [code](https://github.com/MarkipTheMudkip/in-class-project-2) | 6 | -| [Salient Region Detection via High-Dimensional Color Transform](http://openaccess.thecvf.com/content_cvpr_2014/html/Kim_Salient_Region_Detection_2014_CVPR_paper.html) | CVPR | [code](https://github.com/jhkim89/Saliency-HDCT) | 6 | +| [Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation](http://openaccess.thecvf.com/content_cvpr_2014/html/Girshick_Rich_Feature_Hierarchies_2014_CVPR_paper.html) | CVPR | [code](https://github.com/rbgirshick/rcnn) | 1681 | +| [Locally Optimized Product Quantization for Approximate Nearest Neighbor Search](http://openaccess.thecvf.com/content_cvpr_2014/html/Kalantidis_Locally_Optimized_Product_2014_CVPR_paper.html) | CVPR | [code](https://github.com/yahoo/lopq) | 437 | +| [Clothing Co-Parsing by Joint Image Segmentation and Labeling](http://openaccess.thecvf.com/content_cvpr_2014/html/Yang_Clothing_Co-Parsing_by_2014_CVPR_paper.html) | CVPR | [code](https://github.com/bearpaw/clothing-co-parsing) | 218 | +| [Multiscale Combinatorial Grouping](http://openaccess.thecvf.com/content_cvpr_2014/html/Arbelaez_Multiscale_Combinatorial_Grouping_2014_CVPR_paper.html) | CVPR | [code](https://github.com/jponttuset/mcg) | 185 | +| [Face Alignment at 3000 FPS via Regressing Local Binary Features](http://openaccess.thecvf.com/content_cvpr_2014/html/Ren_Face_Alignment_at_2014_CVPR_paper.html) | CVPR | [code](https://github.com/luoyetx/face-alignment-at-3000fps) | 164 | +| [Cross-Scale Cost Aggregation for Stereo Matching](http://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Cross-Scale_Cost_Aggregation_2014_CVPR_paper.html) | CVPR | [code](https://github.com/rookiepig/CrossScaleStereo) | 106 | +| [Transfer Joint Matching for Unsupervised Domain Adaptation](http://openaccess.thecvf.com/content_cvpr_2014/html/Long_Transfer_Joint_Matching_2014_CVPR_paper.html) | CVPR | [code](https://github.com/USTCPCS/CVPR2018_attention) | 67 | +| [Deep Learning Face Representation from Predicting 10,000 Classes](http://openaccess.thecvf.com/content_cvpr_2014/html/Sun_Deep_Learning_Face_2014_CVPR_paper.html) | CVPR | [code](https://github.com/joyhuang9473/deepid-implementation) | 62 | +| [BING: Binarized Normed Gradients for Objectness Estimation at 300fps](http://openaccess.thecvf.com/content_cvpr_2014/html/Cheng_BING_Binarized_Normed_2014_CVPR_paper.html) | CVPR | [code](https://github.com/alessandroferrari/BING-Objectness) | 44 | +| [One Millisecond Face Alignment with an Ensemble of Regression Trees](http://openaccess.thecvf.com/content_cvpr_2014/html/Kazemi_One_Millisecond_Face_2014_CVPR_paper.html) | CVPR | [code](https://github.com/jjrCN/ERT-GBDT_Face_Alignment) | 43 | +| [3D Reconstruction from Accidental Motion](http://openaccess.thecvf.com/content_cvpr_2014/html/Yu_3D_Reconstruction_from_2014_CVPR_paper.html) | CVPR | [code](https://github.com/fyu/tiny) | 42 | +| [Predicting Matchability](http://openaccess.thecvf.com/content_cvpr_2014/html/Hartmann_Predicting_Matchability_2014_CVPR_paper.html) | CVPR | [code](https://github.com/jacekm-git/BetBoy) | 38 | +| [Dense Semantic Image Segmentation with Objects and Attributes](http://openaccess.thecvf.com/content_cvpr_2014/html/Zheng_Dense_Semantic_Image_2014_CVPR_paper.html) | CVPR | [code](https://github.com/bittnt/ImageSpirit) | 28 | +| [Scene-Independent Group Profiling in Crowd](http://openaccess.thecvf.com/content_cvpr_2014/html/Shao_Scene-Independent_Group_Profiling_2014_CVPR_paper.html) | CVPR | [code](https://github.com/amandajshao/crowd_group_profile) | 28 | +| [Shrinkage Fields for Effective Image Restoration](http://openaccess.thecvf.com/content_cvpr_2014/html/Schmidt_Shrinkage_Fields_for_2014_CVPR_paper.html) | CVPR | [code](https://github.com/uschmidt83/shrinkage-fields) | 25 | +| [Adaptive Color Attributes for Real-Time Visual Tracking](http://openaccess.thecvf.com/content_cvpr_2014/html/Danelljan_Adaptive_Color_Attributes_2014_CVPR_paper.html) | CVPR | [code](https://github.com/mostafaizz/ColorTracker) | 25 | +| [Minimal Scene Descriptions from Structure from Motion Models](http://openaccess.thecvf.com/content_cvpr_2014/html/Cao_Minimal_Scene_Descriptions_2014_CVPR_paper.html) | CVPR | [code](https://github.com/caosong/minimal_scene) | 22 | +| [Parallax-tolerant Image Stitching](http://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Parallax-tolerant_Image_Stitching_2014_CVPR_paper.html) | CVPR | [code](https://github.com/gain2217/Robust_Elastic_Warping) | 20 | +| [Learning Mid-level Filters for Person Re-identification](http://openaccess.thecvf.com/content_cvpr_2014/html/Zhao_Learning_Mid-level_Filters_2014_CVPR_paper.html) | CVPR | [code](https://github.com/Robert0812/midfilter_reid) | 20 | +| [Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow](http://openaccess.thecvf.com/content_cvpr_2014/html/Bao_Fast_Edge-Preserving_PatchMatch_2014_CVPR_paper.html) | CVPR | [code](https://github.com/linchaobao/EPPM) | 18 | +| [Product Sparse Coding](http://openaccess.thecvf.com/content_cvpr_2014/html/Ge_Product_Sparse_Coding_2014_CVPR_paper.html) | CVPR | [code](https://github.com/ksopyla/CudaDotProd) | 16 | +| [Convolutional Neural Networks for No-Reference Image Quality Assessment](http://openaccess.thecvf.com/content_cvpr_2014/html/Kang_Convolutional_Neural_Networks_2014_CVPR_paper.html) | CVPR | [code](https://github.com/lidq92/CNNIQA) | 16 | +| [Seeing 3D Chairs: Exemplar Part-based 2D-3D Alignment using a Large Dataset of CAD Models](http://openaccess.thecvf.com/content_cvpr_2014/html/Aubry_Seeing_3D_Chairs_2014_CVPR_paper.html) | CVPR | [code](https://github.com/mathieuaubry/seeing3Dchairs) | 15 | +| [StoryGraphs: Visualizing Character Interactions as a Timeline](http://openaccess.thecvf.com/content_cvpr_2014/html/Tapaswi_StoryGraphs_Visualizing_Character_2014_CVPR_paper.html) | CVPR | [code](https://github.com/makarandtapaswi/StoryGraphs_CVPR2014) | 14 | +| [Nonparametric Part Transfer for Fine-grained Recognition](http://openaccess.thecvf.com/content_cvpr_2014/html/Goring_Nonparametric_Part_Transfer_2014_CVPR_paper.html) | CVPR | [code](https://github.com/cvjena/finegrained-cvpr2014) | 13 | +| [Scalable Multitask Representation Learning for Scene Classification](http://openaccess.thecvf.com/content_cvpr_2014/html/Lapin_Scalable_Multitask_Representation_2014_CVPR_paper.html) | CVPR | [code](https://github.com/mlapin/cvpr14mtl) | 11 | +| [Investigating Haze-relevant Features in A Learning Framework for Image Dehazing](http://openaccess.thecvf.com/content_cvpr_2014/html/Tang_Investigating_Haze-relevant_Features_2014_CVPR_paper.html) | CVPR | [code](https://github.com/zlinker/haze_2014) | 7 | +| [Reconstructing PASCAL VOC](http://openaccess.thecvf.com/content_cvpr_2014/html/Vicente_Reconstructing_PASCAL_VOC_2014_CVPR_paper.html) | CVPR | [code](https://github.com/yihui-he/reconstructing-pascal-voc) | 6 | +| [Collaborative Hashing](http://openaccess.thecvf.com/content_cvpr_2014/html/Liu_Collaborative_Hashing_2014_CVPR_paper.html) | CVPR | [code](https://github.com/27359794/lsh-collab-filtering) | 6 | +| [Tell Me What You See and I will Show You Where It Is](http://openaccess.thecvf.com/content_cvpr_2014/html/Xu_Tell_Me_What_2014_CVPR_paper.html) | CVPR | [code](https://github.com/MarkipTheMudkip/in-class-project-2) | 6 | +| [Salient Region Detection via High-Dimensional Color Transform](http://openaccess.thecvf.com/content_cvpr_2014/html/Kim_Salient_Region_Detection_2014_CVPR_paper.html) | CVPR | [code](https://github.com/jhkim89/Saliency-HDCT) | 6 |
↥ back to top @@ -1587,4 +1599,4 @@ Use [this](https://github.com/zziz/pwc/issues/11) thread to request us your favo ## 2013 | Title | Conf | Code | Stars | |:--------|:--------:|:--------:|:--------:| -| [A generic decentralized trust management framework](http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2012/MSC/MSC-2012-22.pdf) | SPE | [code](https://github.com/amitport/graphpack) | 6 | +| [A generic decentralized trust management framework](http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2012/MSC/MSC-2012-22.pdf) | SPE | [code](https://github.com/amitport/graphpack) | 6 | diff --git a/src/pwc.csv b/src/pwc.csv index 14c6ad0..38eb410 100644 --- a/src/pwc.csv +++ b/src/pwc.csv @@ -1,1848 +1,1852 @@ paper_title,paper_link,conference,year,repo_link,repo_star,last_update -Bridging the Gap Between Value and Policy Based Reinforcement Learning,http://papers.nips.cc/paper/6870-bridging-the-gap-between-value-and-policy-based-reinforcement-learning.pdf,NIPS,2017,https://github.com/tensorflow/models,46593,2019-01-02 -"REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models",http://papers.nips.cc/paper/6856-rebar-low-variance-unbiased-gradient-estimates-for-discrete-latent-variable-models.pdf,NIPS,2017,https://github.com/tensorflow/models,46593,2019-01-02 -Focal Loss for Dense Object Detection,http://openaccess.thecvf.com/content_iccv_2017/html/Lin_Focal_Loss_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/facebookresearch/Detectron,18356,2019-01-02 -Faster R-CNN: Towards Real-Time Object Detectionwith Region Proposal Networks,https://papers.nips.cc/paper/5638-faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks.pdf,NIPS,2015,https://github.com/facebookresearch/Detectron,18356,2019-01-02 -R-FCN: Object Detection via Region-based Fully Convolutional Networks,https://papers.nips.cc/paper/6465-r-fcn-object-detection-via-region-based-fully-convolutional-networks.pdf,NIPS,2016,https://github.com/facebookresearch/Detectron,18356,2019-01-02 -Fast R-CNN,http://openaccess.thecvf.com/content_iccv_2015/html/Girshick_Fast_R-CNN_ICCV_2015_paper.html,ICCV,2015,https://github.com/facebookresearch/Detectron,18356,2019-01-02 -Image Style Transfer Using Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Gatys_Image_Style_Transfer_CVPR_2016_paper.html,CVPR,2016,https://github.com/jcjohnson/neural-style,16435,2019-01-02 -Deep Photo Style Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Luan_Deep_Photo_Style_CVPR_2017_paper.html,CVPR,2017,https://github.com/luanfujun/deep-photo-styletransfer,8655,2019-01-02 -Mask R-CNN,http://openaccess.thecvf.com/content_iccv_2017/html/He_Mask_R-CNN_ICCV_2017_paper.html,ICCV,2017,https://github.com/matterport/Mask_RCNN,9493,2019-01-02 -LightGBM: A Highly Efficient Gradient Boosting Decision Tree,http://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf,NIPS,2017,https://github.com/Microsoft/LightGBM,7536,2019-01-02 -Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation,http://papers.nips.cc/paper/7112-scalable-trust-region-method-for-deep-reinforcement-learning-using-kronecker-factored-approximation.pdf,NIPS,2017,https://github.com/openai/baselines,6449,2019-01-02 -Attention is All you Need,http://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf,NIPS,2017,https://github.com/tensorflow/tensor2tensor,6288,2019-01-02 -Video-to-Video Synthesis,https://arxiv.org/abs/1808.06601,NIPS,2018,https://github.com/NVIDIA/vid2vid,5578,2019-01-02 -Deep Residual Learning for Image Recognition,http://openaccess.thecvf.com/content_cvpr_2016/html/He_Deep_Residual_Learning_CVPR_2016_paper.html,CVPR,2016,https://github.com/KaimingHe/deep-residual-networks,4468,2019-01-02 -Deep Image Prior,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ulyanov_Deep_Image_Prior_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/DmitryUlyanov/deep-image-prior,3736,2019-01-02 -Large Pose 3D Face Reconstruction From a Single Image via Direct Volumetric CNN Regression,http://openaccess.thecvf.com/content_iccv_2017/html/Jackson_Large_Pose_3D_ICCV_2017_paper.html,ICCV,2017,https://github.com/AaronJackson/vrn,3354,2019-01-02 -StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_StarGAN_Unified_Generative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yunjey/StarGAN,3405,2019-01-02 -Convolutional Pose Machines,http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Convolutional_Pose_Machines_CVPR_2016_paper.html,CVPR,2016,https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation,3260,2019-01-02 -Densely Connected Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Densely_Connected_Convolutional_CVPR_2017_paper.html,CVPR,2017,https://github.com/liuzhuang13/DenseNet,3130,2019-01-02 -A Unified Approach to Interpreting Model Predictions,http://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions.pdf,NIPS,2017,https://github.com/slundberg/shap,3122,2019-01-02 -Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network,http://openaccess.thecvf.com/content_ECCV_2018/html/Yao_Feng_Joint_3D_Face_ECCV_2018_paper.html,ECCV,2018,https://github.com/YadiraF/PRNet,2434,2019-01-02 -Learning to See in the Dark,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Learning_to_See_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cchen156/Learning-to-See-in-the-Dark,2326,2019-01-02 -Glow: Generative Flow with Invertible 1x1 Convolutions,http://arxiv.org/abs/1807.03039v2,NIPS,2018,https://github.com/openai/glow,2088,2019-01-02 -Deformable Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Deformable_Convolutional_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/msracver/Deformable-ConvNets,2165,2019-01-02 -"ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games",http://papers.nips.cc/paper/6859-elf-an-extensive-lightweight-and-flexible-research-platform-for-real-time-strategy-games.pdf,NIPS,2017,https://github.com/facebookresearch/ELF,1823,2019-01-02 -Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2014/html/Girshick_Rich_Feature_Hierarchies_2014_CVPR_paper.html,CVPR,2014,https://github.com/rbgirshick/rcnn,1681,2019-01-02 -Fully Convolutional Instance-Aware Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Fully_Convolutional_Instance-Aware_CVPR_2017_paper.html,CVPR,2017,https://github.com/msracver/FCIS,1395,2019-01-02 -PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Qi_PointNet_Deep_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/charlesq34/pointnet,1523,2019-01-02 -Improved Training of Wasserstein GANs,http://papers.nips.cc/paper/7159-improved-training-of-wasserstein-gans.pdf,NIPS,2017,https://github.com/igul222/improved_wgan_training,1405,2019-01-02 -Aggregated Residual Transformations for Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Xie_Aggregated_Residual_Transformations_CVPR_2017_paper.html,CVPR,2017,https://github.com/facebookresearch/ResNeXt,1361,2019-01-02 -Squeeze-and-Excitation Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hujie-frank/SENet,1477,2019-01-02 -Efficient Neural Architecture Search via Parameters Sharing,http://proceedings.mlr.press/v80/pham18a.html,ICML,2018,https://github.com/carpedm20/ENAS-pytorch,1382,2019-01-02 -Multimodal Unsupervised Image-to-image Translation,http://openaccess.thecvf.com/content_ECCV_2018/html/Xun_Huang_Multimodal_Unsupervised_Image-to-image_ECCV_2018_paper.html,ECCV,2018,https://github.com/NVlabs/MUNIT,1296,2019-01-02 -Conditional Random Fields as Recurrent Neural Networks,http://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Conditional_Random_Fields_ICCV_2015_paper.html,ICCV,2015,https://github.com/torrvision/crfasrnn,1189,2019-01-02 -Photographic Image Synthesis With Cascaded Refinement Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Photographic_Image_Synthesis_ICCV_2017_paper.html,ICCV,2017,https://github.com/CQFIO/PhotographicImageSynthesis,1142,2019-01-02 -Unsupervised Image-to-Image Translation Networks,http://papers.nips.cc/paper/6672-unsupervised-image-to-image-translation-networks.pdf,NIPS,2017,https://github.com/mingyuliutw/unit,1205,2019-01-02 -Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Ledig_Photo-Realistic_Single_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/tensorlayer/srgan,1301,2019-01-02 -High-Resolution Image Inpainting Using Multi-Scale Neural Patch Synthesis,http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_High-Resolution_Image_Inpainting_CVPR_2017_paper.html,CVPR,2017,https://github.com/leehomyc/Faster-High-Res-Neural-Inpainting,1072,2019-01-02 -SphereFace: Deep Hypersphere Embedding for Face Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_SphereFace_Deep_Hypersphere_CVPR_2017_paper.html,CVPR,2017,https://github.com/wy1iu/sphereface,1048,2019-01-02 -Bayesian GAN,http://papers.nips.cc/paper/6953-bayesian-gan.pdf,NIPS,2017,https://github.com/andrewgordonwilson/bayesgan,942,2019-01-02 -Deep Feature Flow for Video Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Deep_Feature_Flow_CVPR_2017_paper.html,CVPR,2017,https://github.com/msracver/Deep-Feature-Flow,966,2019-01-02 -Pyramid Scene Parsing Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhao_Pyramid_Scene_Parsing_CVPR_2017_paper.html,CVPR,2017,https://github.com/hszhao/PSPNet,934,2019-01-02 -Non-Local Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Non-Local_Neural_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/facebookresearch/video-nonlocal-net,992,2019-01-02 -Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes,http://papers.nips.cc/paper/7098-efficient-modeling-of-latent-information-in-supervised-learning-using-gaussian-processes.pdf,NIPS,2017,https://github.com/SheffieldML/GPy,906,2019-01-02 -Fully Convolutional Networks for Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2015/html/Long_Fully_Convolutional_Networks_2015_CVPR_paper.html,CVPR,2015,https://github.com/shekkizh/FCN.tensorflow,911,2019-01-02 -Finding Tiny Faces,http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Finding_Tiny_Faces_CVPR_2017_paper.html,CVPR,2017,https://github.com/peiyunh/tiny,856,2019-01-02 -Image Generation From Scene Graphs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Johnson_Image_Generation_From_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/google/sg2im,851,2019-01-02 -Learning to Discover Cross-Domain Relations with Generative Adversarial Networks,http://proceedings.mlr.press/v70/kim17a.html,ICML,2017,https://github.com/carpedm20/DiscoGAN-pytorch,784,2019-01-02 -"YOLO9000: Better, Faster, Stronger",http://openaccess.thecvf.com/content_cvpr_2017/html/Redmon_YOLO9000_Better_Faster_CVPR_2017_paper.html,CVPR,2017,https://github.com/philipperemy/yolo-9000,773,2019-01-02 -Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis,http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Combining_Markov_Random_CVPR_2016_paper.html,CVPR,2016,https://github.com/chuanli11/CNNMRF,731,2019-01-02 -Toward Multimodal Image-to-Image Translation,http://papers.nips.cc/paper/6650-toward-multimodal-image-to-image-translation.pdf,NIPS,2017,https://github.com/junyanz/BiCycleGAN,794,2019-01-02 -Synthetic Data for Text Localisation in Natural Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Gupta_Synthetic_Data_for_CVPR_2016_paper.html,CVPR,2016,https://github.com/ankush-me/SynthText,787,2019-01-02 -Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hara_Can_Spatiotemporal_3D_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kenshohara/3D-ResNets-PyTorch,924,2019-01-02 -Single-Shot Refinement Neural Network for Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Single-Shot_Refinement_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sfzhang15/RefineDet,875,2019-01-02 -FlowNet 2.0: Evolution of Optical Flow Estimation With Deep Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Ilg_FlowNet_2.0_Evolution_CVPR_2017_paper.html,CVPR,2017,https://github.com/lmb-freiburg/flownet2,720,2019-01-02 -PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space,http://papers.nips.cc/paper/7095-pointnet-deep-hierarchical-feature-learning-on-point-sets-in-a-metric-space.pdf,NIPS,2017,https://github.com/charlesq34/pointnet2,772,2019-01-02 -Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks,http://proceedings.mlr.press/v70/finn17a.html,ICML,2017,https://github.com/cbfinn/maml,729,2019-01-02 -GANimation: Anatomically-aware Facial Animation from a Single Image,http://openaccess.thecvf.com/content_ECCV_2018/html/Albert_Pumarola_Anatomically_Coherent_Facial_ECCV_2018_paper.html,ECCV,2018,https://github.com/albertpumarola/GANimation,772,2019-01-02 -Inferring and Executing Programs for Visual Reasoning,http://openaccess.thecvf.com/content_iccv_2017/html/Johnson_Inferring_and_Executing_ICCV_2017_paper.html,ICCV,2017,https://github.com/facebookresearch/clevr-iep,636,2019-01-02 -Channel Pruning for Accelerating Very Deep Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/He_Channel_Pruning_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/yihui-he/channel-pruning,649,2019-01-02 -Dilated Residual Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Yu_Dilated_Residual_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/fyu/drn,640,2019-01-02 -Accelerating Eulerian Fluid Simulation With Convolutional Networks,http://proceedings.mlr.press/v70/tompson17a.html,ICML,2017,https://github.com/google/FluidNet,570,2019-01-02 -Detect-and-Track: Efficient Pose Estimation in Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Girdhar_Detect-and-Track_Efficient_Pose_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/facebookresearch/DetectAndTrack,650,2019-01-02 -DSOD: Learning Deeply Supervised Object Detectors From Scratch,http://openaccess.thecvf.com/content_iccv_2017/html/Shen_DSOD_Learning_Deeply_ICCV_2017_paper.html,ICCV,2017,https://github.com/szq0214/DSOD,582,2019-01-02 -Relation Networks for Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Relation_Networks_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/msracver/Relation-Networks-for-Object-Detection,635,2019-01-02 -Arbitrary Style Transfer in Real-Time With Adaptive Instance Normalization,http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Arbitrary_Style_Transfer_ICCV_2017_paper.html,ICCV,2017,https://github.com/xunhuang1995/AdaIN-style,572,2019-01-02 -Learning Disentangled Representations with Semi-Supervised Deep Generative Models,http://papers.nips.cc/paper/7174-learning-disentangled-representations-with-semi-supervised-deep-generative-models.pdf,NIPS,2017,https://github.com/probtorch/probtorch,556,2019-01-02 -PointCNN,http://arxiv.org/abs/1801.07791v3,NIPS,2018,https://github.com/yangyanli/PointCNN,607,2019-01-02 -"How Far Are We From Solving the 2D & 3D Face Alignment Problem? (And a Dataset of 230,000 3D Facial Landmarks)",http://openaccess.thecvf.com/content_iccv_2017/html/Bulat_How_Far_Are_ICCV_2017_paper.html,ICCV,2017,https://github.com/1adrianb/2D-and-3D-face-alignment,526,2019-01-02 -Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples,http://proceedings.mlr.press/v80/athalye18a.html,ICML,2018,https://github.com/anishathalye/obfuscated-gradients,535,2019-01-02 -Simple Baselines for Human Pose Estimation and Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Bin_Xiao_Simple_Baselines_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/Microsoft/human-pose-estimation.pytorch,752,2019-01-02 -Regressing Robust and Discriminative 3D Morphable Models With a Very Deep Neural Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Tran_Regressing_Robust_and_CVPR_2017_paper.html,CVPR,2017,https://github.com/anhttran/3dmm_cnn,537,2019-01-02 -Learning From Simulated and Unsupervised Images Through Adversarial Training,http://openaccess.thecvf.com/content_cvpr_2017/html/Shrivastava_Learning_From_Simulated_CVPR_2017_paper.html,CVPR,2017,https://github.com/carpedm20/simulated-unsupervised-tensorflow,492,2019-01-02 -Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space,http://openaccess.thecvf.com/content_cvpr_2017/html/Nguyen_Plug__Play_CVPR_2017_paper.html,CVPR,2017,https://github.com/Evolving-AI-Lab/ppgn,487,2019-01-02 -Taskonomy: Disentangling Task Transfer Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zamir_Taskonomy_Disentangling_Task_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/StanfordVL/taskonomy,502,2019-01-02 -Which Training Methods for GANs do actually Converge?,http://proceedings.mlr.press/v80/mescheder18a.html,ICML,2018,https://github.com/LMescheder/GAN_stability,520,2019-01-02 -Cascaded Pyramid Network for Multi-Person Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Cascaded_Pyramid_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chenyilun95/tf-cpn,497,2019-01-02 -Pelee: A Real-Time Object Detection System on Mobile Devices,https://arxiv.org/pdf/1804.06882.pdf,NIPS,2018,https://github.com/Robert-JunWang/Pelee,548,2019-01-02 -Generative Image Inpainting With Contextual Attention,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Generative_Image_Inpainting_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JiahuiYu/generative_inpainting,609,2019-01-02 -Neural 3D Mesh Renderer,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kato_Neural_3D_Mesh_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hiroharu-kato/neural_renderer,489,2019-01-02 -SSH: Single Stage Headless Face Detector,http://openaccess.thecvf.com/content_iccv_2017/html/Najibi_SSH_Single_Stage_ICCV_2017_paper.html,ICCV,2017,https://github.com/mahyarnajibi/SSH,515,2019-01-02 -"GMS: Grid-based Motion Statistics for Fast, Ultra-Robust Feature Correspondence",http://openaccess.thecvf.com/content_cvpr_2017/html/Bian_GMS_Grid-based_Motion_CVPR_2017_paper.html,CVPR,2017,https://github.com/JiawangBian/GMS-Feature-Matcher,460,2019-01-02 -Dual Path Networks,http://papers.nips.cc/paper/7033-dual-path-networks.pdf,NIPS,2017,https://github.com/cypw/DPNs,451,2019-01-02 -Inductive Representation Learning on Large Graphs,http://papers.nips.cc/paper/6703-inductive-representation-learning-on-large-graphs.pdf,NIPS,2017,https://github.com/williamleif/GraphSAGE,552,2019-01-02 -Instance-Aware Semantic Segmentation via Multi-Task Network Cascades,http://openaccess.thecvf.com/content_cvpr_2016/html/Dai_Instance-Aware_Semantic_Segmentation_CVPR_2016_paper.html,CVPR,2016,https://github.com/daijifeng001/MNC,433,2019-01-02 -Video Frame Interpolation via Adaptive Convolution,http://openaccess.thecvf.com/content_cvpr_2017/html/Niklaus_Video_Frame_Interpolation_CVPR_2017_paper.html,CVPR,2017,https://github.com/sniklaus/pytorch-sepconv,482,2019-01-02 -Video Frame Interpolation via Adaptive Separable Convolution,http://openaccess.thecvf.com/content_iccv_2017/html/Niklaus_Video_Frame_Interpolation_ICCV_2017_paper.html,ICCV,2017,https://github.com/sniklaus/pytorch-sepconv,482,2019-01-02 -Look at Boundary: A Boundary-Aware Face Alignment Algorithm,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Look_at_Boundary_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wywu/LAB,575,2019-01-02 -Joint Detection and Identification Feature Learning for Person Search,http://openaccess.thecvf.com/content_cvpr_2017/html/Xiao_Joint_Detection_and_CVPR_2017_paper.html,CVPR,2017,https://github.com/ShuangLI59/person_search,459,2019-01-02 -Zero-Shot Recognition via Semantic Embeddings and Knowledge Graphs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Zero-Shot_Recognition_via_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JudyYe/zero-shot-gcn,489,2019-01-02 -Locally Optimized Product Quantization for Approximate Nearest Neighbor Search,http://openaccess.thecvf.com/content_cvpr_2014/html/Kalantidis_Locally_Optimized_Product_2014_CVPR_paper.html,CVPR,2014,https://github.com/yahoo/lopq,437,2019-01-02 -Flow-Guided Feature Aggregation for Video Object Detection,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Flow-Guided_Feature_Aggregation_ICCV_2017_paper.html,ICCV,2017,https://github.com/msracver/Flow-Guided-Feature-Aggregation,436,2019-01-02 -In-Place Activated BatchNorm for Memory-Optimized Training of DNNs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Bulo_In-Place_Activated_BatchNorm_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mapillary/inplace_abn,485,2019-01-02 -End-to-End Recovery of Human Shape and Pose,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kanazawa_End-to-End_Recovery_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/akanazawa/hmr,502,2019-01-02 -Recurrent Highway Networks,http://proceedings.mlr.press/v70/zilly17a.html,ICML,2017,https://github.com/julian121266/RecurrentHighwayNetworks,397,2019-01-02 -ICNet for Real-Time Semantic Segmentation on High-Resolution Images,http://openaccess.thecvf.com/content_ECCV_2018/html/Hengshuang_Zhao_ICNet_for_Real-Time_ECCV_2018_paper.html,ECCV,2018,https://github.com/hszhao/ICNet,415,2019-01-02 -Deep Image Matting,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Deep_Image_Matting_CVPR_2017_paper.html,CVPR,2017,https://github.com/Joker316701882/Deep-Image-Matting,434,2019-01-02 -The Unreasonable Effectiveness of Deep Features as a Perceptual Metric,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_The_Unreasonable_Effectiveness_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/richzhang/PerceptualSimilarity,447,2019-01-02 -Detect to Track and Track to Detect,http://openaccess.thecvf.com/content_iccv_2017/html/Feichtenhofer_Detect_to_Track_ICCV_2017_paper.html,ICCV,2017,https://github.com/feichtenhofer/Detect-Track,387,2019-01-02 -Distractor-aware Siamese Networks for Visual Object Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Zhu_Distractor-aware_Siamese_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/foolwood/DaSiamRPN,545,2019-01-02 -Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results,http://papers.nips.cc/paper/6719-mean-teachers-are-better-role-models-weight-averaged-consistency-targets-improve-semi-supervised-deep-learning-results.pdf,NIPS,2017,https://github.com/CuriousAI/mean-teacher/,347,2018-09-16 -Frustum PointNets for 3D Object Detection From RGB-D Data,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Frustum_PointNets_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/charlesq34/frustum-pointnets,434,2019-01-02 -Efficient Interactive Annotation of Segmentation Datasets With Polygon-RNN++,http://openaccess.thecvf.com/content_cvpr_2018/papers/Acuna_Efficient_Interactive_Annotation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/fidler-lab/polyrnn-pp-pytorch,397,2019-01-02 -Annotating Object Instances With a Polygon-RNN,http://openaccess.thecvf.com/content_cvpr_2017/html/Castrejon_Annotating_Object_Instances_CVPR_2017_paper.html,CVPR,2017,https://github.com/fidler-lab/polyrnn-pp-pytorch,397,2019-01-02 -RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_RefineNet_Multi-Path_Refinement_CVPR_2017_paper.html,CVPR,2017,https://github.com/guosheng/refinenet,379,2019-01-02 -Learning Multi-Domain Convolutional Neural Networks for Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2016/html/Nam_Learning_Multi-Domain_Convolutional_CVPR_2016_paper.html,CVPR,2016,https://github.com/HyeonseobNam/MDNet,350,2019-01-02 -Gibson Env: Real-World Perception for Embodied Agents,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xia_Gibson_Env_Real-World_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/StanfordVL/GibsonEnv,385,2019-01-02 -Deep Lattice Networks and Partial Monotonic Functions,http://papers.nips.cc/paper/6891-deep-lattice-networks-and-partial-monotonic-functions.pdf,NIPS,2017,https://github.com/tensorflow/lattice,349,2019-01-02 -RON: Reverse Connection With Objectness Prior Networks for Object Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Kong_RON_Reverse_Connection_CVPR_2017_paper.html,CVPR,2017,https://github.com/taokong/RON,345,2019-01-02 -Detecting Oriented Text in Natural Images by Linking Segments,http://openaccess.thecvf.com/content_cvpr_2017/html/Shi_Detecting_Oriented_Text_CVPR_2017_paper.html,CVPR,2017,https://github.com/dengdan/seglink,364,2019-01-02 -Universal Style Transfer via Feature Transforms,http://papers.nips.cc/paper/6642-universal-style-transfer-via-feature-transforms.pdf,NIPS,2017,https://github.com/Yijunmaverick/UniversalStyleTransfer,344,2019-01-02 -Learning Deep Features for Discriminative Localization,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhou_Learning_Deep_Features_CVPR_2016_paper.html,CVPR,2016,https://github.com/jazzsaxmafia/Weakly_detector,323,2019-01-02 -Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mascharka_Transparency_by_Design_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/davidmascharka/tbd-nets,317,2019-01-02 -Soccer on Your Tabletop,http://openaccess.thecvf.com/content_cvpr_2018/papers/Rematas_Soccer_on_Your_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/krematas/soccerontable,338,2019-01-02 -Noise2Noise: Learning Image Restoration without Clean Data,http://proceedings.mlr.press/v80/lehtinen18a.html,ICML,2018,https://github.com/yu4u/noise2noise,370,2019-01-02 -Accurate Single Stage Detector Using Recurrent Rolling Convolution,http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_Accurate_Single_Stage_CVPR_2017_paper.html,CVPR,2017,https://github.com/xiaohaoChen/rrc_detection,314,2019-01-02 -Convolutional Two-Stream Network Fusion for Video Action Recognition,http://openaccess.thecvf.com/content_cvpr_2016/html/Feichtenhofer_Convolutional_Two-Stream_Network_CVPR_2016_paper.html,CVPR,2016,https://github.com/feichtenhofer/twostreamfusion,342,2019-01-02 -"GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose",http://openaccess.thecvf.com/content_cvpr_2018/papers/Yin_GeoNet_Unsupervised_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yzcjtr/GeoNet,359,2019-01-02 -GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_GeoNet_Geometric_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yzcjtr/GeoNet,359,2019-01-02 -One-Shot Video Object Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Caelles_One-Shot_Video_Object_CVPR_2017_paper.html,CVPR,2017,https://github.com/scaelles/OSVOS-TensorFlow,316,2019-01-02 -Neural Baby Talk,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lu_Neural_Baby_Talk_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiasenlu/NeuralBabyTalk,332,2019-01-02 -Learning Deconvolution Network for Semantic Segmentation,http://openaccess.thecvf.com/content_iccv_2015/html/Noh_Learning_Deconvolution_Network_ICCV_2015_paper.html,ICCV,2015,https://github.com/HyeonwooNoh/DeconvNet,296,2019-01-02 -Efficient softmax approximation for GPUs,http://proceedings.mlr.press/v70/grave17a.html,ICML,2017,https://github.com/facebookresearch/adaptive-softmax,304,2019-01-02 -Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution,http://openaccess.thecvf.com/content_cvpr_2017/html/Lai_Deep_Laplacian_Pyramid_CVPR_2017_paper.html,CVPR,2017,https://github.com/phoenix104104/LapSRN,301,2019-01-02 -Learning to Track: Online Multi-Object Tracking by Decision Making,http://openaccess.thecvf.com/content_iccv_2015/html/Xiang_Learning_to_Track_ICCV_2015_paper.html,ICCV,2015,https://github.com/yuxng/MDP_Tracking,308,2019-01-02 -Learning to Compare Image Patches via Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2015/html/Zagoruyko_Learning_to_Compare_2015_CVPR_paper.html,CVPR,2015,https://github.com/szagoruyko/cvpr15deepcompare,300,2019-01-02 -Acquisition of Localization Confidence for Accurate Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Borui_Jiang_Acquisition_of_Localization_ECCV_2018_paper.html,ECCV,2018,https://github.com/vacancy/PreciseRoIPooling,384,2019-01-02 -"PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume",http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_PWC-Net_CNNs_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/NVlabs/PWC-Net,398,2019-01-02 -Pixel Recursive Super Resolution,http://openaccess.thecvf.com/content_iccv_2017/html/Dahl_Pixel_Recursive_Super_ICCV_2017_paper.html,ICCV,2017,https://github.com/nilboy/pixel-recursive-super-resolution,301,2019-01-02 -The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Berman_The_LovaSz-Softmax_Loss_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/bermanmaxim/LovaszSoftmax,416,2019-01-02 -Residual Attention Network for Image Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Residual_Attention_Network_CVPR_2017_paper.html,CVPR,2017,https://github.com/fwang91/residual-attention-network,329,2019-01-02 -OctNet: Learning Deep 3D Representations at High Resolutions,http://openaccess.thecvf.com/content_cvpr_2017/html/Riegler_OctNet_Learning_Deep_CVPR_2017_paper.html,CVPR,2017,https://github.com/griegler/octnet,302,2019-01-02 -Dilated Recurrent Neural Networks,http://papers.nips.cc/paper/6613-dilated-recurrent-neural-networks.pdf,NIPS,2017,https://github.com/code-terminator/DilatedRNN,285,2019-01-02 -Fast End-to-End Trainable Guided Filter,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Fast_End-to-End_Trainable_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wuhuikai/DeepGuidedFilter,312,2019-01-02 -Feature Pyramid Networks for Object Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Feature_Pyramid_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/unsky/FPN,310,2019-01-02 -The Predictron: End-To-End Learning and Planning,http://proceedings.mlr.press/v70/silver17a.html,ICML,2017,https://github.com/zhongwen/predictron,274,2019-01-02 -Single Image Super-Resolution From Transformed Self-Exemplars,http://openaccess.thecvf.com/content_cvpr_2015/html/Huang_Single_Image_Super-Resolution_2015_CVPR_paper.html,CVPR,2015,https://github.com/jbhuang0604/SelfExSR,289,2019-01-02 -Adversarially Regularized Autoencoders,http://proceedings.mlr.press/v80/zhao18b.html,ICML,2018,https://github.com/jakezhaojb/ARAE,282,2019-01-02 -DeepBach: a Steerable Model for Bach Chorales Generation,http://proceedings.mlr.press/v70/hadjeres17a.html,ICML,2017,https://github.com/Ghadjeres/DeepBach,276,2019-01-02 -Age Progression/Regression by Conditional Adversarial Autoencoder,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Age_ProgressionRegression_by_CVPR_2017_paper.html,CVPR,2017,https://github.com/ZZUTK/Face-Aging-CAAE,297,2019-01-02 -Style Transfer from Non-Parallel Text by Cross-Alignment,http://papers.nips.cc/paper/7259-style-transfer-from-non-parallel-text-by-cross-alignment.pdf,NIPS,2017,https://github.com/shentianxiao/language-style-transfer,296,2019-01-02 -Self-Critical Sequence Training for Image Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Rennie_Self-Critical_Sequence_Training_CVPR_2017_paper.html,CVPR,2017,https://github.com/ruotianluo/self-critical.pytorch,299,2019-01-02 -License Plate Detection and Recognition in Unconstrained Scenarios,http://openaccess.thecvf.com/content_ECCV_2018/html/Sergio_Silva_License_Plate_Detection_ECCV_2018_paper.html,ECCV,2018,https://github.com/sergiomsilva/alpr-unconstrained,326,2019-01-02 -Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors,http://openaccess.thecvf.com/content_cvpr_2018/papers/Dong_Supervision-by-Registration_An_Unsupervised_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/facebookresearch/supervision-by-registration,326,2019-01-02 -Supervising Unsupervised Learning,http://arxiv.org/abs/1709.05262v2,NIPS,2018,https://github.com/quinnliu/machineLearning,262,2019-01-02 -Pyramid Stereo Matching Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chang_Pyramid_Stereo_Matching_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JiaRenChang/PSMNet,335,2019-01-02 -Convolutional Neural Networks With Alternately Updated Clique,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Convolutional_Neural_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/iboing/CliqueNet,272,2019-01-02 -Lifting From the Deep: Convolutional 3D Pose Estimation From a Single Image,http://openaccess.thecvf.com/content_cvpr_2017/html/Tome_Lifting_From_the_CVPR_2017_paper.html,CVPR,2017,https://github.com/DenisTome/Lifting-from-the-Deep-release,280,2019-01-02 -Deep Photo Enhancer: Unpaired Learning for Image Enhancement From Photographs With GANs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Deep_Photo_Enhancer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nothinglo/Deep-Photo-Enhancer,294,2019-01-02 -Neural Relational Inference for Interacting Systems,http://proceedings.mlr.press/v80/kipf18a.html,ICML,2018,https://github.com/ethanfetaya/NRI,289,2019-01-02 -Learning to Adapt Structured Output Space for Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tsai_Learning_to_Adapt_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wasidennis/AdaptSegNet,280,2019-01-02 -Richer Convolutional Features for Edge Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Richer_Convolutional_Features_CVPR_2017_paper.html,CVPR,2017,https://github.com/yun-liu/rcf,399,2019-01-02 -OptNet: Differentiable Optimization as a Layer in Neural Networks,http://proceedings.mlr.press/v70/amos17a.html,ICML,2017,https://github.com/locuslab/optnet,245,2019-01-02 -Deep Metric Learning via Lifted Structured Feature Embedding,http://openaccess.thecvf.com/content_cvpr_2016/html/Song_Deep_Metric_Learning_CVPR_2016_paper.html,CVPR,2016,https://github.com/rksltnl/Deep-Metric-Learning-CVPR16,251,2019-01-02 -Sequence to Sequence - Video to Text,http://openaccess.thecvf.com/content_iccv_2015/html/Venugopalan_Sequence_to_Sequence_ICCV_2015_paper.html,ICCV,2015,https://github.com/jazzsaxmafia/video_to_sequence,239,2019-01-02 -An intriguing failing of convolutional neural networks and the CoordConv solution,https://arxiv.org/abs/1807.03247,NIPS,2018,https://github.com/mkocabas/CoordConv-pytorch,249,2019-01-02 -Deep Voice: Real-time Neural Text-to-Speech,http://proceedings.mlr.press/v70/arik17a.html,ICML,2017,https://github.com/israelg99/deepvoice,242,2019-01-02 -Convolutional Sequence to Sequence Learning,http://proceedings.mlr.press/v70/gehring17a.html,ICML,2017,https://github.com/tobyyouup/conv_seq2seq,258,2019-01-02 -Learning to Segment Every Thing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Learning_to_Segment_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ronghanghu/seg_every_thing,269,2019-01-02 -LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hui_LiteFlowNet_A_Lightweight_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/twhui/LiteFlowNet,261,2019-01-02 -End-to-End Learning of Motion Representation for Video Understanding,http://openaccess.thecvf.com/content_cvpr_2018/papers/Fan_End-to-End_Learning_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/LijieFan/tvnet,238,2019-01-02 -Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images,http://openaccess.thecvf.com/content_ECCV_2018/html/Nanyang_Wang_Pixel2Mesh_Generating_3D_ECCV_2018_paper.html,ECCV,2018,https://github.com/nywang16/Pixel2Mesh,323,2019-01-02 -Bilinear Attention Networks,http://arxiv.org/abs/1805.07932v1,NIPS,2018,https://github.com/jnhwkim/ban-vqa,258,2019-01-02 -Semi-Parametric Image Synthesis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Semi-Parametric_Image_Synthesis_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xjqicuhk/SIMS,226,2019-01-02 -Iterative Visual Reasoning Beyond Convolutions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Iterative_Visual_Reasoning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/endernewton/iter-reason,228,2019-01-02 -Learning Deep Representations of Fine-Grained Visual Descriptions,http://openaccess.thecvf.com/content_cvpr_2016/html/Reed_Learning_Deep_Representations_CVPR_2016_paper.html,CVPR,2016,https://github.com/reedscot/cvpr2016,229,2019-01-02 -Reinforcement Learning with Deep Energy-Based Policies,http://proceedings.mlr.press/v70/haarnoja17a.html,ICML,2017,https://github.com/haarnoja/softqlearning,233,2019-01-02 -Stacked Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Stacked_Generative_Adversarial_CVPR_2017_paper.html,CVPR,2017,https://github.com/xunhuang1995/SGAN,215,2019-01-02 -Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Lu_Knowing_When_to_CVPR_2017_paper.html,CVPR,2017,https://github.com/jiasenlu/AdaptiveAttention,214,2019-01-02 -RMPE: Regional Multi-Person Pose Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Fang_RMPE_Regional_Multi-Person_ICCV_2017_paper.html,ICCV,2017,https://github.com/MVIG-SJTU/RMPE,215,2019-01-02 -BlitzNet: A Real-Time Deep Network for Scene Understanding,http://openaccess.thecvf.com/content_iccv_2017/html/Dvornik_BlitzNet_A_Real-Time_ICCV_2017_paper.html,ICCV,2017,https://github.com/dvornikita/blitznet,227,2019-01-02 -A Style-Aware Content Loss for Real-time HD Style Transfer,http://openaccess.thecvf.com/content_ECCV_2018/html/Artsiom_Sanakoyeu_A_Style-aware_Content_ECCV_2018_paper.html,ECCV,2018,https://github.com/CompVis/adaptive-style-transfer,349,2019-01-02 -Language Modeling with Gated Convolutional Networks,http://proceedings.mlr.press/v70/dauphin17a.html,ICML,2017,https://github.com/anantzoid/Language-Modeling-GatedCNN,221,2019-01-02 -A Point Set Generation Network for 3D Object Reconstruction From a Single Image,http://openaccess.thecvf.com/content_cvpr_2017/html/Fan_A_Point_Set_CVPR_2017_paper.html,CVPR,2017,https://github.com/fanhqme/PointSetGeneration,228,2019-01-02 -Spatially Adaptive Computation Time for Residual Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Figurnov_Spatially_Adaptive_Computation_CVPR_2017_paper.html,CVPR,2017,https://github.com/mfigurnov/sact,203,2019-01-02 -Prototypical Networks for Few-shot Learning,http://papers.nips.cc/paper/6996-prototypical-networks-for-few-shot-learning.pdf,NIPS,2017,https://github.com/jakesnell/prototypical-networks,244,2019-01-02 -Unlabeled Samples Generated by GAN Improve the Person Re-Identification Baseline in Vitro,http://openaccess.thecvf.com/content_iccv_2017/html/Zheng_Unlabeled_Samples_Generated_ICCV_2017_paper.html,ICCV,2017,https://github.com/layumi/Person-reID_GAN,215,2019-01-02 -The Reversible Residual Network: Backpropagation Without Storing Activations,http://papers.nips.cc/paper/6816-the-reversible-residual-network-backpropagation-without-storing-activations.pdf,NIPS,2017,https://github.com/renmengye/revnet-public,210,2019-01-02 -Style Aggregated Network for Facial Landmark Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Dong_Style_Aggregated_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/D-X-Y/SAN,223,2019-01-02 -Generative Face Completion,http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Generative_Face_Completion_CVPR_2017_paper.html,CVPR,2017,https://github.com/Yijunmaverick/GenerativeFaceCompletion,212,2019-01-02 -Eye Tracking for Everyone,http://openaccess.thecvf.com/content_cvpr_2016/html/Krafka_Eye_Tracking_for_CVPR_2016_paper.html,CVPR,2016,https://github.com/CSAILVision/GazeCapture,223,2019-01-02 -Deeply Supervised Salient Object Detection With Short Connections,http://openaccess.thecvf.com/content_cvpr_2017/html/Hou_Deeply_Supervised_Salient_CVPR_2017_paper.html,CVPR,2017,https://github.com/Joker316701882/Salient-Object-Detection,228,2019-01-02 -Recurrent Scale Approximation for Object Detection in CNN,http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Recurrent_Scale_Approximation_ICCV_2017_paper.html,ICCV,2017,https://github.com/sciencefans/RSA-for-object-detection,209,2019-01-02 -Pose-Robust Face Recognition via Deep Residual Equivariant Mapping,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Pose-Robust_Face_Recognition_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/penincillin/DREAM,220,2019-01-02 -Clothing Co-Parsing by Joint Image Segmentation and Labeling,http://openaccess.thecvf.com/content_cvpr_2014/html/Yang_Clothing_Co-Parsing_by_2014_CVPR_paper.html,CVPR,2014,https://github.com/bearpaw/clothing-co-parsing,218,2019-01-02 -Visual Dialog,http://openaccess.thecvf.com/content_cvpr_2017/html/Das_Visual_Dialog_CVPR_2017_paper.html,CVPR,2017,https://github.com/batra-mlp-lab/visdial,199,2019-01-02 -GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models,http://proceedings.mlr.press/v80/you18a.html,ICML,2018,https://github.com/JiaxuanYou/graph-generation,214,2019-01-02 -Referring Relationships,http://openaccess.thecvf.com/content_cvpr_2018/papers/Krishna_Referring_Relationships_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/StanfordVL/ReferringRelationships,210,2019-01-02 -Deep Neural Decision Forests,http://openaccess.thecvf.com/content_iccv_2015/html/Kontschieder_Deep_Neural_Decision_ICCV_2015_paper.html,ICCV,2015,https://github.com/chrischoy/fully-differentiable-deep-ndf-tf,192,2019-01-02 -MoCoGAN: Decomposing Motion and Content for Video Generation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulyakov_MoCoGAN_Decomposing_Motion_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sergeytulyakov/mocogan,205,2019-01-02 -FastMask: Segment Multi-Scale Object Candidates in One Shot,http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_FastMask_Segment_Multi-Scale_CVPR_2017_paper.html,CVPR,2017,https://github.com/voidrank/FastMask,189,2019-01-02 -Compressed Video Action Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Compressed_Video_Action_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chaoyuaw/pytorch-coviar,225,2019-01-02 -VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition,http://openaccess.thecvf.com/content_iccv_2017/html/Lee_VPGNet_Vanishing_Point_ICCV_2017_paper.html,ICCV,2017,https://github.com/SeokjuLee/VPGNet,210,2019-01-02 -Learning Deep CNN Denoiser Prior for Image Restoration,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Learning_Deep_CNN_CVPR_2017_paper.html,CVPR,2017,https://github.com/cszn/IRCNN,231,2019-01-02 -LayoutNet: Reconstructing the 3D Room Layout From a Single RGB Image,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zou_LayoutNet_Reconstructing_the_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zouchuhang/LayoutNet,202,2019-01-02 -Hierarchical Convolutional Features for Visual Tracking,http://openaccess.thecvf.com/content_iccv_2015/html/Ma_Hierarchical_Convolutional_Features_ICCV_2015_paper.html,ICCV,2015,https://github.com/jbhuang0604/CF2,179,2019-01-02 -ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Sachin_Mehta_ESPNet_Efficient_Spatial_ECCV_2018_paper.html,ECCV,2018,https://github.com/sacmehta/ESPNet,254,2019-01-02 -Interpretable Explanations of Black Boxes by Meaningful Perturbation,http://openaccess.thecvf.com/content_iccv_2017/html/Fong_Interpretable_Explanations_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/jacobgil/pytorch-explain-black-box,192,2019-01-02 -NetVLAD: CNN Architecture for Weakly Supervised Place Recognition,http://openaccess.thecvf.com/content_cvpr_2016/html/Arandjelovic_NetVLAD_CNN_Architecture_CVPR_2016_paper.html,CVPR,2016,https://github.com/Relja/netvlad,204,2019-01-02 -Semantic Scene Completion From a Single Depth Image,http://openaccess.thecvf.com/content_cvpr_2017/html/Song_Semantic_Scene_Completion_CVPR_2017_paper.html,CVPR,2017,https://github.com/shurans/sscnet,188,2019-01-02 -Deep Colorization,http://openaccess.thecvf.com/content_iccv_2015/html/Cheng_Deep_Colorization_ICCV_2015_paper.html,ICCV,2015,https://github.com/richzhang/colorization-pytorch,198,2019-01-02 -Multiscale Combinatorial Grouping,http://openaccess.thecvf.com/content_cvpr_2014/html/Arbelaez_Multiscale_Combinatorial_Grouping_2014_CVPR_paper.html,CVPR,2014,https://github.com/jponttuset/mcg,185,2019-01-02 -Latent Alignment and Variational Attention,http://arxiv.org/abs/1807.03756v1,NIPS,2018,https://github.com/harvardnlp/var-attn,204,2019-01-02 -Inverse Compositional Spatial Transformer Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Inverse_Compositional_Spatial_CVPR_2017_paper.html,CVPR,2017,https://github.com/chenhsuanlin/inverse-compositional-STN,189,2019-01-02 -Learning From Synthetic Humans,http://openaccess.thecvf.com/content_cvpr_2017/html/Varol_Learning_From_Synthetic_CVPR_2017_paper.html,CVPR,2017,https://github.com/gulvarol/surreal,207,2019-01-02 -Joint Unsupervised Learning of Deep Representations and Image Clusters,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Joint_Unsupervised_Learning_CVPR_2016_paper.html,CVPR,2016,https://github.com/jwyang/JULE.torch,182,2019-01-02 -Multi-Content GAN for Few-Shot Font Style Transfer,http://openaccess.thecvf.com/content_cvpr_2018/papers/Azadi_Multi-Content_GAN_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/azadis/MC-GAN,218,2019-01-02 -Staple: Complementary Learners for Real-Time Tracking,http://openaccess.thecvf.com/content_cvpr_2016/html/Bertinetto_Staple_Complementary_Learners_CVPR_2016_paper.html,CVPR,2016,https://github.com/bertinetto/staple,183,2019-01-02 -Learning Feature Pyramids for Human Pose Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Yang_Learning_Feature_Pyramids_ICCV_2017_paper.html,ICCV,2017,https://github.com/bearpaw/PyraNet,185,2019-01-02 -Be Your Own Prada: Fashion Synthesis With Structural Coherence,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Be_Your_Own_ICCV_2017_paper.html,ICCV,2017,https://github.com/zhusz/ICCV17-fashionGAN,183,2019-01-02 -3D Bounding Box Estimation Using Deep Learning and Geometry,http://openaccess.thecvf.com/content_cvpr_2017/html/Mousavian_3D_Bounding_Box_CVPR_2017_paper.html,CVPR,2017,https://github.com/smallcorgi/3D-Deepbox,200,2019-01-02 -OnACID: Online Analysis of Calcium Imaging Data in Real Time,http://papers.nips.cc/paper/6832-onacid-online-analysis-of-calcium-imaging-data-in-real-time.pdf,NIPS,2017,https://github.com/simonsfoundation/caiman,189,2019-01-02 -Learning to Reason: End-To-End Module Networks for Visual Question Answering,http://openaccess.thecvf.com/content_iccv_2017/html/Hu_Learning_to_Reason_ICCV_2017_paper.html,ICCV,2017,https://github.com/ronghanghu/n2nmn,178,2019-01-02 -SPLATNet: Sparse Lattice Networks for Point Cloud Processing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Su_SPLATNet_Sparse_Lattice_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/NVlabs/splatnet,188,2019-01-02 -Accurate Image Super-Resolution Using Very Deep Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Kim_Accurate_Image_Super-Resolution_CVPR_2016_paper.html,CVPR,2016,https://github.com/Jongchan/tensorflow-vdsr,182,2019-01-02 -Multi-View 3D Object Detection Network for Autonomous Driving,http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Multi-View_3D_Object_CVPR_2017_paper.html,CVPR,2017,https://github.com/bostondiditeam/MV3D,199,2019-01-02 -Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment With Limited Resources,http://openaccess.thecvf.com/content_iccv_2017/html/Bulat_Binarized_Convolutional_Landmark_ICCV_2017_paper.html,ICCV,2017,https://github.com/1adrianb/binary-human-pose-estimation,175,2019-01-02 -Learning Efficient Convolutional Networks Through Network Slimming,http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Learning_Efficient_Convolutional_ICCV_2017_paper.html,ICCV,2017,https://github.com/liuzhuang13/slimming,186,2019-01-02 -Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis,http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Beyond_Face_Rotation_ICCV_2017_paper.html,ICCV,2017,https://github.com/HRLTY/TP-GAN,202,2019-01-02 -GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium,http://papers.nips.cc/paper/7240-gans-trained-by-a-two-time-scale-update-rule-converge-to-a-local-nash-equilibrium.pdf,NIPS,2017,https://github.com/bioinf-jku/TTUR,229,2019-01-02 -Render for CNN: Viewpoint Estimation in Images Using CNNs Trained With Rendered 3D Model Views,http://openaccess.thecvf.com/content_iccv_2015/html/Su_Render_for_CNN_ICCV_2015_paper.html,ICCV,2015,https://github.com/ShapeNet/RenderForCNN,176,2019-01-02 -Realtime Edge-Based Visual Odometry for a Monocular Camera,http://openaccess.thecvf.com/content_iccv_2015/html/Tarrio_Realtime_Edge-Based_Visual_ICCV_2015_paper.html,ICCV,2015,https://github.com/JuanTarrio/rebvo,175,2019-01-02 -Fast Image Processing With Fully-Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Fast_Image_Processing_ICCV_2017_paper.html,ICCV,2017,https://github.com/CQFIO/FastImageProcessing,180,2019-01-02 -Temporal Action Localization in Untrimmed Videos via Multi-Stage CNNs,http://openaccess.thecvf.com/content_cvpr_2016/html/Shou_Temporal_Action_Localization_CVPR_2016_paper.html,CVPR,2016,https://github.com/zhengshou/scnn,167,2019-01-02 -Scene Graph Generation by Iterative Message Passing,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Scene_Graph_Generation_CVPR_2017_paper.html,CVPR,2017,https://github.com/danfeiX/scene-graph-TF-release,182,2019-01-02 -Attentive Generative Adversarial Network for Raindrop Removal From a Single Image,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qian_Attentive_Generative_Adversarial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rui1996/DeRaindrop,186,2019-01-02 -Single View Stereo Matching,http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_Single_View_Stereo_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lawy623/SVS,182,2019-01-02 -Unsupervised Feature Learning via Non-Parametric Instance Discrimination,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Unsupervised_Feature_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhirongw/lemniscate.pytorch,180,2019-01-02 -An End-to-End TextSpotter With Explicit Alignment and Attention,http://openaccess.thecvf.com/content_cvpr_2018/papers/He_An_End-to-End_TextSpotter_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tonghe90/textspotter,195,2019-01-02 -Single Shot Text Detector With Regional Attention,http://openaccess.thecvf.com/content_iccv_2017/html/He_Single_Shot_Text_ICCV_2017_paper.html,ICCV,2017,https://github.com/BestSonny/SSTD,176,2019-01-02 -Social GAN: Socially Acceptable Trajectories With Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gupta_Social_GAN_Socially_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/agrimgupta92/sgan,178,2019-01-02 -LocNet: Improving Localization Accuracy for Object Detection,http://openaccess.thecvf.com/content_cvpr_2016/html/Gidaris_LocNet_Improving_Localization_CVPR_2016_paper.html,CVPR,2016,https://github.com/gidariss/LocNet,155,2019-01-02 -ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_ST-GAN_Spatial_Transformer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chenhsuanlin/spatial-transformer-GAN,179,2019-01-02 -Image Super-Resolution via Deep Recursive Residual Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Tai_Image_Super-Resolution_via_CVPR_2017_paper.html,CVPR,2017,https://github.com/tyshiwo/DRRN_CVPR17,163,2019-01-02 -Input Convex Neural Networks,http://proceedings.mlr.press/v70/amos17b.html,ICML,2017,https://github.com/locuslab/icnn,159,2019-01-02 -Understanding Deep Image Representations by Inverting Them,http://openaccess.thecvf.com/content_cvpr_2015/html/Mahendran_Understanding_Deep_Image_2015_CVPR_paper.html,CVPR,2015,https://github.com/aravindhm/deep-goggle,154,2019-01-02 -Evolved Policy Gradients,http://arxiv.org/abs/1802.04821v2,NIPS,2018,https://github.com/openai/EPG,160,2019-01-02 -Oriented Response Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Oriented_Response_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/ZhouYanzhao/ORN,157,2019-01-02 -Large-Scale Point Cloud Semantic Segmentation With Superpoint Graphs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Landrieu_Large-Scale_Point_Cloud_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/loicland/superpoint_graph,197,2019-01-02 -Optimizing Video Object Detection via a Scale-Time Lattice,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Optimizing_Video_Object_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hellock/scale-time-lattice,168,2019-01-02 -Learning Multiple Tasks with Multilinear Relationship Networks,http://papers.nips.cc/paper/6757-learning-multiple-tasks-with-multilinear-relationship-networks.pdf,NIPS,2017,https://github.com/thuml/Xlearn,178,2019-01-02 -Face Alignment at 3000 FPS via Regressing Local Binary Features,http://openaccess.thecvf.com/content_cvpr_2014/html/Ren_Face_Alignment_at_2014_CVPR_paper.html,CVPR,2014,https://github.com/luoyetx/face-alignment-at-3000fps,164,2019-01-02 -Learning Cross-Modal Embeddings for Cooking Recipes and Food Images,http://openaccess.thecvf.com/content_cvpr_2017/html/Salvador_Learning_Cross-Modal_Embeddings_CVPR_2017_paper.html,CVPR,2017,https://github.com/torralba-lab/im2recipe,160,2019-01-02 -Learning Category-Specific Mesh Reconstruction from Image Collections,http://openaccess.thecvf.com/content_ECCV_2018/html/Angjoo_Kanazawa_Learning_Category-Specific_Mesh_ECCV_2018_paper.html,ECCV,2018,https://github.com/akanazawa/cmr,176,2019-01-02 -Group Normalization,http://openaccess.thecvf.com/content_ECCV_2018/html/Yuxin_Wu_Group_Normalization_ECCV_2018_paper.html,ECCV,2018,https://github.com/shaohua0116/Group-Normalization-Tensorflow,175,2019-01-02 -On Human Motion Prediction Using Recurrent Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Martinez_On_Human_Motion_CVPR_2017_paper.html,CVPR,2017,https://github.com/una-dinosauria/human-motion-prediction,167,2019-01-02 -Language Modeling with Recurrent Highway Hypernetworks,http://papers.nips.cc/paper/6919-language-modeling-with-recurrent-highway-hypernetworks.pdf,NIPS,2017,https://github.com/jsuarez5341/Recurrent-Highway-Hypernetworks-NIPS,141,2019-01-02 -Context-Aware CNNs for Person Head Detection,http://openaccess.thecvf.com/content_iccv_2015/html/Vu_Context-Aware_CNNs_for_ICCV_2015_paper.html,ICCV,2015,https://github.com/aosokin/cnn_head_detection,153,2019-01-02 -Soft Proposal Networks for Weakly Supervised Object Localization,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Soft_Proposal_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/yeezhu/SPN.pytorch,154,2019-01-02 -DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kupyn_DeblurGAN_Blind_Motion_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/RaphaelMeudec/deblur-gan,189,2019-01-02 -MegaDepth: Learning Single-View Depth Prediction From Internet Photos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_MegaDepth_Learning_Single-View_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lixx2938/MegaDepth,181,2019-01-02 -Shallow and Deep Convolutional Networks for Saliency Prediction,http://openaccess.thecvf.com/content_cvpr_2016/html/Pan_Shallow_and_Deep_CVPR_2016_paper.html,CVPR,2016,https://github.com/imatge-upc/saliency-2016-cvpr,153,2019-01-02 -ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_ShuffleNet_An_Extremely_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/camel007/Caffe-ShuffleNet,152,2019-01-02 -Axiomatic Attribution for Deep Networks,http://proceedings.mlr.press/v70/sundararajan17a.html,ICML,2017,https://github.com/hiranumn/IntegratedGradients,146,2019-01-02 -Compact Bilinear Pooling,http://openaccess.thecvf.com/content_cvpr_2016/html/Gao_Compact_Bilinear_Pooling_CVPR_2016_paper.html,CVPR,2016,https://github.com/gy20073/compact_bilinear_pooling,148,2019-01-02 -Simple Does It: Weakly Supervised Instance and Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Khoreva_Simple_Does_It_CVPR_2017_paper.html,CVPR,2017,https://github.com/philferriere/tfwss,159,2019-01-02 -Low-Shot Visual Recognition by Shrinking and Hallucinating Features,http://openaccess.thecvf.com/content_iccv_2017/html/Hariharan_Low-Shot_Visual_Recognition_ICCV_2017_paper.html,ICCV,2017,https://github.com/facebookresearch/low-shot-shrink-hallucinate,158,2019-01-02 -BSN: Boundary Sensitive Network for Temporal Action Proposal Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Tianwei_Lin_BSN_Boundary_Sensitive_ECCV_2018_paper.html,ECCV,2018,https://github.com/wzmsltw/BSN-boundary-sensitive-network,175,2019-01-02 -Deep Feature Interpolation for Image Content Changes,http://openaccess.thecvf.com/content_cvpr_2017/html/Upchurch_Deep_Feature_Interpolation_CVPR_2017_paper.html,CVPR,2017,https://github.com/paulu/deepfeatinterp,170,2019-01-02 -Deep Clustering for Unsupervised Learning of Visual Features,http://openaccess.thecvf.com/content_ECCV_2018/html/Mathilde_Caron_Deep_Clustering_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/facebookresearch/deepcluster,302,2019-01-02 -Learning a Single Convolutional Super-Resolution Network for Multiple Degradations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Learning_a_Single_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cszn/SRMD,169,2019-01-02 -Facelet-Bank for Fast Portrait Manipulation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Facelet-Bank_for_Fast_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yingcong/Facelet_Bank,150,2019-01-02 -Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning,http://papers.nips.cc/paper/6974-interpolated-policy-gradient-merging-on-policy-and-off-policy-gradient-estimation-for-deep-reinforcement-learning.pdf,NIPS,2017,https://github.com/shaneshixiang/rllabplusplus,138,2019-01-02 -Learning Compact Binary Descriptors With Unsupervised Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Lin_Learning_Compact_Binary_CVPR_2016_paper.html,CVPR,2016,https://github.com/kevinlin311tw/cvpr16-deepbit,144,2019-01-02 -Image Super-Resolution Using Very Deep Residual Channel Attention Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Yulun_Zhang_Image_Super-Resolution_Using_ECCV_2018_paper.html,ECCV,2018,https://github.com/yulunzhang/RCAN,234,2019-01-02 -ECO: Efficient Convolutional Network for Online Video Understanding,http://openaccess.thecvf.com/content_ECCV_2018/html/Mohammadreza_Zolfaghari_ECO_Efficient_Convolutional_ECCV_2018_paper.html,ECCV,2018,https://github.com/mzolfaghari/ECO-efficient-video-understanding,180,2019-01-02 -PlaneNet: Piece-Wise Planar Reconstruction From a Single RGB Image,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_PlaneNet_Piece-Wise_Planar_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/art-programmer/PlaneNet,164,2019-01-02 -Self-Imitation Learning,http://proceedings.mlr.press/v80/oh18b.html,ICML,2018,https://github.com/junhyukoh/self-imitation-learning,145,2019-01-02 -Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks,http://proceedings.mlr.press/v70/mescheder17a.html,ICML,2017,https://github.com/LMescheder/AdversarialVariationalBayes,147,2019-01-02 -Residual Dense Network for Image Super-Resolution,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Residual_Dense_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yulunzhang/RDN,163,2019-01-02 -Attend to You: Personalized Image Captioning With Context Sequence Memory Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Attend_to_You_CVPR_2017_paper.html,CVPR,2017,https://github.com/cesc-park/attend2u,143,2019-01-02 -Face Alignment by Coarse-to-Fine Shape Searching,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html,CVPR,2015,https://github.com/zhusz/CVPR15-CFSS,140,2019-01-02 -Triple Generative Adversarial Nets,http://papers.nips.cc/paper/6997-triple-generative-adversarial-nets.pdf,NIPS,2017,https://github.com/zhenxuan00/triple-gan,138,2019-01-02 -Embodied Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Das_Embodied_Question_Answering_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/facebookresearch/EmbodiedQA,162,2019-01-02 -Conditional Similarity Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Veit_Conditional_Similarity_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/andreasveit/conditional-similarity-networks,142,2019-01-02 -Two-Stream Convolutional Networks for Dynamic Texture Synthesis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tesfaldet_Two-Stream_Convolutional_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ryersonvisionlab/two-stream-dyntex-synth,141,2019-01-02 -Unsupervised Cross-Dataset Person Re-Identification by Transfer Learning of Spatial-Temporal Patterns,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lv_Unsupervised_Cross-Dataset_Person_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ahangchen/TFusion,166,2019-01-02 -Attentive Recurrent Comparators,http://proceedings.mlr.press/v70/shyam17a.html,ICML,2017,https://github.com/sanyam5/arc-pytorch,136,2019-01-02 -One-Sided Unsupervised Domain Mapping,http://papers.nips.cc/paper/6677-one-sided-unsupervised-domain-mapping.pdf,NIPS,2017,https://github.com/sagiebenaim/DistanceGAN,137,2019-01-02 -Densely Connected Pyramid Dehazing Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Densely_Connected_Pyramid_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hezhangsprinter/DCPDN,155,2019-01-02 -Detecting Visual Relationships With Deep Relational Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Dai_Detecting_Visual_Relationships_CVPR_2017_paper.html,CVPR,2017,https://github.com/doubledaibo/drnet_cvpr2017,137,2019-01-02 -Rethinking the Inception Architecture for Computer Vision,http://openaccess.thecvf.com/content_cvpr_2016/html/Szegedy_Rethinking_the_Inception_CVPR_2016_paper.html,CVPR,2016,https://github.com/Moodstocks/inception-v3.torch,130,2019-01-02 -Show and Tell: A Neural Image Caption Generator,http://openaccess.thecvf.com/content_cvpr_2015/html/Vinyals_Show_and_Tell_2015_CVPR_paper.html,CVPR,2015,https://github.com/KranthiGV/Pretrained-Show-and-Tell-model,141,2019-01-02 -Camera Style Adaptation for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhong_Camera_Style_Adaptation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhunzhong07/CamStyle,159,2019-01-02 -Neural Motifs: Scene Graph Parsing With Global Context,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zellers_Neural_Motifs_Scene_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rowanz/neural-motifs,171,2019-01-02 -Gradient Episodic Memory for Continual Learning,http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf,NIPS,2017,https://github.com/facebookresearch/GradientEpisodicMemory,146,2019-01-02 -CREST: Convolutional Residual Learning for Visual Tracking,http://openaccess.thecvf.com/content_iccv_2017/html/Song_CREST_Convolutional_Residual_ICCV_2017_paper.html,ICCV,2017,https://github.com/ybsong00/CREST-Release,126,2019-01-02 -Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer,http://openaccess.thecvf.com/content_cvpr_2018/papers/Fang_Weakly_and_Semi_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MVIG-SJTU/WSHP,159,2019-01-02 -Controlling Perceptual Factors in Neural Style Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Gatys_Controlling_Perceptual_Factors_CVPR_2017_paper.html,CVPR,2017,https://github.com/leongatys/NeuralImageSynthesis,130,2019-01-02 -LSTM Pose Machines,http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_LSTM_Pose_Machines_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lawy623/LSTM_Pose_Machines,141,2019-01-02 -Relational recurrent neural networks,https://arxiv.org/abs/1806.01822,NIPS,2018,https://github.com/L0SG/relational-rnn-pytorch,157,2019-01-02 -Multi-Context Attention for Human Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Chu_Multi-Context_Attention_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/bearpaw/pose-attention,131,2019-01-02 -SO-Net: Self-Organizing Network for Point Cloud Analysis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_SO-Net_Self-Organizing_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lijx10/SO-Net,152,2019-01-02 -SegFlow: Joint Learning for Video Object Segmentation and Optical Flow,http://openaccess.thecvf.com/content_iccv_2017/html/Cheng_SegFlow_Joint_Learning_ICCV_2017_paper.html,ICCV,2017,https://github.com/JingchunCheng/SegFlow,127,2019-01-02 -Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach,http://openaccess.thecvf.com/content_iccv_2017/html/Zhou_Towards_3D_Human_ICCV_2017_paper.html,ICCV,2017,https://github.com/xingyizhou/pose-hg-3d,136,2019-01-02 -Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Deng_Image-Image_Domain_Adaptation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Simon4Yan/Learning-via-Translation,137,2019-01-02 -An Improved Deep Learning Architecture for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2015/html/Ahmed_An_Improved_Deep_2015_CVPR_paper.html,CVPR,2015,https://github.com/Ning-Ding/Implementation-CVPR2015-CNN-for-ReID,127,2019-01-02 -Context Embedding Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kim_Context_Embedding_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/thunlp/CANE,131,2019-01-02 -Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model,http://papers.nips.cc/paper/7145-deep-learning-for-precipitation-nowcasting-a-benchmark-and-a-new-model.pdf,NIPS,2017,https://github.com/sxjscience/HKO-7,134,2019-01-02 -Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Song_Deep_Sliding_Shapes_CVPR_2016_paper.html,CVPR,2016,https://github.com/shurans/DeepSlidingShape,126,2019-01-02 -DSAC - Differentiable RANSAC for Camera Localization,http://openaccess.thecvf.com/content_cvpr_2017/html/Brachmann_DSAC_-_Differentiable_CVPR_2017_paper.html,CVPR,2017,https://github.com/cvlab-dresden/DSAC,144,2019-01-02 -Learning a Multi-View Stereo Machine,http://papers.nips.cc/paper/6640-learning-a-multi-view-stereo-machine.pdf,NIPS,2017,https://github.com/akar43/lsm,135,2019-01-02 -Segmentation-Aware Convolutional Networks Using Local Attention Masks,http://openaccess.thecvf.com/content_iccv_2017/html/Harley_Segmentation-Aware_Convolutional_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/aharley/segaware,126,2019-01-02 -Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Inoue_Cross-Domain_Weakly-Supervised_Object_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/naoto0804/cross-domain-detection,143,2019-01-02 -Bayesian Compression for Deep Learning,http://papers.nips.cc/paper/6921-bayesian-compression-for-deep-learning.pdf,NIPS,2017,https://github.com/KarenUllrich/Tutorial_BayesianCompressionForDL,130,2019-01-02 -Fast and Accurate Online Video Object Segmentation via Tracking Parts,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cheng_Fast_and_Accurate_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JingchunCheng/FAVOS,129,2019-01-02 -Learning to Compare: Relation Network for Few-Shot Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sung_Learning_to_Compare_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lzrobots/LearningToCompare_ZSL,135,2019-01-02 -Dynamic Image Networks for Action Recognition,http://openaccess.thecvf.com/content_cvpr_2016/html/Bilen_Dynamic_Image_Networks_CVPR_2016_paper.html,CVPR,2016,https://github.com/hbilen/dynamic-image-nets,133,2019-01-02 -Context Encoders: Feature Learning by Inpainting,http://openaccess.thecvf.com/content_cvpr_2016/html/Pathak_Context_Encoders_Feature_CVPR_2016_paper.html,CVPR,2016,https://github.com/jazzsaxmafia/Inpainting,124,2019-01-02 -Weakly Supervised Instance Segmentation Using Class Peak Response,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Weakly_Supervised_Instance_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ZhouYanzhao/PRM,166,2019-01-02 -MVSNet: Depth Inference for Unstructured Multi-view Stereo,http://openaccess.thecvf.com/content_ECCV_2018/html/Yao_Yao_MVSNet_Depth_Inference_ECCV_2018_paper.html,ECCV,2018,https://github.com/YoYo000/MVSNet,174,2019-01-02 -Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining,http://openaccess.thecvf.com/content_ECCV_2018/html/Xia_Li_Recurrent_Squeeze-and-Excitation_Context_ECCV_2018_paper.html,ECCV,2018,https://github.com/XiaLiPKU/RESCAN,142,2019-01-02 -L4: Practical loss-based stepsize adaptation for deep learning,http://arxiv.org/abs/1802.05074v4,NIPS,2018,https://github.com/martius-lab/l4-optimizer,123,2019-01-02 -Value Prediction Network,http://papers.nips.cc/paper/7192-value-prediction-network.pdf,NIPS,2017,https://github.com/junhyukoh/value-prediction-network,119,2019-01-02 -Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Structure_Inference_Net_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/choasup/SIN,140,2019-01-02 -Hierarchical Attentive Recurrent Tracking,http://papers.nips.cc/paper/6898-hierarchical-attentive-recurrent-tracking.pdf,NIPS,2017,https://github.com/akosiorek/hart,121,2019-01-02 -A Closer Look at Spatiotemporal Convolutions for Action Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tran_A_Closer_Look_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/irhumshafkat/R2Plus1D-PyTorch,143,2019-01-02 -Discriminative Correlation Filter With Channel and Spatial Reliability,http://openaccess.thecvf.com/content_cvpr_2017/html/Lukezic_Discriminative_Correlation_Filter_CVPR_2017_paper.html,CVPR,2017,https://github.com/alanlukezic/csr-dcf,124,2019-01-02 -Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_Pix3D_Dataset_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xingyuansun/pix3d,152,2019-01-02 -Unsupervised Learning of Monocular Depth Estimation and Visual Odometry With Deep Feature Reconstruction,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhan_Unsupervised_Learning_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Huangying-Zhan/Depth-VO-Feat,158,2019-01-02 -Learning by Association -- A Versatile Semi-Supervised Training Method for Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Haeusser_Learning_by_Association_CVPR_2017_paper.html,CVPR,2017,https://github.com/haeusser/learning_by_association,119,2019-01-02 -Associative Domain Adaptation,http://openaccess.thecvf.com/content_iccv_2017/html/Haeusser_Associative_Domain_Adaptation_ICCV_2017_paper.html,ICCV,2017,https://github.com/haeusser/learning_by_association,119,2019-01-02 -Concrete Dropout,http://papers.nips.cc/paper/6949-concrete-dropout.pdf,NIPS,2017,https://github.com/yaringal/ConcreteDropout,127,2019-01-02 -SVDNet for Pedestrian Retrieval,http://openaccess.thecvf.com/content_iccv_2017/html/Sun_SVDNet_for_Pedestrian_ICCV_2017_paper.html,ICCV,2017,https://github.com/syfafterzy/SVDNet-for-Pedestrian-Retrieval,121,2019-01-02 -MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network,http://openaccess.thecvf.com/content_ECCV_2018/html/Muhammed_Kocabas_MultiPoseNet_Fast_Multi-Person_ECCV_2018_paper.html,ECCV,2018,https://github.com/salihkaragoz/pose-residual-network-pytorch,167,2019-01-02 -Gated Path Planning Networks,http://proceedings.mlr.press/v80/lee18c.html,ICML,2018,https://github.com/lileee/gated-path-planning-networks,121,2019-01-02 -Semantic Image Synthesis via Adversarial Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Dong_Semantic_Image_Synthesis_ICCV_2017_paper.html,ICCV,2017,https://github.com/woozzu/dong_iccv_2017,121,2019-01-02 -"Depth-Based Hand Pose Estimation: Data, Methods, and Challenges",http://openaccess.thecvf.com/content_iccv_2015/html/Supancic_Depth-Based_Hand_Pose_ICCV_2015_paper.html,ICCV,2015,https://github.com/jsupancic/deep_hand_pose,121,2019-01-02 -Deep Pyramidal Residual Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Han_Deep_Pyramidal_Residual_CVPR_2017_paper.html,CVPR,2017,https://github.com/jhkim89/PyramidNet,112,2019-01-02 -Spatiotemporal Multiplier Networks for Video Action Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Feichtenhofer_Spatiotemporal_Multiplier_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/feichtenhofer/st-resnet,121,2019-01-02 -PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mallya_PackNet_Adding_Multiple_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/arunmallya/packnet,117,2019-01-02 -CosFace: Large Margin Cosine Loss for Deep Face Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_CosFace_Large_Margin_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yule-li/CosFace,135,2019-01-02 -Decoupled Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Decoupled_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wy1iu/DCNets,105,2019-01-02 -Video Based Reconstruction of 3D People Models,http://openaccess.thecvf.com/content_cvpr_2018/papers/Alldieck_Video_Based_Reconstruction_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/thmoa/videoavatars,179,2019-01-02 -Good Semi-supervised Learning That Requires a Bad GAN,http://papers.nips.cc/paper/7229-good-semi-supervised-learning-that-requires-a-bad-gan.pdf,NIPS,2017,https://github.com/kimiyoung/ssl_bad_gan,120,2019-01-02 -DeepMVS: Learning Multi-View Stereopsis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_DeepMVS_Learning_Multi-View_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/phuang17/DeepMVS,125,2019-01-02 -Deep Watershed Transform for Instance Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Bai_Deep_Watershed_Transform_CVPR_2017_paper.html,CVPR,2017,https://github.com/min2209/dwt,120,2019-01-02 -PoseTrack: Joint Multi-Person Pose Estimation and Tracking,http://openaccess.thecvf.com/content_cvpr_2017/html/Iqbal_PoseTrack_Joint_Multi-Person_CVPR_2017_paper.html,CVPR,2017,https://github.com/iqbalu/PoseTrack-CVPR2017,121,2019-01-02 -TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning,http://papers.nips.cc/paper/6749-terngrad-ternary-gradients-to-reduce-communication-in-distributed-deep-learning.pdf,NIPS,2017,https://github.com/wenwei202/terngrad,117,2019-01-02 -Adaptive Affinity Fields for Semantic Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Jyh-Jing_Hwang_Adaptive_Affinity_Field_ECCV_2018_paper.html,ECCV,2018,https://github.com/twke18/Adaptive_Affinity_Fields,141,2019-01-02 -"Show, Adapt and Tell: Adversarial Training of Cross-Domain Image Captioner",http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Show_Adapt_and_ICCV_2017_paper.html,ICCV,2017,https://github.com/tsenghungchen/show-adapt-and-tell,115,2019-01-02 -Real-Time Seamless Single Shot 6D Object Pose Prediction,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tekin_Real-Time_Seamless_Single_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Microsoft/singleshotpose,174,2019-01-02 -Hierarchical Imitation and Reinforcement Learning,http://proceedings.mlr.press/v80/le18a.html,ICML,2018,https://github.com/hoangminhle/hierarchical_IL_RL,124,2019-01-02 -TI-Pooling: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Laptev_TI-Pooling_Transformation-Invariant_Pooling_CVPR_2016_paper.html,CVPR,2016,https://github.com/dlaptev/TI-pooling,109,2019-01-02 -Bayesian Optimization with Gradients,http://papers.nips.cc/paper/7111-bayesian-optimization-with-gradients.pdf,NIPS,2017,https://github.com/wujian16/Cornell-MOE,117,2019-01-02 -MemNet: A Persistent Memory Network for Image Restoration,http://openaccess.thecvf.com/content_iccv_2017/html/Tai_MemNet_A_Persistent_ICCV_2017_paper.html,ICCV,2017,https://github.com/tyshiwo/MemNet,119,2019-01-02 -Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Split-Brain_Autoencoders_Unsupervised_CVPR_2017_paper.html,CVPR,2017,https://github.com/richzhang/splitbrainauto,110,2019-01-02 -Long-term Tracking in the Wild: a Benchmark,http://openaccess.thecvf.com/content_ECCV_2018/html/Efstratios_Gavves_Long-term_Tracking_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/oxuva/long-term-tracking-benchmark,116,2019-01-02 -Detail-Revealing Deep Video Super-Resolution,http://openaccess.thecvf.com/content_iccv_2017/html/Tao_Detail-Revealing_Deep_Video_ICCV_2017_paper.html,ICCV,2017,https://github.com/jiangsutx/SPMC_VideoSR,126,2019-01-02 -Realistic Evaluation of Deep Semi-Supervised Learning Algorithms,http://arxiv.org/abs/1804.09170v2,NIPS,2018,https://github.com/brain-research/realistic-ssl-evaluation,175,2019-01-02 -FaceNet: A Unified Embedding for Face Recognition and Clustering,http://openaccess.thecvf.com/content_cvpr_2015/html/Schroff_FaceNet_A_Unified_2015_CVPR_paper.html,CVPR,2015,https://github.com/liorshk/facenet_pytorch,124,2019-01-02 -Compressed Sensing using Generative Models,http://proceedings.mlr.press/v70/bora17a.html,ICML,2017,https://github.com/AshishBora/csgm,116,2019-01-02 -Unrestricted Facial Geometry Reconstruction Using Image-To-Image Translation,http://openaccess.thecvf.com/content_iccv_2017/html/Sela_Unrestricted_Facial_Geometry_ICCV_2017_paper.html,ICCV,2017,https://github.com/matansel/pix2vertex,119,2019-01-02 -Deep Back-Projection Networks for Super-Resolution,http://openaccess.thecvf.com/content_cvpr_2018/papers/Haris_Deep_Back-Projection_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/alterzero/DBPN-Pytorch,132,2019-01-02 -Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kendall_Multi-Task_Learning_Using_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/alexgkendall/multitaskvision,131,2019-01-02 -Deep Hyperspherical Learning,http://papers.nips.cc/paper/6984-deep-hyperspherical-learning.pdf,NIPS,2017,https://github.com/wy1iu/SphereNet,92,2019-01-02 -Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Recovering_Realistic_Texture_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xinntao/CVPR18-SFTGAN,139,2019-01-02 -Switching Convolutional Neural Network for Crowd Counting,http://openaccess.thecvf.com/content_cvpr_2017/html/Sam_Switching_Convolutional_Neural_CVPR_2017_paper.html,CVPR,2017,https://github.com/val-iisc/crowd-counting-scnn,116,2019-01-02 -3D-CODED: 3D Correspondences by Deep Deformation,http://openaccess.thecvf.com/content_ECCV_2018/html/Thibault_Groueix_Shape_correspondences_from_ECCV_2018_paper.html,ECCV,2018,https://github.com/ThibaultGROUEIX/3D-CODED,125,2019-01-02 -FeUdal Networks for Hierarchical Reinforcement Learning,http://proceedings.mlr.press/v70/vezhnevets17a.html,ICML,2017,https://github.com/dmakian/feudal_networks,107,2019-01-02 -PU-Net: Point Cloud Upsampling Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_PU-Net_Point_Cloud_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yulequan/PU-Net,117,2019-01-02 -Scale-Recurrent Network for Deep Image Deblurring,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tao_Scale-Recurrent_Network_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiangsutx/SRN-Deblur,159,2019-01-02 -"WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation",http://openaccess.thecvf.com/content_cvpr_2017/html/Durand_WILDCAT_Weakly_Supervised_CVPR_2017_paper.html,CVPR,2017,https://github.com/durandtibo/wildcat.pytorch,116,2019-01-02 -Noisy Natural Gradient as Variational Inference,http://proceedings.mlr.press/v80/zhang18l.html,ICML,2018,https://github.com/wlwkgus/NoisyNaturalGradient,108,2019-01-02 -Video Frame Synthesis Using Deep Voxel Flow,http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Video_Frame_Synthesis_ICCV_2017_paper.html,ICCV,2017,https://github.com/liuziwei7/voxel-flow,114,2019-01-02 -Working hard to know your neighbor's margins: Local descriptor learning loss,http://papers.nips.cc/paper/7068-working-hard-to-know-your-neighbors-margins-local-descriptor-learning-loss.pdf,NIPS,2017,https://github.com/DagnyT/hardnet,128,2019-01-02 -Domain Adaptive Faster R-CNN for Object Detection in the Wild,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Domain_Adaptive_Faster_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yuhuayc/da-faster-rcnn,123,2019-01-02 -"Train longer, generalize better: closing the generalization gap in large batch training of neural networks",http://papers.nips.cc/paper/6770-train-longer-generalize-better-closing-the-generalization-gap-in-large-batch-training-of-neural-networks.pdf,NIPS,2017,https://github.com/eladhoffer/bigBatch,112,2019-01-02 -Natural Language Object Retrieval,http://openaccess.thecvf.com/content_cvpr_2016/html/Hu_Natural_Language_Object_CVPR_2016_paper.html,CVPR,2016,https://github.com/ronghanghu/natural-language-object-retrieval,100,2019-01-02 -Adversarial Discriminative Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2017/html/Tzeng_Adversarial_Discriminative_Domain_CVPR_2017_paper.html,CVPR,2017,https://github.com/corenel/pytorch-adda,129,2019-01-02 -Quantized Densely Connected U-Nets for Efficient Landmark Localization,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhiqiang_Tang_Quantized_Densely_Connected_ECCV_2018_paper.html,ECCV,2018,https://github.com/zhiqiangdon/CU-Net,143,2019-01-02 -Rethinking Feature Distribution for Loss Functions in Image Classification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wan_Rethinking_Feature_Distribution_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/WeitaoVan/L-GM-loss,120,2019-01-02 -DenseASPP for Semantic Segmentation in Street Scenes,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_DenseASPP_for_Semantic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/DeepMotionAIResearch/DenseASPP,151,2019-01-02 -ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression,http://openaccess.thecvf.com/content_iccv_2017/html/Luo_ThiNet_A_Filter_ICCV_2017_paper.html,ICCV,2017,https://github.com/Roll920/ThiNet,105,2019-01-02 -Graph R-CNN for Scene Graph Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Jianwei_Yang_Graph_R-CNN_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/jwyang/graph-rcnn.pytorch,144,2019-01-02 -"Factoring Shape, Pose, and Layout From the 2D Image of a 3D Scene",http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulsiani_Factoring_Shape_Pose_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shubhtuls/factored3d,114,2019-01-02 -Multi-View Supervision for Single-View Reconstruction via Differentiable Ray Consistency,http://openaccess.thecvf.com/content_cvpr_2017/html/Tulsiani_Multi-View_Supervision_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/shubhtuls/drc,100,2019-01-02 -Massively Parallel Multiview Stereopsis by Surface Normal Diffusion,http://openaccess.thecvf.com/content_iccv_2015/html/Galliani_Massively_Parallel_Multiview_ICCV_2015_paper.html,ICCV,2015,https://github.com/kysucix/gipuma,105,2019-01-02 -Deep Depth Completion of a Single RGB-D Image,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Deep_Depth_Completion_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yindaz/DeepCompletionRelease,134,2019-01-02 -Cross-Scale Cost Aggregation for Stereo Matching,http://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Cross-Scale_Cost_Aggregation_2014_CVPR_paper.html,CVPR,2014,https://github.com/rookiepig/CrossScaleStereo,106,2019-01-02 -Density-Aware Single Image De-Raining Using a Multi-Stream Dense Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Density-Aware_Single_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hezhangsprinter/DID-MDN,118,2019-01-02 -Weakly Supervised Deep Detection Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Bilen_Weakly_Supervised_Deep_CVPR_2016_paper.html,CVPR,2016,https://github.com/hbilen/WSDDN,103,2019-01-02 -Task-based End-to-end Model Learning in Stochastic Optimization,http://papers.nips.cc/paper/7132-task-based-end-to-end-model-learning-in-stochastic-optimization.pdf,NIPS,2017,https://github.com/locuslab/e2e-model-learning,100,2019-01-02 -MAttNet: Modular Attention Network for Referring Expression Comprehension,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_MAttNet_Modular_Attention_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lichengunc/MAttNet,104,2019-01-02 -Interleaved Group Convolutions,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Interleaved_Group_Convolutions_ICCV_2017_paper.html,ICCV,2017,https://github.com/hellozting/InterleavedGroupConvolutions,95,2019-01-02 -"Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis",http://proceedings.mlr.press/v80/wang18h.html,ICML,2018,https://github.com/syang1993/gst-tacotron,129,2019-01-02 -ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes,http://openaccess.thecvf.com/content_ECCV_2018/html/Taihong_Xiao_ELEGANT_Exchanging_Latent_ECCV_2018_paper.html,ECCV,2018,https://github.com/Prinsphield/ELEGANT,117,2019-01-02 -Learning to Propose Objects,http://openaccess.thecvf.com/content_cvpr_2015/html/Krahenbuhl_Learning_to_Propose_2015_CVPR_paper.html,CVPR,2015,https://github.com/philkr/lpo,91,2019-01-02 -Learning to Compose Domain-Specific Transformations for Data Augmentation,http://papers.nips.cc/paper/6916-learning-to-compose-domain-specific-transformations-for-data-augmentation.pdf,NIPS,2017,https://github.com/HazyResearch/tanda,97,2019-01-02 -Deeply-Recursive Convolutional Network for Image Super-Resolution,http://openaccess.thecvf.com/content_cvpr_2016/html/Kim_Deeply-Recursive_Convolutional_Network_CVPR_2016_paper.html,CVPR,2016,https://github.com/jiny2001/deeply-recursive-cnn-tf,96,2019-01-02 -Neural Arithmetic Logic Units,http://arxiv.org/abs/1808.00508v1,NIPS,2018,https://github.com/llSourcell/Neural_Arithmetic_Logic_Units,87,2019-01-02 -Learning a Deep Embedding Model for Zero-Shot Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Learning_a_Deep_CVPR_2017_paper.html,CVPR,2017,https://github.com/lzrobots/DeepEmbeddingModel_ZSL,104,2019-01-02 -Knowledge Aided Consistency for Weakly Supervised Phrase Grounding,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Knowledge_Aided_Consistency_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kanchen-usc/KAC-Net,87,2019-01-02 -AMC: Attention guided Multi-modal Correlation Learning for Image Search,http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_AMC_Attention_guided_CVPR_2017_paper.html,CVPR,2017,https://github.com/kanchen-usc/AMC_ATT,90,2019-01-02 -Perturbative Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Juefei-Xu_Perturbative_Neural_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/juefeix/pnn.pytorch,130,2019-01-02 -End-to-End Weakly-Supervised Semantic Alignment,http://openaccess.thecvf.com/content_cvpr_2018/papers/Rocco_End-to-End_Weakly-Supervised_Semantic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ignacio-rocco/weakalign,106,2019-01-02 -Repulsion Loss: Detecting Pedestrians in a Crowd,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Repulsion_Loss_Detecting_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/bailvwangzi/repulsion_loss_ssd,113,2019-01-02 -Decoupled Neural Interfaces using Synthetic Gradients,http://proceedings.mlr.press/v70/jaderberg17a.html,ICML,2017,https://github.com/andrewliao11/dni.pytorch,90,2019-01-02 -Image Question Answering Using Convolutional Neural Network With Dynamic Parameter Prediction,http://openaccess.thecvf.com/content_cvpr_2016/html/Noh_Image_Question_Answering_CVPR_2016_paper.html,CVPR,2016,https://github.com/HyeonwooNoh/DPPnet,88,2019-01-02 -Semantic Autoencoder for Zero-Shot Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Kodirov_Semantic_Autoencoder_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/Elyorcv/SAE,92,2019-01-02 -Unite the People: Closing the Loop Between 3D and 2D Human Representations,http://openaccess.thecvf.com/content_cvpr_2017/html/Lassner_Unite_the_People_CVPR_2017_paper.html,CVPR,2017,https://github.com/classner/up,110,2019-01-02 -Genetic CNN,http://openaccess.thecvf.com/content_iccv_2017/html/Xie_Genetic_CNN_ICCV_2017_paper.html,ICCV,2017,https://github.com/aqibsaeed/Genetic-CNN,97,2019-01-02 -HashNet: Deep Learning to Hash by Continuation,http://openaccess.thecvf.com/content_iccv_2017/html/Cao_HashNet_Deep_Learning_ICCV_2017_paper.html,ICCV,2017,https://github.com/thuml/HashNet,97,2019-01-02 -Learning Blind Video Temporal Consistency,http://openaccess.thecvf.com/content_ECCV_2018/html/Wei-Sheng_Lai_Real-Time_Blind_Video_ECCV_2018_paper.html,ECCV,2018,https://github.com/phoenix104104/fast_blind_video_consistency,109,2019-01-02 -ECO: Efficient Convolution Operators for Tracking,http://openaccess.thecvf.com/content_cvpr_2017/html/Danelljan_ECO_Efficient_Convolution_CVPR_2017_paper.html,CVPR,2017,https://github.com/nicewsyly/ECO,103,2019-01-02 -PSANet: Point-wise Spatial Attention Network for Scene Parsing,http://openaccess.thecvf.com/content_ECCV_2018/html/Hengshuang_Zhao_PSANet_Point-wise_Spatial_ECCV_2018_paper.html,ECCV,2018,https://github.com/hszhao/PSANet,121,2019-01-02 -Learning Combinatorial Optimization Algorithms over Graphs,http://papers.nips.cc/paper/7214-learning-combinatorial-optimization-algorithms-over-graphs.pdf,NIPS,2017,https://github.com/Hanjun-Dai/graph_comb_opt,109,2019-01-02 -Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model,http://papers.nips.cc/paper/6635-best-of-both-worlds-transferring-knowledge-from-discriminative-learning-to-a-generative-visual-dialog-model.pdf,NIPS,2017,https://github.com/jiasenlu/visDial.pytorch,94,2019-01-02 -Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights,http://openaccess.thecvf.com/content_ECCV_2018/html/Arun_Mallya_Piggyback_Adapting_a_ECCV_2018_paper.html,ECCV,2018,https://github.com/arunmallya/piggyback,88,2019-01-02 -SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_SCA-CNN_Spatial_and_CVPR_2017_paper.html,CVPR,2017,https://github.com/zjuchenlong/sca-cnn.cvpr17,102,2019-01-02 -GANs for Biological Image Synthesis,http://openaccess.thecvf.com/content_iccv_2017/html/Osokin_GANs_for_Biological_ICCV_2017_paper.html,ICCV,2017,https://github.com/aosokin/biogans,85,2019-01-02 -Fast-Slow Recurrent Neural Networks,http://papers.nips.cc/paper/7173-fast-slow-recurrent-neural-networks.pdf,NIPS,2017,https://github.com/amujika/Fast-Slow-LSTM,82,2019-01-02 -Nonlinear 3D Face Morphable Model,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tran_Nonlinear_3D_Face_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tranluan/Nonlinear_Face_3DMM,128,2019-01-02 -Deep Mutual Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Deep_Mutual_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/YingZhangDUT/Deep-Mutual-Learning,100,2019-01-02 -DynamicFusion: Reconstruction and Tracking of Non-Rigid Scenes in Real-Time,http://openaccess.thecvf.com/content_cvpr_2015/html/Newcombe_DynamicFusion_Reconstruction_and_2015_CVPR_paper.html,CVPR,2015,https://github.com/mihaibujanca/dynamicfusion,118,2019-01-02 -Octree Generating Networks: Efficient Convolutional Architectures for High-Resolution 3D Outputs,http://openaccess.thecvf.com/content_iccv_2017/html/Tatarchenko_Octree_Generating_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/lmb-freiburg/ogn,92,2019-01-02 -Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search,http://papers.nips.cc/paper/6780-practical-bayesian-optimization-for-model-fitting-with-bayesian-adaptive-direct-search.pdf,NIPS,2017,https://github.com/lacerbi/bads,90,2019-01-02 -Optical Flow in Mostly Rigid Scenes,http://openaccess.thecvf.com/content_cvpr_2017/html/Wulff_Optical_Flow_in_CVPR_2017_paper.html,CVPR,2017,https://github.com/jswulff/mrflow,83,2019-01-02 -Representation Learning by Learning to Count,http://openaccess.thecvf.com/content_iccv_2017/html/Noroozi_Representation_Learning_by_ICCV_2017_paper.html,ICCV,2017,https://github.com/gitlimlab/Representation-Learning-by-Learning-to-Count,84,2019-01-02 -Image Inpainting for Irregular Holes Using Partial Convolutions,http://openaccess.thecvf.com/content_ECCV_2018/html/Guilin_Liu_Image_Inpainting_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/naoto0804/pytorch-inpainting-with-partial-conv,153,2019-01-02 -Deeply-Learned Part-Aligned Representations for Person Re-Identification,http://openaccess.thecvf.com/content_iccv_2017/html/Zhao_Deeply-Learned_Part-Aligned_Representations_ICCV_2017_paper.html,ICCV,2017,https://github.com/zlmzju/part_reid,95,2019-01-02 -Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data,http://papers.nips.cc/paper/6784-unsupervised-learning-of-disentangled-and-interpretable-representations-from-sequential-data.pdf,NIPS,2017,https://github.com/wnhsu/FactorizedHierarchicalVAE,88,2019-01-02 -Deep Video Deblurring for Hand-Held Cameras,http://openaccess.thecvf.com/content_cvpr_2017/html/Su_Deep_Video_Deblurring_CVPR_2017_paper.html,CVPR,2017,https://github.com/shuochsu/DeepVideoDeblurring,89,2019-01-02 -A Comparative Study for Single Image Blind Deblurring,http://openaccess.thecvf.com/content_cvpr_2016/html/Lai_A_Comparative_Study_CVPR_2016_paper.html,CVPR,2016,https://github.com/phoenix104104/cvpr16_deblur_study,82,2019-01-02 -BodyNet: Volumetric Inference of 3D Human Body Shapes,http://openaccess.thecvf.com/content_ECCV_2018/html/Gul_Varol_BodyNet_Volumetric_Inference_ECCV_2018_paper.html,ECCV,2018,https://github.com/gulvarol/bodynet,126,2019-01-02 -Causal Effect Inference with Deep Latent-Variable Models,http://papers.nips.cc/paper/7223-causal-effect-inference-with-deep-latent-variable-models.pdf,NIPS,2017,https://github.com/AMLab-Amsterdam/CEVAE,87,2019-01-02 -FSRNet: End-to-End Learning Face Super-Resolution With Facial Priors,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_FSRNet_End-to-End_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tyshiwo/FSRNet,100,2019-01-02 -Multiple Instance Detection Network With Online Instance Classifier Refinement,http://openaccess.thecvf.com/content_cvpr_2017/html/Tang_Multiple_Instance_Detection_CVPR_2017_paper.html,CVPR,2017,https://github.com/ppengtang/oicr,113,2019-01-02 -MMD GAN: Towards Deeper Understanding of Moment Matching Network,http://papers.nips.cc/paper/6815-mmd-gan-towards-deeper-understanding-of-moment-matching-network.pdf,NIPS,2017,https://github.com/OctoberChang/MMD-GAN,84,2019-01-02 -Recurrent Convolutional Network for Video-Based Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2016/html/McLaughlin_Recurrent_Convolutional_Network_CVPR_2016_paper.html,CVPR,2016,https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID,82,2019-01-02 -Integral Human Pose Regression,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiao_Sun_Integral_Human_Pose_ECCV_2018_paper.html,ECCV,2018,https://github.com/JimmySuen/integral-human-pose,141,2019-01-02 -LiDAR-Video Driving Dataset: Learning Driving Policies Effectively,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_LiDAR-Video_Driving_Dataset_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/driving-behavior/DBNet,104,2019-01-02 -Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Multi-Scale_Continuous_CRFs_CVPR_2017_paper.html,CVPR,2017,https://github.com/danxuhk/ContinuousCRF-CNN,93,2019-01-02 -Attention-based Deep Multiple Instance Learning,http://proceedings.mlr.press/v80/ilse18a.html,ICML,2018,https://github.com/AMLab-Amsterdam/AttentionDeepMIL,109,2019-01-02 -Multi-View Consistency as Supervisory Signal for Learning Shape and Pose Prediction,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulsiani_Multi-View_Consistency_as_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shubhtuls/mvcSnP,80,2019-01-02 -Macro-Micro Adversarial Network for Human Parsing,http://openaccess.thecvf.com/content_ECCV_2018/html/Yawei_Luo_Macro-Micro_Adversarial_Network_ECCV_2018_paper.html,ECCV,2018,https://github.com/RoyalVane/MMAN,98,2019-01-02 -A Convolutional Neural Network Cascade for Face Detection,http://openaccess.thecvf.com/content_cvpr_2015/html/Li_A_Convolutional_Neural_2015_CVPR_paper.html,CVPR,2015,https://github.com/mks0601/A-Convolutional-Neural-Network-Cascade-for-Face-Detection,85,2019-01-02 -Neural Module Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Andreas_Neural_Module_Networks_CVPR_2016_paper.html,CVPR,2016,https://github.com/HarshTrivedi/nmn-pytorch,81,2019-01-02 -Multi-view to Novel view: Synthesizing novel views with Self-Learned Confidence,http://openaccess.thecvf.com/content_ECCV_2018/html/Shao-Hua_Sun_Multi-view_to_Novel_ECCV_2018_paper.html,ECCV,2018,https://github.com/shaohua0116/Multiview2Novelview,92,2019-01-02 -Neural Kinematic Networks for Unsupervised Motion Retargetting,http://openaccess.thecvf.com/content_cvpr_2018/papers/Villegas_Neural_Kinematic_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rubenvillegas/cvpr2018nkn,90,2019-01-02 -LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Dongqing_Zhang_Optimized_Quantization_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/Microsoft/LQ-Nets,103,2019-01-02 -Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Spatial-Temporal_Regularized_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lifeng9472/STRCF,86,2019-01-02 -Learning Spatially Regularized Correlation Filters for Visual Tracking,http://openaccess.thecvf.com/content_iccv_2015/html/Danelljan_Learning_Spatially_Regularized_ICCV_2015_paper.html,ICCV,2015,https://github.com/lifeng9472/STRCF,86,2019-01-02 -DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data,http://openaccess.thecvf.com/content_cvpr_2017/html/Gurumurthy_DeLiGAN__Generative_CVPR_2017_paper.html,CVPR,2017,https://github.com/val-iisc/deligan,78,2019-01-02 -A PID Controller Approach for Stochastic Optimization of Deep Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/An_A_PID_Controller_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tensorboy/PIDOptimizer,87,2019-01-02 -A-NICE-MC: Adversarial Training for MCMC,http://papers.nips.cc/paper/7099-a-nice-mc-adversarial-training-for-mcmc.pdf,NIPS,2017,https://github.com/jiamings/a-nice-mc,80,2019-01-02 -Coarse-To-Fine Volumetric Prediction for Single-Image 3D Human Pose,http://openaccess.thecvf.com/content_cvpr_2017/html/Pavlakos_Coarse-To-Fine_Volumetric_Prediction_CVPR_2017_paper.html,CVPR,2017,https://github.com/geopavlakos/c2f-vol-train,80,2019-01-02 -Synthesizing Images of Humans in Unseen Poses,http://openaccess.thecvf.com/content_cvpr_2018/papers/Balakrishnan_Synthesizing_Images_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/balakg/posewarp-cvpr2018,88,2019-01-02 -Tell Me Where to Look: Guided Attention Inference Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Tell_Me_Where_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/alokwhitewolf/Guided-Attention-Inference-Network,91,2019-01-02 -Stacked Attention Networks for Image Question Answering,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Stacked_Attention_Networks_CVPR_2016_paper.html,CVPR,2016,https://github.com/zcyang/imageqa-san,78,2019-01-02 -VITAL: VIsual Tracking via Adversarial Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_VITAL_VIsual_Tracking_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ybsong00/Vital_release,86,2019-01-02 -VITON: An Image-Based Virtual Try-On Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Han_VITON_An_Image-Based_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xthan/VITON,95,2019-01-02 -Recurrent Relational Networks,http://arxiv.org/abs/1711.08028v2,NIPS,2018,https://github.com/rasmusbergpalm/recurrent-relational-networks,121,2019-01-02 -Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network,http://openaccess.thecvf.com/content_cvpr_2016/html/Shi_Real-Time_Single_Image_CVPR_2016_paper.html,CVPR,2016,https://github.com/leftthomas/ESPCN,92,2019-01-02 -Local Binary Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Juefei-Xu_Local_Binary_Convolutional_CVPR_2017_paper.html,CVPR,2017,https://github.com/juefeix/lbcnn.torch,77,2019-01-02 -Unsupervised Video Summarization With Adversarial LSTM Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Mahasseni_Unsupervised_Video_Summarization_CVPR_2017_paper.html,CVPR,2017,https://github.com/j-min/Adversarial_Video_Summary,82,2019-01-02 -Multi-Scale Location-Aware Kernel Representation for Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Multi-Scale_Location-Aware_Kernel_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Hwang64/MLKP,84,2019-01-02 -Future Frame Prediction for Anomaly Detection – A New Baseline,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Future_Frame_Prediction_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/StevenLiuWen/ano_pred_cvpr2018,92,2019-01-02 -Hard-Aware Deeply Cascaded Embedding,http://openaccess.thecvf.com/content_iccv_2017/html/Yuan_Hard-Aware_Deeply_Cascaded_ICCV_2017_paper.html,ICCV,2017,https://github.com/PkuRainBow/Hard-Aware-Deeply-Cascaded-Embedding_release,75,2019-01-02 -Query-Guided Regression Network With Context Policy for Phrase Grounding,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Query-Guided_Regression_Network_ICCV_2017_paper.html,ICCV,2017,https://github.com/kanchen-usc/QRC-Net,72,2019-01-02 -End-To-End Instance Segmentation With Recurrent Attention,http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_End-To-End_Instance_Segmentation_CVPR_2017_paper.html,CVPR,2017,https://github.com/renmengye/rec-attend-public,78,2019-01-02 -Improved Stereo Matching With Constant Highway Networks and Reflective Confidence Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Shaked_Improved_Stereo_Matching_CVPR_2017_paper.html,CVPR,2017,https://github.com/amitshaked/resmatch,72,2019-01-02 -Progressive Prioritized Multi-View Stereo,http://openaccess.thecvf.com/content_cvpr_2016/html/Locher_Progressive_Prioritized_Multi-View_CVPR_2016_paper.html,CVPR,2016,https://github.com/alexlocher/hpmvs,73,2019-01-02 -Recurrent Pixel Embedding for Instance Grouping,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kong_Recurrent_Pixel_Embedding_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/aimerykong/Recurrent-Pixel-Embedding-for-Instance-Grouping,85,2019-01-02 -Learning Shape Abstractions by Assembling Volumetric Primitives,http://openaccess.thecvf.com/content_cvpr_2017/html/Tulsiani_Learning_Shape_Abstractions_CVPR_2017_paper.html,CVPR,2017,https://github.com/shubhtuls/volumetricPrimitives,77,2019-01-02 -Constrained Policy Optimization,http://proceedings.mlr.press/v70/achiam17a.html,ICML,2017,https://github.com/jachiam/cpo,81,2019-01-02 -Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks,http://papers.nips.cc/paper/6960-geometric-matrix-completion-with-recurrent-multi-graph-neural-networks.pdf,NIPS,2017,https://github.com/fmonti/mgcnn,90,2019-01-02 -Learning Human-Object Interactions by Graph Parsing Neural Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Siyuan_Qi_Learning_Human-Object_Interactions_ECCV_2018_paper.html,ECCV,2018,https://github.com/SiyuanQi/gpnn,93,2019-01-02 -Positive-Unlabeled Learning with Non-Negative Risk Estimator,http://papers.nips.cc/paper/6765-positive-unlabeled-learning-with-non-negative-risk-estimator.pdf,NIPS,2017,https://github.com/kiryor/nnPUlearning,76,2019-01-02 -Unsupervised Visual Representation Learning by Context Prediction,http://openaccess.thecvf.com/content_iccv_2015/html/Doersch_Unsupervised_Visual_Representation_ICCV_2015_paper.html,ICCV,2015,https://github.com/cdoersch/deepcontext,73,2019-01-02 -Top-Down Visual Saliency Guided by Captions,http://openaccess.thecvf.com/content_cvpr_2017/html/Ramanishka_Top-Down_Visual_Saliency_CVPR_2017_paper.html,CVPR,2017,https://github.com/VisionLearningGroup/caption-guided-saliency,72,2019-01-02 -Deep Image Harmonization,http://openaccess.thecvf.com/content_cvpr_2017/html/Tsai_Deep_Image_Harmonization_CVPR_2017_paper.html,CVPR,2017,https://github.com/wasidennis/DeepHarmonization,73,2019-01-02 -Visual Feature Attribution Using Wasserstein GANs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Baumgartner_Visual_Feature_Attribution_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/orobix/Visual-Feature-Attribution-Using-Wasserstein-GANs-Pytorch,72,2019-01-02 -A Hierarchical Deep Temporal Model for Group Activity Recognition,http://openaccess.thecvf.com/content_cvpr_2016/html/Ibrahim_A_Hierarchical_Deep_CVPR_2016_paper.html,CVPR,2016,https://github.com/mostafa-saad/deep-activity-rec,71,2019-01-02 -What Actions Are Needed for Understanding Human Actions in Videos?,http://openaccess.thecvf.com/content_iccv_2017/html/Sigurdsson_What_Actions_Are_ICCV_2017_paper.html,ICCV,2017,https://github.com/gsig/actions-for-actions,71,2019-01-02 -Discriminative Learning of Deep Convolutional Feature Point Descriptors,http://openaccess.thecvf.com/content_iccv_2015/html/Simo-Serra_Discriminative_Learning_of_ICCV_2015_paper.html,ICCV,2015,https://github.com/etrulls/deepdesc-release,77,2019-01-02 -Repeatability Is Not Enough: Learning Affine Regions via Discriminability,http://openaccess.thecvf.com/content_ECCV_2018/html/Dmytro_Mishkin_Repeatability_Is_Not_ECCV_2018_paper.html,ECCV,2018,https://github.com/ducha-aiki/affnet,84,2019-01-02 -Shape Completion Using 3D-Encoder-Predictor CNNs and Shape Synthesis,http://openaccess.thecvf.com/content_cvpr_2017/html/Dai_Shape_Completion_Using_CVPR_2017_paper.html,CVPR,2017,https://github.com/angeladai/cnncomplete,73,2019-01-02 -Avatar-Net: Multi-Scale Zero-Shot Style Transfer by Feature Decoration,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sheng_Avatar-Net_Multi-Scale_Zero-Shot_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/LucasSheng/avatar-net,71,2019-01-02 -Feedback Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zamir_Feedback_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/amir32002/feedback-networks,72,2019-01-02 -Video Propagation Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Jampani_Video_Propagation_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/varunjampani/video_prop_networks,70,2019-01-02 -Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs,http://openaccess.thecvf.com/content_cvpr_2016/html/Ge_Robust_3D_Hand_CVPR_2016_paper.html,CVPR,2016,https://github.com/geliuhao/CVPR2016_HandPoseEstimation,70,2019-01-02 -Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Yikang_LI_Factorizable_Net_An_ECCV_2018_paper.html,ECCV,2018,https://github.com/yikang-li/FactorizableNet,78,2019-01-02 -Saliency Detection by Multi-Context Deep Learning,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhao_Saliency_Detection_by_2015_CVPR_paper.html,CVPR,2015,https://github.com/Robert0812/deepsaldet,66,2019-01-02 -Self-Supervised Learning of Visual Features Through Embedding Images Into Text Topic Spaces,http://openaccess.thecvf.com/content_cvpr_2017/html/Gomez_Self-Supervised_Learning_of_CVPR_2017_paper.html,CVPR,2017,https://github.com/lluisgomez/TextTopicNet,69,2019-01-02 -SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_SGPN_Similarity_Group_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/laughtervv/SGPN,84,2019-01-02 -Action-Decision Networks for Visual Tracking With Deep Reinforcement Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Yun_Action-Decision_Networks_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/hellbell/ADNet,71,2019-01-02 -Learning SO(3) Equivariant Representations with Spherical CNNs,http://openaccess.thecvf.com/content_ECCV_2018/html/Carlos_Esteves_Learning_SO3_Equivariant_ECCV_2018_paper.html,ECCV,2018,https://github.com/daniilidis-group/spherical-cnn,89,2019-01-02 -ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans,http://openaccess.thecvf.com/content_cvpr_2018/papers/Dai_ScanComplete_Large-Scale_Scene_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/angeladai/ScanComplete,97,2019-01-02 -Towards Open Set Deep Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Bendale_Towards_Open_Set_CVPR_2016_paper.html,CVPR,2016,https://github.com/abhijitbendale/OSDN,71,2019-01-02 -Deep Neural Networks Are Easily Fooled: High Confidence Predictions for Unrecognizable Images,http://openaccess.thecvf.com/content_cvpr_2015/html/Nguyen_Deep_Neural_Networks_2015_CVPR_paper.html,CVPR,2015,https://github.com/abhijitbendale/OSDN,71,2019-01-02 -Marr Revisited: 2D-3D Alignment via Surface Normal Prediction,http://openaccess.thecvf.com/content_cvpr_2016/html/Bansal_Marr_Revisited_2D-3D_CVPR_2016_paper.html,CVPR,2016,https://github.com/aayushbansal/MarrRevisited,72,2019-01-02 -Optical Flow Estimation Using a Spatial Pyramid Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Ranjan_Optical_Flow_Estimation_CVPR_2017_paper.html,CVPR,2017,https://github.com/sniklaus/pytorch-spynet,90,2019-01-02 -SurfaceNet: An End-To-End 3D Neural Network for Multiview Stereopsis,http://openaccess.thecvf.com/content_iccv_2017/html/Ji_SurfaceNet_An_End-To-End_ICCV_2017_paper.html,ICCV,2017,https://github.com/mjiUST/SurfaceNet,66,2019-01-02 -TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals,http://openaccess.thecvf.com/content_iccv_2017/html/Gao_TURN_TAP_Temporal_ICCV_2017_paper.html,ICCV,2017,https://github.com/jiyanggao/TURN-TAP,66,2019-01-02 -Raster-To-Vector: Revisiting Floorplan Transformation,http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Raster-To-Vector_Revisiting_Floorplan_ICCV_2017_paper.html,ICCV,2017,https://github.com/art-programmer/FloorplanTransformation,76,2019-01-02 -Multi-Shot Pedestrian Re-Identification via Sequential Decision Making,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Multi-Shot_Pedestrian_Re-Identification_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/TuSimple/rl-multishot-reid,70,2019-01-02 -One-Shot Unsupervised Cross Domain Translation,http://arxiv.org/abs/1806.06029v1,NIPS,2018,https://github.com/sagiebenaim/OneShotTranslation,89,2019-01-02 -Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade,http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Not_All_Pixels_CVPR_2017_paper.html,CVPR,2017,https://github.com/liuziwei7/region-conv,73,2019-01-02 -Pairwise Confusion for Fine-Grained Visual Classification,http://openaccess.thecvf.com/content_ECCV_2018/html/Abhimanyu_Dubey_Improving_Fine-Grained_Visual_ECCV_2018_paper.html,ECCV,2018,https://github.com/abhimanyudubey/confusion,77,2019-01-02 -Borrowing Treasures From the Wealthy: Deep Transfer Learning Through Selective Joint Fine-Tuning,http://openaccess.thecvf.com/content_cvpr_2017/html/Ge_Borrowing_Treasures_From_CVPR_2017_paper.html,CVPR,2017,https://github.com/ZYYSzj/Selective-Joint-Fine-tuning,64,2019-01-02 -Generalizing A Person Retrieval Model Hetero- and Homogeneously,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhun_Zhong_Generalizing_A_Person_ECCV_2018_paper.html,ECCV,2018,https://github.com/zhunzhong07/HHL,78,2019-01-02 -Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-Identification,http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Jointly_Attentive_Spatial-Temporal_ICCV_2017_paper.html,ICCV,2017,https://github.com/shuangjiexu/Spatial-Temporal-Pooling-Networks-ReID,65,2019-01-02 -Learning Depth From Monocular Videos Using Direct Methods,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_Depth_From_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MightyChaos/LKVOLearner,97,2019-01-02 -Training Deep Networks without Learning Rates Through Coin Betting,http://papers.nips.cc/paper/6811-training-deep-networks-without-learning-rates-through-coin-betting.pdf,NIPS,2017,https://github.com/bremen79/cocob,66,2019-01-02 -Optimizing the Latent Space of Generative Networks,http://proceedings.mlr.press/v80/bojanowski18a.html,ICML,2018,https://github.com/tneumann/minimal_glo,66,2019-01-02 -Playing for Benchmarks,http://openaccess.thecvf.com/content_iccv_2017/html/Richter_Playing_for_Benchmarks_ICCV_2017_paper.html,ICCV,2017,https://github.com/PatrykChrabaszcz/Canonical_ES_Atari,61,2019-01-02 -Bilateral Space Video Segmentation,http://openaccess.thecvf.com/content_cvpr_2016/html/Maerki_Bilateral_Space_Video_CVPR_2016_paper.html,CVPR,2016,https://github.com/owang/BilateralVideoSegmentation,63,2019-01-02 -ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching,http://papers.nips.cc/paper/7133-alice-towards-understanding-adversarial-learning-for-joint-distribution-matching.pdf,NIPS,2017,https://github.com/ChunyuanLI/ALICE,63,2019-01-02 -Full Resolution Image Compression With Recurrent Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Toderici_Full_Resolution_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/1zb/pytorch-image-comp-rnn,66,2019-01-02 -CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_CSRNet_Dilated_Convolutional_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/leeyeehoo/CSRNet-pytorch,87,2019-01-02 -"Deep Learning Face Representation from Predicting 10,000 Classes",http://openaccess.thecvf.com/content_cvpr_2014/html/Sun_Deep_Learning_Face_2014_CVPR_paper.html,CVPR,2014,https://github.com/joyhuang9473/deepid-implementation,62,2019-01-02 -Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_Attentions_Residual_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/foolwood/RASNet,67,2019-01-02 -“Zero-Shot” Super-Resolution Using Deep Internal Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shocher_Zero-Shot_Super-Resolution_Using_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/assafshocher/ZSSR,84,2019-01-02 -Generative Neural Machine Translation,http://arxiv.org/abs/1806.05138v1,NIPS,2018,https://github.com/ZhenYangIACAS/NMT_GAN,68,2019-01-02 -Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Physically-Based_Rendering_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/yindaz/pbrs,67,2019-01-02 -AdaGAN: Boosting Generative Models,http://papers.nips.cc/paper/7126-adagan-boosting-generative-models.pdf,NIPS,2017,https://github.com/tolstikhin/adagan,59,2019-01-02 -Progressive Neural Architecture Search,http://openaccess.thecvf.com/content_ECCV_2018/html/Chenxi_Liu_Progressive_Neural_Architecture_ECCV_2018_paper.html,ECCV,2018,https://github.com/titu1994/progressive-neural-architecture-search,68,2019-01-02 -Quality Aware Network for Set to Set Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Quality_Aware_Network_CVPR_2017_paper.html,CVPR,2017,https://github.com/sciencefans/Quality-Aware-Network,69,2019-01-02 -PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Uy_PointNetVLAD_Deep_Point_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mikacuy/pointnetvlad,69,2019-01-02 -Deep Filter Banks for Texture Recognition and Segmentation,http://openaccess.thecvf.com/content_cvpr_2015/html/Cimpoi_Deep_Filter_Banks_2015_CVPR_paper.html,CVPR,2015,https://github.com/mcimpoi/deep-fbanks,68,2019-01-02 -Person Re-Identification in the Wild,http://openaccess.thecvf.com/content_cvpr_2017/html/Zheng_Person_Re-Identification_in_CVPR_2017_paper.html,CVPR,2017,https://github.com/liangzheng06/PRW-baseline,63,2019-01-02 -Doubly Stochastic Variational Inference for Deep Gaussian Processes,http://papers.nips.cc/paper/7045-doubly-stochastic-variational-inference-for-deep-gaussian-processes.pdf,NIPS,2017,https://github.com/ICL-SML/Doubly-Stochastic-DGP,66,2019-01-02 -Toward Controlled Generation of Text,http://proceedings.mlr.press/v70/hu17e.html,ICML,2017,https://github.com/GBLin5566/toward-controlled-generation-of-text-pytorch,63,2019-01-02 -Learning to Reweight Examples for Robust Deep Learning,http://proceedings.mlr.press/v80/ren18a.html,ICML,2018,https://github.com/danieltan07/learning-to-reweight-examples,76,2019-01-02 -Dance Dance Convolution,http://proceedings.mlr.press/v70/donahue17a.html,ICML,2017,https://github.com/chrisdonahue/ddc,65,2019-01-02 -Generate to Adapt: Aligning Domains Using Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Generate_to_Adapt_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yogeshbalaji/Generate_To_Adapt,67,2019-01-02 -Image-To-Image Translation With Conditional Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/williamFalcon/pix2pix-keras,70,2019-01-02 -Decorrelated Batch Normalization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Decorrelated_Batch_Normalization_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/umich-vl/DecorrelatedBN,57,2019-01-02 -Xception: Deep Learning With Depthwise Separable Convolutions,http://openaccess.thecvf.com/content_cvpr_2017/html/Chollet_Xception_Deep_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/tstandley/Xception-PyTorch,71,2019-01-02 -Geometry-Aware Learning of Maps for Camera Localization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Brahmbhatt_Geometry-Aware_Learning_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/samarth-robo/MapNet,63,2019-01-02 -Improving Generalization via Scalable Neighborhood Component Analysis,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhirong_Wu_Improving_Embedding_Generalization_ECCV_2018_paper.html,ECCV,2018,https://github.com/Microsoft/snca.pytorch,76,2019-01-02 -Convolutional Gaussian Processes,http://papers.nips.cc/paper/6877-convolutional-gaussian-processes.pdf,NIPS,2017,https://github.com/markvdw/convgp/,57,2018-09-16 -Path-Level Network Transformation for Efficient Architecture Search,http://proceedings.mlr.press/v80/cai18a.html,ICML,2018,https://github.com/han-cai/PathLevel-EAS,73,2019-01-02 -Ordinal Depth Supervision for 3D Human Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Pavlakos_Ordinal_Depth_Supervision_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/geopavlakos/ordinal-pose3d,74,2019-01-02 -Escape From Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models,http://openaccess.thecvf.com/content_iccv_2017/html/Klokov_Escape_From_Cells_ICCV_2017_paper.html,ICCV,2017,https://github.com/fxia22/kdnet.pytorch,68,2019-01-02 -Object Level Visual Reasoning in Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Fabien_Baradel_Object_Level_Visual_ECCV_2018_paper.html,ECCV,2018,https://github.com/fabienbaradel/object_level_visual_reasoning,71,2019-01-02 -Regularizing RNNs for Caption Generation by Reconstructing the Past With the Present,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Regularizing_RNNs_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chenxinpeng/ARNet,70,2019-01-02 -Disentangled Person Image Generation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ma_Disentangled_Person_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/charliememory/Disentangled-Person-Image-Generation,75,2019-01-02 -Diverse Image-to-Image Translation via Disentangled Representations,http://openaccess.thecvf.com/content_ECCV_2018/html/Hsin-Ying_Lee_Diverse_Image-to-Image_Translation_ECCV_2018_paper.html,ECCV,2018,https://github.com/taki0112/DRIT-Tensorflow,72,2019-01-02 -A Distributional Perspective on Reinforcement Learning,http://proceedings.mlr.press/v70/bellemare17a.html,ICML,2017,https://github.com/Silvicek/distributional-dqn,68,2019-01-02 -Neural Program Synthesis from Diverse Demonstration Videos,http://proceedings.mlr.press/v80/sun18a.html,ICML,2018,https://github.com/shaohua0116/demo2program,62,2019-01-02 -Pointwise Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hua_Pointwise_Convolutional_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/scenenn/pointwise,67,2019-01-02 -Modeling Relationships in Referential Expressions With Compositional Modular Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Modeling_Relationships_in_CVPR_2017_paper.html,CVPR,2017,https://github.com/ronghanghu/cmn,57,2019-01-02 -Deep Subspace Clustering Networks,http://papers.nips.cc/paper/6608-deep-subspace-clustering-networks.pdf,NIPS,2017,https://github.com/panji1990/Deep-subspace-clustering-networks,68,2019-01-02 -Multi-Channel Weighted Nuclear Norm Minimization for Real Color Image Denoising,http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Multi-Channel_Weighted_Nuclear_ICCV_2017_paper.html,ICCV,2017,https://github.com/csjunxu/MCWNNM-ICCV2017,61,2019-01-02 -Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency,http://openaccess.thecvf.com/content_ECCV_2018/html/Xingyi_Zhou_Unsupervised_Domain_Adaptation_ECCV_2018_paper.html,ECCV,2018,https://github.com/xingyizhou/3DKeypoints-DA,60,2019-01-02 -Learning Less Is More - 6D Camera Localization via 3D Surface Regression,http://openaccess.thecvf.com/content_cvpr_2018/papers/Brachmann_Learning_Less_Is_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/vislearn/LessMore,72,2019-01-02 -End-To-End 3D Face Reconstruction With Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Dou_End-To-End_3D_Face_CVPR_2017_paper.html,CVPR,2017,https://github.com/ShownX/mxnet-E2FAR,60,2019-01-02 -Learning Latent Super-Events to Detect Multiple Activities in Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Piergiovanni_Learning_Latent_Super-Events_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/piergiaj/super-events-cvpr18,67,2019-01-02 -Factorized Bilinear Models for Image Recognition,http://openaccess.thecvf.com/content_iccv_2017/html/Li_Factorized_Bilinear_Models_ICCV_2017_paper.html,ICCV,2017,https://github.com/lyttonhao/Factorized-Bilinear-Network,55,2019-01-02 -Depth-aware CNN for RGB-D Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Weiyue_Wang_Depth-aware_CNN_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/laughtervv/DepthAwareCNN,88,2019-01-02 -Online and Linear-Time Attention by Enforcing Monotonic Alignments,http://proceedings.mlr.press/v70/raffel17a.html,ICML,2017,https://github.com/craffel/mad,56,2019-01-02 -Unsupervised Discovery of Object Landmarks as Structural Representations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Unsupervised_Discovery_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/YutingZhang/lmdis-rep,61,2019-01-02 -Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Crafting_a_Toolchain_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yuke93/RL-Restore,77,2019-01-02 -SparseMAP: Differentiable Sparse Structured Inference,http://proceedings.mlr.press/v80/niculae18a.html,ICML,2018,https://github.com/vene/sparsemap,75,2019-01-02 -Adversarial Feature Augmentation for Unsupervised Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Volpi_Adversarial_Feature_Augmentation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ricvolpi/adversarial-feature-augmentation,67,2019-01-02 -Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Self-Supervised_Adversarial_Hashing_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lelan-li/SSAH,72,2019-01-02 -Unsupervised Learning by Predicting Noise,http://proceedings.mlr.press/v70/bojanowski17a.html,ICML,2017,https://github.com/facebookresearch/noise-as-targets,60,2019-01-02 -Fast and Accurate Single Image Super-Resolution via Information Distillation Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hui_Fast_and_Accurate_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Zheng222/IDN-Caffe,71,2019-01-02 -CoupleNet: Coupling Global Structure With Local Parts for Object Detection,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_CoupleNet_Coupling_Global_ICCV_2017_paper.html,ICCV,2017,https://github.com/tshizys/CoupleNet,59,2019-01-02 -A Deep Regression Architecture With Two-Stage Re-Initialization for High Performance Facial Landmark Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Lv_A_Deep_Regression_CVPR_2017_paper.html,CVPR,2017,https://github.com/shaoxiaohu/Face_Alignment_Two_Stage_Re-initialization,57,2019-01-02 -On-the-fly Operation Batching in Dynamic Computation Graphs,http://papers.nips.cc/paper/6986-on-the-fly-operation-batching-in-dynamic-computation-graphs.pdf,NIPS,2017,https://github.com/neulab/dynet-benchmark,54,2019-01-02 -Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes With Deep Generative Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Soltani_Synthesizing_3D_Shapes_CVPR_2017_paper.html,CVPR,2017,https://github.com/Amir-Arsalan/Synthesize3DviaDepthOrSil,65,2019-01-02 -Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Curriculum_Domain_Adaptation_ICCV_2017_paper.html,ICCV,2017,https://github.com/YangZhang4065/AdaptationSeg,64,2019-01-02 -Deep Compositional Captioning: Describing Novel Object Categories Without Paired Training Data,http://openaccess.thecvf.com/content_cvpr_2016/html/Hendricks_Deep_Compositional_Captioning_CVPR_2016_paper.html,CVPR,2016,https://github.com/LisaAnne/DCC,57,2019-01-02 -Neural Style Transfer via Meta Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Neural_Style_Transfer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/FalongShen/styletransfer,59,2019-01-02 -Deep Marching Cubes: Learning Explicit Surface Representations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liao_Deep_Marching_Cubes_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yiyiliao/deep_marching_cubes,56,2019-01-02 -Shift-Net: Image Inpainting via Deep Feature Rearrangement,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhaoyi_Yan_Shift-Net_Image_Inpainting_ECCV_2018_paper.html,ECCV,2018,https://github.com/Zhaoyi-Yan/Shift-Net_pytorch,74,2019-01-02 -Dense-Captioning Events in Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Krishna_Dense-Captioning_Events_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/ranjaykrishna/densevid_eval,55,2019-01-02 -Cascade R-CNN: Delving Into High Quality Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cai_Cascade_R-CNN_Delving_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/guoruoqian/cascade-rcnn_Pytorch,93,2019-01-02 -Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee,http://papers.nips.cc/paper/6910-net-trim-convex-pruning-of-deep-neural-networks-with-performance-guarantee.pdf,NIPS,2017,https://github.com/DNNToolBox/Net-Trim-v1,54,2019-01-02 -Leveraging Unlabeled Data for Crowd Counting by Learning to Rank,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Leveraging_Unlabeled_Data_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xialeiliu/CrowdCountingCVPR18,56,2019-01-02 -Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Learning_From_Synthetic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/swamiviv/LSD-seg,56,2019-01-02 -Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Weakly-Supervised_Semantic_Segmentation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/speedinghzl/DSRG,71,2019-01-02 -SST: Single-Stream Temporal Action Proposals,http://openaccess.thecvf.com/content_cvpr_2017/html/Buch_SST_Single-Stream_Temporal_CVPR_2017_paper.html,CVPR,2017,https://github.com/ranjaykrishna/SST,51,2019-01-02 -Fighting Fake News: Image Splice Detection via Learned Self-Consistency,http://openaccess.thecvf.com/content_ECCV_2018/html/Jacob_Huh_Fighting_Fake_News_ECCV_2018_paper.html,ECCV,2018,https://github.com/minyoungg/selfconsistency,62,2019-01-02 -Curiosity-driven Exploration by Self-supervised Prediction,http://proceedings.mlr.press/v70/pathak17a.html,ICML,2017,https://github.com/kimhc6028/pytorch-noreward-rl,56,2019-01-02 -Deep IV: A Flexible Approach for Counterfactual Prediction,http://proceedings.mlr.press/v70/hartford17a.html,ICML,2017,https://github.com/jhartford/DeepIV,52,2019-01-02 -Hierarchical Long-term Video Prediction without Supervision,http://proceedings.mlr.press/v80/wichers18a.html,ICML,2018,https://github.com/brain-research/long-term-video-prediction-without-supervision,60,2019-01-02 -PDE-Net: Learning PDEs from Data,http://proceedings.mlr.press/v80/long18a.html,ICML,2018,https://github.com/ZichaoLong/PDE-Net,75,2019-01-02 -Efficient 3D Room Shape Recovery From a Single Panorama,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Efficient_3D_Room_CVPR_2016_paper.html,CVPR,2016,https://github.com/YANG-H/Panoramix,55,2019-01-02 -Learning Discrete Representations via Information Maximizing Self-Augmented Training,http://proceedings.mlr.press/v70/hu17b.html,ICML,2017,https://github.com/weihua916/imsat,49,2019-01-02 -Video Segmentation via Object Flow,http://openaccess.thecvf.com/content_cvpr_2016/html/Tsai_Video_Segmentation_via_CVPR_2016_paper.html,CVPR,2016,https://github.com/wasidennis/ObjectFlow,50,2019-01-02 -Person Search With Natural Language Description,http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Person_Search_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/ShuangLI59/Person-Search-with-Natural-Language-Description,61,2019-01-02 -Discriminability Objective for Training Descriptive Captions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_Discriminability_Objective_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ruotianluo/DiscCaptioning,54,2019-01-02 -Triangle Generative Adversarial Networks,http://papers.nips.cc/paper/7109-triangle-generative-adversarial-networks.pdf,NIPS,2017,https://github.com/LiqunChen0606/Triangle-GAN,51,2019-01-02 -The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process,http://papers.nips.cc/paper/7252-the-neural-hawkes-process-a-neurally-self-modulating-multivariate-point-process.pdf,NIPS,2017,https://github.com/HMEIatJHU/neurawkes,56,2019-01-02 -Finding Action Tubes,http://openaccess.thecvf.com/content_cvpr_2015/html/Gkioxari_Finding_Action_Tubes_2015_CVPR_paper.html,CVPR,2015,https://github.com/gkioxari/ActionTubes,51,2019-01-02 -Differentiable Learning of Logical Rules for Knowledge Base Reasoning,http://papers.nips.cc/paper/6826-differentiable-learning-of-logical-rules-for-knowledge-base-reasoning.pdf,NIPS,2017,https://github.com/fanyangxyz/Neural-LP,62,2019-01-02 -L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space,http://openaccess.thecvf.com/content_cvpr_2017/html/Tian_L2-Net_Deep_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/yuruntian/L2-Net,51,2019-01-02 -Visual Question Generation as Dual Task of Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Visual_Question_Generation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yikang-li/iQAN,50,2019-01-02 -DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency,http://openaccess.thecvf.com/content_ECCV_2018/html/Yuliang_Zou_DF-Net_Unsupervised_Joint_ECCV_2018_paper.html,ECCV,2018,https://github.com/vt-vl-lab/DF-Net,82,2019-01-02 -BlockDrop: Dynamic Inference Paths in Residual Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_BlockDrop_Dynamic_Inference_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Tushar-N/blockdrop,54,2019-01-02 -Efficient end-to-end learning for quantizable representations,http://proceedings.mlr.press/v80/jeong18a.html,ICML,2018,https://github.com/maestrojeong/Deep-Hash-Table-ICML18,50,2019-01-02 -Predicting Deeper Into the Future of Semantic Segmentation,http://openaccess.thecvf.com/content_iccv_2017/html/Luc_Predicting_Deeper_Into_ICCV_2017_paper.html,ICCV,2017,https://github.com/facebookresearch/SegmPred,51,2019-01-02 -Towards Diverse and Natural Image Descriptions via a Conditional GAN,http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Towards_Diverse_and_ICCV_2017_paper.html,ICCV,2017,https://github.com/doubledaibo/gancaption_iccv2017,53,2019-01-02 -CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Shou_CDC_Convolutional-De-Convolutional_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/ColumbiaDVMM/CDC,53,2019-01-02 -Category-Specific Object Reconstruction From a Single Image,http://openaccess.thecvf.com/content_cvpr_2015/html/Kar_Category-Specific_Object_Reconstruction_2015_CVPR_paper.html,CVPR,2015,https://github.com/akar43/CategoryShapes,48,2019-01-02 -Learning to Find Good Correspondences,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yi_Learning_to_Find_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/vcg-uvic/learned-correspondence-release,72,2019-01-02 -Neural Expectation Maximization,http://papers.nips.cc/paper/7246-neural-expectation-maximization.pdf,NIPS,2017,https://github.com/sjoerdvansteenkiste/Neural-EM,56,2019-01-02 -Semantic Video CNNs Through Representation Warping,http://openaccess.thecvf.com/content_iccv_2017/html/Gadde_Semantic_Video_CNNs_ICCV_2017_paper.html,ICCV,2017,https://github.com/raghudeep/netwarp_public,46,2019-01-02 -EAST: An Efficient and Accurate Scene Text Detector,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_EAST_An_Efficient_CVPR_2017_paper.html,CVPR,2017,https://github.com/Kathrine94/EAST,51,2019-01-02 -Learning Blind Motion Deblurring,http://openaccess.thecvf.com/content_iccv_2017/html/Wieschollek_Learning_Blind_Motion_ICCV_2017_paper.html,ICCV,2017,https://github.com/cgtuebingen/learning-blind-motion-deblurring,54,2019-01-02 -Pose-Normalized Image Generation for Person Re-identification,http://openaccess.thecvf.com/content_ECCV_2018/html/Xuelin_Qian_Pose-Normalized_Image_Generation_ECCV_2018_paper.html,ECCV,2018,https://github.com/naiq/PN_GAN,75,2019-01-02 -Multi-Objective Convolutional Learning for Face Labeling,http://openaccess.thecvf.com/content_cvpr_2015/html/Liu_Multi-Objective_Convolutional_Learning_2015_CVPR_paper.html,CVPR,2015,https://github.com/Liusifei/Face_Parsing_2016,55,2019-01-02 -Wasserstein Introspective Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_Wasserstein_Introspective_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kjunelee/WINN,51,2019-01-02 -Conditional Probability Models for Deep Image Compression,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mentzer_Conditional_Probability_Models_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/fab-jul/imgcomp-cvpr,54,2019-01-02 -Efficient Diffusion on Region Manifolds: Recovering Small Objects With Compact CNN Representations,http://openaccess.thecvf.com/content_cvpr_2017/html/Iscen_Efficient_Diffusion_on_CVPR_2017_paper.html,CVPR,2017,https://github.com/ahmetius/diffusion-retrieval,48,2019-01-02 -Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Peng_Jointly_Optimize_Data_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhiqiangdon/pose-adv-aug,54,2019-01-02 -PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction,http://openaccess.thecvf.com/content_ECCV_2018/html/Yifei_Shi_PlaneMatch_Patch_Coplanarity_ECCV_2018_paper.html,ECCV,2018,https://github.com/yifeishi/PlaneMatch,57,2019-01-02 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Autoencoder,http://proceedings.mlr.press/v70/kusner17a.html,ICML,2017,https://github.com/episodeyang/grammar_variational_autoencoder,46,2019-01-02 -Measuring abstract reasoning in neural networks,http://proceedings.mlr.press/v80/santoro18a.html,ICML,2018,https://github.com/deepmind/abstract-reasoning-matrices,51,2019-01-02 -Unsupervised Attention-guided Image-to-Image Translation,https://arxiv.org/abs/1806.02311,NIPS,2018,https://github.com/AlamiMejjati/Unsupervised-Attention-guided-Image-to-Image-Translation,110,2019-01-02 -Visual Translation Embedding Network for Visual Relation Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Visual_Translation_Embedding_CVPR_2017_paper.html,CVPR,2017,https://github.com/zawlin/cvpr17_vtranse,54,2019-01-02 -Learning towards Minimum Hyperspherical Energy,http://arxiv.org/abs/1805.09298v4,NIPS,2018,https://github.com/wy1iu/MHE,54,2019-01-02 -Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network,http://papers.nips.cc/paper/6854-predicting-organic-reaction-outcomes-with-weisfeiler-lehman-network.pdf,NIPS,2017,https://github.com/wengong-jin/nips17-rexgen,46,2019-01-02 -Structured Bayesian Pruning via Log-Normal Multiplicative Noise,http://papers.nips.cc/paper/7254-structured-bayesian-pruning-via-log-normal-multiplicative-noise.pdf,NIPS,2017,https://github.com/necludov/group-sparsity-sbp,44,2019-01-02 -Modulating early visual processing by language,http://papers.nips.cc/paper/7237-modulating-early-visual-processing-by-language.pdf,NIPS,2017,https://github.com/GuessWhatGame/guesswhat,49,2019-01-02 -Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam,http://proceedings.mlr.press/v80/khan18a.html,ICML,2018,https://github.com/emtiyaz/vadam,49,2019-01-02 -A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning,http://papers.nips.cc/paper/6951-a-disentangled-recognition-and-nonlinear-dynamics-model-for-unsupervised-learning.pdf,NIPS,2017,https://github.com/simonkamronn/kvae,53,2019-01-02 -Learning Pose Specific Representations by Predicting Different Views,http://openaccess.thecvf.com/content_cvpr_2018/papers/Poier_Learning_Pose_Specific_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/poier/PreView,44,2019-01-02 -Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhaoyang_Lv_Learning_Rigidity_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/NVlabs/learningrigidity,61,2019-01-02 -Adversarial Examples for Semantic Segmentation and Object Detection,http://openaccess.thecvf.com/content_iccv_2017/html/Xie_Adversarial_Examples_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/cihangxie/DAG,49,2019-01-02 -BING: Binarized Normed Gradients for Objectness Estimation at 300fps,http://openaccess.thecvf.com/content_cvpr_2014/html/Cheng_BING_Binarized_Normed_2014_CVPR_paper.html,CVPR,2014,https://github.com/alessandroferrari/BING-Objectness,44,2019-01-02 -Video Pixel Networks,http://proceedings.mlr.press/v70/kalchbrenner17a.html,ICML,2017,https://github.com/3ammor/Video-Pixel-Networks,45,2019-01-02 -Learning Residual Images for Face Attribute Manipulation,http://openaccess.thecvf.com/content_cvpr_2017/html/Shen_Learning_Residual_Images_CVPR_2017_paper.html,CVPR,2017,https://github.com/Zhongdao/FaceAttributeManipulation,43,2019-01-02 -Differentiable Compositional Kernel Learning for Gaussian Processes,http://proceedings.mlr.press/v80/sun18e.html,ICML,2018,https://github.com/ssydasheng/Neural-Kernel-Network,45,2019-01-02 -Learned D-AMP: Principled Neural Network based Compressive Image Recovery,http://papers.nips.cc/paper/6774-learned-d-amp-principled-neural-network-based-compressive-image-recovery.pdf,NIPS,2017,https://github.com/ricedsp/D-AMP_Toolbox,47,2019-01-02 -Accurate Optical Flow via Direct Cost Volume Processing,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Accurate_Optical_Flow_CVPR_2017_paper.html,CVPR,2017,https://github.com/IntelVCL/dcflow,42,2019-01-02 -Learning From Massive Noisy Labeled Data for Image Classification,http://openaccess.thecvf.com/content_cvpr_2015/html/Xiao_Learning_From_Massive_2015_CVPR_paper.html,CVPR,2015,https://github.com/Cysu/noisy_label,45,2019-01-02 -Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition,http://openaccess.thecvf.com/content_ECCV_2018/html/Chaojian_Yu_Hierarchical_Bilinear_Pooling_ECCV_2018_paper.html,ECCV,2018,https://github.com/ChaojianYu/Hierarchical-Bilinear-Pooling,57,2019-01-02 -CRAFT Objects From Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_CRAFT_Objects_From_CVPR_2016_paper.html,CVPR,2016,https://github.com/byangderek/CRAFT,41,2019-01-02 -Semantic Compositional Networks for Visual Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Gan_Semantic_Compositional_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/zhegan27/Semantic_Compositional_Nets,45,2019-01-02 -Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Exploit_the_Unknown_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Yu-Wu/Exploit-Unknown-Gradually,59,2019-01-02 -Real-World Anomaly Detection in Surveillance Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sultani_Real-World_Anomaly_Detection_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/WaqasSultani/AnomalyDetectionCVPR2018,72,2019-01-02 -Deriving Neural Architectures from Sequence and Graph Kernels,http://proceedings.mlr.press/v70/lei17a.html,ICML,2017,https://github.com/taolei87/icml17_knn,44,2019-01-02 -DeepVS: A Deep Learning Based Video Saliency Prediction Approach,http://openaccess.thecvf.com/content_ECCV_2018/html/Lai_Jiang_DeepVS_A_Deep_ECCV_2018_paper.html,ECCV,2018,https://github.com/remega/OMCNN_2CLSTM,53,2019-01-02 -Slicing Convolutional Neural Network for Crowd Video Understanding,http://openaccess.thecvf.com/content_cvpr_2016/html/Shao_Slicing_Convolutional_Neural_CVPR_2016_paper.html,CVPR,2016,https://github.com/amandajshao/Slicing-CNN,40,2019-01-02 -A Linear-Time Kernel Goodness-of-Fit Test,http://papers.nips.cc/paper/6630-a-linear-time-kernel-goodness-of-fit-test.pdf,NIPS,2017,https://github.com/wittawatj/kernel-gof,40,2019-01-02 -Stabilizing Training of Generative Adversarial Networks through Regularization,http://papers.nips.cc/paper/6797-stabilizing-training-of-generative-adversarial-networks-through-regularization.pdf,NIPS,2017,https://github.com/rothk/Stabilizing_GANs,45,2019-01-02 -RayNet: Learning Volumetric 3D Reconstruction With Ray Potentials,http://openaccess.thecvf.com/content_cvpr_2018/papers/Paschalidou_RayNet_Learning_Volumetric_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/paschalidoud/raynet,51,2019-01-02 -Rotation-Sensitive Regression for Oriented Scene Text Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liao_Rotation-Sensitive_Regression_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MhLiao/RRD,61,2019-01-02 -Learning Intrinsic Image Decomposition From Watching the World,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Intrinsic_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lixx2938/unsupervised-learning-intrinsic-images,45,2019-01-02 -Learning Efficient Single-stage Pedestrian Detectors by Asymptotic Localization Fitting,http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html,ECCV,2018,https://github.com/liuwei16/ALFNet,52,2019-01-02 -Neural Scene De-Rendering,http://openaccess.thecvf.com/content_cvpr_2017/html/Wu_Neural_Scene_De-Rendering_CVPR_2017_paper.html,CVPR,2017,https://github.com/jiajunwu/nsd,40,2019-01-02 -P-CNN: Pose-Based CNN Features for Action Recognition,http://openaccess.thecvf.com/content_iccv_2015/html/Cheron_P-CNN_Pose-Based_CNN_ICCV_2015_paper.html,ICCV,2015,https://github.com/gcheron/P-CNN,45,2019-01-02 -Video Re-localization,http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_Feng_Video_Re-localization_via_ECCV_2018_paper.html,ECCV,2018,https://github.com/fengyang0317/video_reloc,46,2019-01-02 -Image Manipulation with Perceptual Discriminators,http://openaccess.thecvf.com/content_ECCV_2018/html/Diana_Sungatullina_Image_Manipulation_with_ECCV_2018_paper.html,ECCV,2018,https://github.com/egorzakharov/PerceptualGAN,45,2019-01-02 -Unsupervised Adaptation for Deep Stereo,http://openaccess.thecvf.com/content_iccv_2017/html/Tonioni_Unsupervised_Adaptation_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/CVLAB-Unibo/Unsupervised-Adaptation-for-Deep-Stereo,44,2019-01-02 -Generalized Orderless Pooling Performs Implicit Salient Matching,http://openaccess.thecvf.com/content_iccv_2017/html/Simon_Generalized_Orderless_Pooling_ICCV_2017_paper.html,ICCV,2017,https://github.com/cvjena/alpha_pooling,42,2019-01-02 -Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,http://openaccess.thecvf.com/content_ECCV_2018/html/Baris_Gecer_Semi-supervised_Adversarial_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/barisgecer/facegan,55,2019-01-02 -Comparative Evaluation of Hand-Crafted and Learned Local Features,http://openaccess.thecvf.com/content_cvpr_2017/html/Schonberger_Comparative_Evaluation_of_CVPR_2017_paper.html,CVPR,2017,https://github.com/ahojnnes/local-feature-evaluation,42,2019-01-02 -Deep Region and Multi-Label Learning for Facial Action Unit Detection,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhao_Deep_Region_and_CVPR_2016_paper.html,CVPR,2016,https://github.com/zkl20061823/DRML,43,2019-01-02 -On-Demand Learning for Deep Image Restoration,http://openaccess.thecvf.com/content_iccv_2017/html/Gao_On-Demand_Learning_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/rhgao/on-demand-learning,45,2019-01-02 -Wavelet-SRNet: A Wavelet-Based CNN for Multi-Scale Face Super Resolution,http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Wavelet-SRNet_A_Wavelet-Based_ICCV_2017_paper.html,ICCV,2017,https://github.com/hhb072/WaveletSRNet,56,2019-01-02 -Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Hyojin_Bahng_Coloring_with_Words_ECCV_2018_paper.html,ECCV,2018,https://github.com/awesome-davian/Text2Colors,50,2019-01-02 -SchNet: A continuous-filter convolutional neural network for modeling quantum interactions,http://papers.nips.cc/paper/6700-schnet-a-continuous-filter-convolutional-neural-network-for-modeling-quantum-interactions.pdf,NIPS,2017,https://github.com/atomistic-machine-learning/SchNet,41,2019-01-02 -Diversified Texture Synthesis With Feed-Forward Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Diversified_Texture_Synthesis_CVPR_2017_paper.html,CVPR,2017,https://github.com/Yijunmaverick/MultiTextureSynthesis,39,2019-01-02 -Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions,http://proceedings.mlr.press/v80/wu18h.html,ICML,2018,https://github.com/Sandbox3aster/Deep-K-Means-pytorch,48,2019-01-02 -Superpixel Sampling Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Varun_Jampani_Superpixel_Sampling_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/NVlabs/ssn_superpixels,74,2019-01-02 -Multiple People Tracking by Lifted Multicut and Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2017/html/Tang_Multiple_People_Tracking_CVPR_2017_paper.html,CVPR,2017,https://github.com/jutanke/cabbage,47,2019-01-02 -TALL: Temporal Activity Localization via Language Query,http://openaccess.thecvf.com/content_iccv_2017/html/Gao_TALL_Temporal_Activity_ICCV_2017_paper.html,ICCV,2017,https://github.com/jiyanggao/TALL,50,2019-01-02 -Learning Pixel-Level Semantic Affinity With Image-Level Supervision for Weakly Supervised Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ahn_Learning_Pixel-Level_Semantic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiwoon-ahn/psa,52,2019-01-02 -Least Squares Generative Adversarial Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Mao_Least_Squares_Generative_ICCV_2017_paper.html,ICCV,2017,https://github.com/GunhoChoi/LSGAN-TF,39,2019-01-02 -Masked Autoregressive Flow for Density Estimation,http://papers.nips.cc/paper/6828-masked-autoregressive-flow-for-density-estimation.pdf,NIPS,2017,https://github.com/gpapamak/maf,44,2019-01-02 -Fast Fourier Color Constancy,http://openaccess.thecvf.com/content_cvpr_2017/html/Barron_Fast_Fourier_Color_CVPR_2017_paper.html,CVPR,2017,https://github.com/google/ffcc,49,2019-01-02 -A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing,http://openaccess.thecvf.com/content_iccv_2017/html/Fan_A_Generic_Deep_ICCV_2017_paper.html,ICCV,2017,https://github.com/fqnchina/CEILNet,52,2019-01-02 -Neural Episodic Control,http://proceedings.mlr.press/v70/pritzel17a.html,ICML,2017,https://github.com/EndingCredits/Neural-Episodic-Control,37,2019-01-02 -Multiplicative Normalizing Flows for Variational Bayesian Neural Networks,http://proceedings.mlr.press/v70/louizos17a.html,ICML,2017,https://github.com/AMLab-Amsterdam/MNF_VBNN,41,2019-01-02 -CBAM: Convolutional Block Attention Module,http://openaccess.thecvf.com/content_ECCV_2018/html/Sanghyun_Woo_Convolutional_Block_Attention_ECCV_2018_paper.html,ECCV,2018,https://github.com/Youngkl0726/Convolutional-Block-Attention-Module,57,2019-01-02 -Self-produced Guidance for Weakly-supervised Object Localization,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaolin_Zhang_Self-produced_Guidance_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/xiaomengyc/SPG,51,2019-01-02 -Deep Spectral Clustering Learning,http://proceedings.mlr.press/v70/law17a.html,ICML,2017,https://github.com/wlwkgus/DeepSpectralClustering,45,2019-01-02 -"Face Normals ""In-The-Wild"" Using Fully Convolutional Networks",http://openaccess.thecvf.com/content_cvpr_2017/html/Trigeorgis_Face_Normals_In-The-Wild_CVPR_2017_paper.html,CVPR,2017,https://github.com/trigeorgis/face_normals_cvpr17,38,2019-01-02 -What's in a Question: Using Visual Questions as a Form of Supervision,http://openaccess.thecvf.com/content_cvpr_2017/html/Ganju_Whats_in_a_CVPR_2017_paper.html,CVPR,2017,https://github.com/sidgan/whats_in_a_question,38,2019-01-02 -Surface Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kostrikov_Surface_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiangzhongshi/SurfaceNetworks,48,2019-01-02 -PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning,http://proceedings.mlr.press/v80/wang18b.html,ICML,2018,https://github.com/Yunbo426/predrnn-pp,42,2019-01-02 -FC4: Fully Convolutional Color Constancy With Confidence-Weighted Pooling,http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_FC4_Fully_Convolutional_CVPR_2017_paper.html,CVPR,2017,https://github.com/yuanming-hu/fc4,47,2019-01-02 -Convolutional Color Constancy,http://openaccess.thecvf.com/content_iccv_2015/html/Barron_Convolutional_Color_Constancy_ICCV_2015_paper.html,ICCV,2015,https://github.com/yuanming-hu/fc4,47,2019-01-02 -Deep Supervised Hashing for Fast Image Retrieval,http://openaccess.thecvf.com/content_cvpr_2016/html/Liu_Deep_Supervised_Hashing_CVPR_2016_paper.html,CVPR,2016,https://github.com/yg33717/DSH_tensorflow,50,2019-01-02 -SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_SketchyGAN_Towards_Diverse_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wchen342/SketchyGAN,51,2019-01-02 -Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples,http://proceedings.mlr.press/v80/weiss18a.html,ICML,2018,https://github.com/tech-srl/lstar_extraction,37,2019-01-02 -Template Matching With Deformable Diversity Similarity,http://openaccess.thecvf.com/content_cvpr_2017/html/Talmi_Template_Matching_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/roimehrez/DDIS,38,2019-01-02 -Temporal Generative Adversarial Nets With Singular Value Clipping,http://openaccess.thecvf.com/content_iccv_2017/html/Saito_Temporal_Generative_Adversarial_ICCV_2017_paper.html,ICCV,2017,https://github.com/pfnet-research/tgan,41,2019-01-02 -Structured Embedding Models for Grouped Data,http://papers.nips.cc/paper/6629-structured-embedding-models-for-grouped-data.pdf,NIPS,2017,https://github.com/mariru/structured_embeddings,36,2019-01-02 -Overcoming Catastrophic Forgetting with Hard Attention to the Task,http://proceedings.mlr.press/v80/serra18a.html,ICML,2018,https://github.com/joansj/hat,44,2019-01-02 -Predicting Matchability,http://openaccess.thecvf.com/content_cvpr_2014/html/Hartmann_Predicting_Matchability_2014_CVPR_paper.html,CVPR,2014,https://github.com/jacekm-git/BetBoy,38,2019-01-02 -3D Reconstruction from Accidental Motion,http://openaccess.thecvf.com/content_cvpr_2014/html/Yu_3D_Reconstruction_from_2014_CVPR_paper.html,CVPR,2014,https://github.com/fyu/tiny,42,2019-01-02 -Neural Autoregressive Flows,http://proceedings.mlr.press/v80/huang18d.html,ICML,2018,https://github.com/CW-Huang/NAF,47,2019-01-02 -Image Specificity,http://openaccess.thecvf.com/content_cvpr_2015/html/Jas_Image_Specificity_2015_CVPR_paper.html,CVPR,2015,https://github.com/burliEnterprises/tensorflow-image-classifier,40,2019-01-02 -Robust Classification With Convolutional Prototype Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Robust_Classification_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/YangHM/Convolutional-Prototype-Learning,43,2019-01-02 -Transfer Joint Matching for Unsupervised Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2014/html/Long_Transfer_Joint_Matching_2014_CVPR_paper.html,CVPR,2014,https://github.com/USTCPCS/CVPR2018_attention,67,2019-01-02 -Deep Transfer Learning with Joint Adaptation Networks,http://proceedings.mlr.press/v70/long17a.html,ICML,2017,https://github.com/USTCPCS/CVPR2018_attention,67,2019-01-02 -Face Flow,http://openaccess.thecvf.com/content_iccv_2015/html/Snape_Face_Flow_ICCV_2015_paper.html,ICCV,2015,https://github.com/shashanktyagi/HyperFace-TensorFlow-implementation,45,2019-01-02 -Sketch Me That Shoe,http://openaccess.thecvf.com/content_cvpr_2016/html/Yu_Sketch_Me_That_CVPR_2016_paper.html,CVPR,2016,https://github.com/seuliufeng/DeepSBIR,39,2019-01-02 -Learning to Generate Long-term Future via Hierarchical Prediction,http://proceedings.mlr.press/v70/villegas17a.html,ICML,2017,https://github.com/rubenvillegas/icml2017hierchvid,43,2019-01-02 -"Predicting Depth, Surface Normals and Semantic Labels With a Common Multi-Scale Convolutional Architecture",http://openaccess.thecvf.com/content_iccv_2015/html/Eigen_Predicting_Depth_Surface_ICCV_2015_paper.html,ICCV,2015,https://github.com/Rostifar/NYUDepthNet,35,2019-01-02 -One Millisecond Face Alignment with an Ensemble of Regression Trees,http://openaccess.thecvf.com/content_cvpr_2014/html/Kazemi_One_Millisecond_Face_2014_CVPR_paper.html,CVPR,2014,https://github.com/jjrCN/ERT-GBDT_Face_Alignment,43,2019-01-02 -Neural Activation Constellations: Unsupervised Part Model Discovery With Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2015/html/Simon_Neural_Activation_Constellations_ICCV_2015_paper.html,ICCV,2015,https://github.com/cvjena/part_constellation_models,35,2019-01-02 -Mid-Level Deep Pattern Mining,http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Mid-Level_Deep_Pattern_2015_CVPR_paper.html,CVPR,2015,https://github.com/yaoliUoA/MDPM,34,2019-01-02 -Partial Adversarial Domain Adaptation,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhangjie_Cao_Partial_Adversarial_Domain_ECCV_2018_paper.html,ECCV,2018,https://github.com/thuml/PADA,43,2019-01-02 -Real Time Image Saliency for Black Box Classifiers,http://papers.nips.cc/paper/7272-real-time-image-saliency-for-black-box-classifiers.pdf,NIPS,2017,https://github.com/PiotrDabkowski/pytorch-saliency,48,2019-01-02 -Pose Partition Networks for Multi-Person Pose Estimation,http://openaccess.thecvf.com/content_ECCV_2018/html/Xuecheng_Nie_Pose_Partition_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/NieXC/pytorch-ppn,47,2019-01-02 -Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation,http://openaccess.thecvf.com/content_ECCV_2018/html/Xuecheng_Nie_Mutual_Learning_to_ECCV_2018_paper.html,ECCV,2018,https://github.com/NieXC/pytorch-mula,43,2019-01-02 -Frame-Recurrent Video Super-Resolution,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sajjadi_Frame-Recurrent_Video_Super-Resolution_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/msmsajjadi/FRVSR,58,2019-01-02 -VQA: Visual Question Answering,http://openaccess.thecvf.com/content_iccv_2015/html/Antol_VQA_Visual_Question_ICCV_2015_paper.html,ICCV,2015,https://github.com/imatge-upc/vqa-2016-cvprw,35,2019-01-02 -Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation,https://arxiv.org/abs/1802.09987,NIPS,2018,https://github.com/EdwardSmith1884/Multi-View-Silhouette-and-Depth-Decomposition-for-High-Resolution-3D-Object-Representation,40,2019-01-02 -Part-Aligned Bilinear Representations for Person Re-Identification,http://openaccess.thecvf.com/content_ECCV_2018/html/Yumin_Suh_Part-Aligned_Bilinear_Representations_ECCV_2018_paper.html,ECCV,2018,https://github.com/yuminsuh/part_bilinear_reid,64,2019-01-02 -Structured Attentions for Visual Question Answering,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Structured_Attentions_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/shtechair/vqa-sva,34,2019-01-02 -Generalisation in humans and deep neural networks,http://arxiv.org/abs/1808.08750v1,NIPS,2018,https://github.com/rgeirhos/generalisation-humans-DNNs,41,2019-01-02 -Using Ranking-CNN for Age Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Using_Ranking-CNN_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/RankingCNN/Using-Ranking-CNN-for-Age-Estimation,33,2019-01-02 -Generative Adversarial Perturbations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Poursaeed_Generative_Adversarial_Perturbations_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/OmidPoursaeed/Generative_Adversarial_Perturbations,40,2019-01-02 -EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis,http://openaccess.thecvf.com/content_iccv_2017/html/Sajjadi_EnhanceNet_Single_Image_ICCV_2017_paper.html,ICCV,2017,https://github.com/msmsajjadi/EnhanceNet-Code,46,2019-01-02 -A Dual-Source Approach for 3D Pose Estimation From a Single Image,http://openaccess.thecvf.com/content_cvpr_2016/html/Yasin_A_Dual-Source_Approach_CVPR_2016_paper.html,CVPR,2016,https://github.com/iqbalu/3D_Pose_Estimation_CVPR2016,32,2019-01-02 -Human Semantic Parsing for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kalayeh_Human_Semantic_Parsing_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/emrahbasaran/SPReID,61,2019-01-02 -Car That Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models,http://openaccess.thecvf.com/content_iccv_2015/html/Jain_Car_That_Knows_ICCV_2015_paper.html,ICCV,2015,https://github.com/asheshjain399/ICCV2015_Brain4Cars,33,2019-01-02 -3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Angela_Dai_3DMV_Joint_3D-Multi-View_ECCV_2018_paper.html,ECCV,2018,https://github.com/angeladai/3DMV,74,2019-01-02 -Towards Binary-Valued Gates for Robust LSTM Training,http://proceedings.mlr.press/v80/li18c.html,ICML,2018,https://github.com/zhuohan123/g2-lstm,41,2019-01-02 -Dynamic Word Embeddings,http://proceedings.mlr.press/v70/bamler17a.html,ICML,2017,https://github.com/YingyuLiang/SemanticVector,32,2019-01-02 -Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image,http://openaccess.thecvf.com/content_ECCV_2018/html/Siyuan_Huang_Monocular_Scene_Parsing_ECCV_2018_paper.html,ECCV,2018,https://github.com/thusiyuan/holistic_scene_parsing,72,2019-01-02 -Unified Deep Supervised Domain Adaptation and Generalization,http://openaccess.thecvf.com/content_iccv_2017/html/Motiian_Unified_Deep_Supervised_ICCV_2017_paper.html,ICCV,2017,https://github.com/samotiian/CCSA,35,2019-01-02 -Conditional Image Synthesis with Auxiliary Classifier GANs,http://proceedings.mlr.press/v70/odena17a.html,ICML,2017,https://github.com/kimhc6028/acgan-pytorch,37,2019-01-02 -Few-Shot Image Recognition by Predicting Parameters From Activations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qiao_Few-Shot_Image_Recognition_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/joe-siyuan-qiao/FewShot-CVPR,37,2019-01-02 -Actor and Observer: Joint Modeling of First and Third-Person Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sigurdsson_Actor_and_Observer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/gsig/actor-observer,48,2019-01-02 -Visualizing and Understanding Atari Agents,http://proceedings.mlr.press/v80/greydanus18a.html,ICML,2018,https://github.com/greydanus/visualize_atari,45,2019-01-02 -A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation,http://openaccess.thecvf.com/content_cvpr_2016/html/Perazzi_A_Benchmark_Dataset_CVPR_2016_paper.html,CVPR,2016,https://github.com/davisvideochallenge/davis-matlab,33,2019-01-02 -NetGAN: Generating Graphs via Random Walks,http://proceedings.mlr.press/v80/bojchevski18a.html,ICML,2018,https://github.com/danielzuegner/netgan,39,2019-01-02 -Hyperbolic Entailment Cones for Learning Hierarchical Embeddings,http://proceedings.mlr.press/v80/ganea18a.html,ICML,2018,https://github.com/dalab/hyperbolic_cones,46,2019-01-02 -Semantic Image Inpainting With Deep Generative Models,http://openaccess.thecvf.com/content_cvpr_2017/html/Yeh_Semantic_Image_Inpainting_CVPR_2017_paper.html,CVPR,2017,https://github.com/ChengBinJin/semantic-image-inpainting,40,2019-01-02 -Image Captioning With Semantic Attention,http://openaccess.thecvf.com/content_cvpr_2016/html/You_Image_Captioning_With_CVPR_2016_paper.html,CVPR,2016,https://github.com/chapternewscu/image-captioning-with-semantic-attention,35,2019-01-02 -Safe Model-based Reinforcement Learning with Stability Guarantees,http://papers.nips.cc/paper/6692-safe-model-based-reinforcement-learning-with-stability-guarantees.pdf,NIPS,2017,https://github.com/befelix/safe_learning,45,2019-01-02 -Learning Detection With Diverse Proposals,http://openaccess.thecvf.com/content_cvpr_2017/html/Azadi_Learning_Detection_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/azadis/LDDP,31,2019-01-02 -Learning-based Video Motion Magnification,http://openaccess.thecvf.com/content_ECCV_2018/html/Tae-Hyun_Oh_Learning-based_Video_Motion_ECCV_2018_paper.html,ECCV,2018,https://github.com/12dmodel/deep_motion_mag,47,2019-01-02 -Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance,http://openaccess.thecvf.com/content_ECCV_2018/html/Ramprasaath_Ramasamy_Selvaraju_Choose_Your_Neuron_ECCV_2018_paper.html,ECCV,2018,https://github.com/ramprs/neuron-importance-zsl,40,2019-01-02 -Mean Field Multi-Agent Reinforcement Learning,http://proceedings.mlr.press/v80/yang18d.html,ICML,2018,https://github.com/mlii/mfrl,43,2019-01-02 -Learning Active Learning from Data,http://papers.nips.cc/paper/7010-learning-active-learning-from-data.pdf,NIPS,2017,https://github.com/ksenia-konyushkova/LAL,36,2019-01-02 -TILDE: A Temporally Invariant Learned DEtector,http://openaccess.thecvf.com/content_cvpr_2015/html/Verdie_TILDE_A_Temporally_2015_CVPR_paper.html,CVPR,2015,https://github.com/kmyid/TILDE,30,2019-01-02 -Deep Saliency With Encoded Low Level Distance Map and High Level Features,http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Deep_Saliency_With_CVPR_2016_paper.html,CVPR,2016,https://github.com/gylee1103/SaliencyELD,34,2019-01-02 -Learning Visual Question Answering by Bootstrapping Hard Attention,http://openaccess.thecvf.com/content_ECCV_2018/html/Mateusz_Malinowski_Learning_Visual_Question_ECCV_2018_paper.html,ECCV,2018,https://github.com/gnouhp/PyTorch-AdaHAN,33,2019-01-02 -Non-Local Image Dehazing,http://openaccess.thecvf.com/content_cvpr_2016/html/Berman_Non-Local_Image_Dehazing_CVPR_2016_paper.html,CVPR,2016,https://github.com/danaberman/non-local-dehazing,50,2019-01-02 -QMDP-Net: Deep Learning for Planning under Partial Observability,http://papers.nips.cc/paper/7055-qmdp-net-deep-learning-for-planning-under-partial-observability.pdf,NIPS,2017,https://github.com/AdaCompNUS/qmdp-net,34,2019-01-02 -3D-PRNN: Generating Shape Primitives With Recurrent Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Zou_3D-PRNN_Generating_Shape_ICCV_2017_paper.html,ICCV,2017,https://github.com/zouchuhang/3D-PRNN,37,2019-01-02 -Learning Local Image Descriptors With Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions,http://openaccess.thecvf.com/content_cvpr_2016/html/G_Learning_Local_Image_CVPR_2016_paper.html,CVPR,2016,https://github.com/vijaykbg/deep-patchmatch,30,2019-01-02 -Transformation-Grounded Image Generation Network for Novel 3D View Synthesis,http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Transformation-Grounded_Image_Generation_CVPR_2017_paper.html,CVPR,2017,https://github.com/silverbottlep/tvsn,35,2019-01-02 -Zero-Shot Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Ankan_Bansal_Zero-Shot_Object_Detection_ECCV_2018_paper.html,ECCV,2018,https://github.com/salman-h-khan/ZSD_Release,43,2019-01-02 -Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training,http://openaccess.thecvf.com/content_iccv_2017/html/Shetty_Speaking_the_Same_ICCV_2017_paper.html,ICCV,2017,https://github.com/rakshithShetty/captionGAN,30,2019-01-02 -Black-box Adversarial Attacks with Limited Queries and Information,http://proceedings.mlr.press/v80/ilyas18a.html,ICML,2018,https://github.com/labsix/limited-blackbox-attacks,46,2019-01-02 -Stacked Cross Attention for Image-Text Matching,http://openaccess.thecvf.com/content_ECCV_2018/html/Kuang-Huei_Lee_Stacked_Cross_Attention_ECCV_2018_paper.html,ECCV,2018,https://github.com/kuanghuei/SCAN,48,2019-01-02 -StyleNet: Generating Attractive Visual Captions With Styles,http://openaccess.thecvf.com/content_cvpr_2017/html/Gan_StyleNet_Generating_Attractive_CVPR_2017_paper.html,CVPR,2017,https://github.com/kacky24/stylenet,32,2019-01-02 -Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes,http://openaccess.thecvf.com/content_cvpr_2017/html/Pohlen_Full-Resolution_Residual_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/hiwonjoon/tf-frrn,31,2019-01-02 -Geometric Loss Functions for Camera Pose Regression With Deep Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Kendall_Geometric_Loss_Functions_CVPR_2017_paper.html,CVPR,2017,https://github.com/futurely/deep-camera-relocalization,34,2019-01-02 -VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization,http://openaccess.thecvf.com/content_cvpr_2017/html/Clark_VidLoc_A_Deep_CVPR_2017_paper.html,CVPR,2017,https://github.com/futurely/deep-camera-relocalization,34,2019-01-02 -PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization,http://openaccess.thecvf.com/content_iccv_2015/html/Kendall_PoseNet_A_Convolutional_ICCV_2015_paper.html,ICCV,2015,https://github.com/futurely/deep-camera-relocalization,34,2019-01-02 -The Statistical Recurrent Unit,http://proceedings.mlr.press/v70/oliva17a.html,ICML,2017,https://github.com/DLHacks/SRU,29,2019-01-02 -SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization,http://proceedings.mlr.press/v70/kim17b.html,ICML,2017,https://github.com/dalgu90/splitnet-wrn,29,2019-01-02 -Graphical Generative Adversarial Networks,http://arxiv.org/abs/1804.03429v1,NIPS,2018,https://github.com/zhenxuan00/graphical-gan,36,2019-01-02 -Fast Bilateral-Space Stereo for Synthetic Defocus,http://openaccess.thecvf.com/content_cvpr_2015/html/Barron_Fast_Bilateral-Space_Stereo_2015_CVPR_paper.html,CVPR,2015,https://github.com/tvandenzegel/fast_bilateral_space_stereo,29,2019-01-02 -Gated Fusion Network for Single Image Dehazing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ren_Gated_Fusion_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rwenqi/GFN-dehazing,35,2019-01-02 -Isolating Sources of Disentanglement in Variational Autoencoders,http://arxiv.org/abs/1802.04942v2,NIPS,2018,https://github.com/rtqichen/beta-tcvae,62,2019-01-02 -Learning Semantic Representations for Unsupervised Domain Adaptation,http://proceedings.mlr.press/v80/xie18c.html,ICML,2018,https://github.com/Mid-Push/Moving-Semantic-Transfer-Network,39,2019-01-02 -GP CaKe: Effective brain connectivity with causal kernels,http://papers.nips.cc/paper/6696-gp-cake-effective-brain-connectivity-with-causal-kernels.pdf,NIPS,2017,https://github.com/LucaAmbrogioni/GP-CaKe-project,46,2019-01-02 -CleanNet: Transfer Learning for Scalable Image Classifier Training With Label Noise,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_CleanNet_Transfer_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kuanghuei/clean-net,33,2019-01-02 -Recurrent Convolutional Neural Network for Object Recognition,http://openaccess.thecvf.com/content_cvpr_2015/html/Liang_Recurrent_Convolutional_Neural_2015_CVPR_paper.html,CVPR,2015,https://github.com/JimLee4530/RCNN,32,2019-01-02 -On the Robustness of Semantic Segmentation Models to Adversarial Attacks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Arnab_On_the_Robustness_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hmph/adversarial-attacks,31,2019-01-02 -3D Point Cloud Registration for Localization Using a Deep Neural Network Auto-Encoder,http://openaccess.thecvf.com/content_cvpr_2017/html/Elbaz_3D_Point_Cloud_CVPR_2017_paper.html,CVPR,2017,https://github.com/gilbaz/LORAX,32,2019-01-02 -Continual Learning Through Synaptic Intelligence,http://proceedings.mlr.press/v70/zenke17a.html,ICML,2017,https://github.com/ganguli-lab/pathint,31,2019-01-02 -In Defense of Color-Based Model-Free Tracking,http://openaccess.thecvf.com/content_cvpr_2015/html/Possegger_In_Defense_of_2015_CVPR_paper.html,CVPR,2015,https://github.com/foolwood/DAT,30,2019-01-02 -SeGAN: Segmenting and Generating the Invisible,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_SeGAN_Segmenting_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ehsanik/SeGAN,36,2019-01-02 -Unsupervised Learning of Disentangled Representations from Video,http://papers.nips.cc/paper/7028-unsupervised-learning-of-disentangled-representations-from-video.pdf,NIPS,2017,https://github.com/edenton/drnet-py,32,2019-01-02 -Deeply Learned Attributes for Crowded Scene Understanding,http://openaccess.thecvf.com/content_cvpr_2015/html/Shao_Deeply_Learned_Attributes_2015_CVPR_paper.html,CVPR,2015,https://github.com/amandajshao/www_deep_crowd,27,2019-01-02 -Parsimonious Labeling,http://openaccess.thecvf.com/content_iccv_2015/html/Dokania_Parsimonious_Labeling_ICCV_2015_paper.html,ICCV,2015,https://github.com/aimerykong/Pixel-Attentional-Gating,33,2019-01-02 -Deep Learning on Lie Groups for Skeleton-Based Action Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Deep_Learning_on_CVPR_2017_paper.html,CVPR,2017,https://github.com/zzhiwu/LieNet,32,2019-01-02 -A Unified Approach of Multi-Scale Deep and Hand-Crafted Features for Defocus Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Park_A_Unified_Approach_CVPR_2017_paper.html,CVPR,2017,https://github.com/zzangjinsun/DHDE_CVPR17,28,2019-01-02 -Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Jiang_Super_SloMo_High_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/TheFairBear/Super-SlowMo,47,2019-01-02 -Human-Centric Indoor Scene Synthesis Using Stochastic Grammar,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Human-Centric_Indoor_Scene_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/SiyuanQi/human-centric-scene-synthesis,33,2019-01-02 -The Sound of Pixels,http://openaccess.thecvf.com/content_ECCV_2018/html/Hang_Zhao_The_Sound_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/roudimit/MUSIC_dataset,40,2019-01-02 -Video Rain Streak Removal by Multiscale Convolutional Sparse Coding,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Video_Rain_Streak_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MinghanLi/MS-CSC-Rain-Streak-Removal,29,2019-01-02 -Adversarial Logit Pairing,http://arxiv.org/abs/1803.06373v1,NIPS,2018,https://github.com/labsix/adversarial-logit-pairing-analysis,32,2019-01-02 -Deflecting Adversarial Attacks With Pixel Deflection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Prakash_Deflecting_Adversarial_Attacks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/iamaaditya/pixel-deflection,34,2019-01-02 -LCNN: Lookup-Based Convolutional Neural Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Bagherinezhad_LCNN_Lookup-Based_Convolutional_CVPR_2017_paper.html,CVPR,2017,https://github.com/hessamb/lcnn,31,2019-01-02 -Deep Model-Based 6D Pose Refinement in RGB,http://openaccess.thecvf.com/content_ECCV_2018/html/Fabian_Manhardt_Deep_Model-Based_6D_ECCV_2018_paper.html,ECCV,2018,https://github.com/fabi92/eccv18-rgb_pose_refinement,30,2019-01-02 -No Fuss Distance Metric Learning Using Proxies,http://openaccess.thecvf.com/content_iccv_2017/html/Movshovitz-Attias_No_Fuss_Distance_ICCV_2017_paper.html,ICCV,2017,https://github.com/dichotomies/proxy-nca,38,2019-01-02 -Learning Warped Guidance for Blind Face Restoration,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaoming_Li_Learning_Warped_Guidance_ECCV_2018_paper.html,ECCV,2018,https://github.com/csxmli2016/GFRNet,39,2019-01-02 -Structured Feature Learning for Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2016/html/Chu_Structured_Feature_Learning_CVPR_2016_paper.html,CVPR,2016,https://github.com/chuxiaoselena/StructuredFeature,29,2019-01-02 -Dense Semantic Image Segmentation with Objects and Attributes,http://openaccess.thecvf.com/content_cvpr_2014/html/Zheng_Dense_Semantic_Image_2014_CVPR_paper.html,CVPR,2014,https://github.com/bittnt/ImageSpirit,28,2019-01-02 -Scene-Independent Group Profiling in Crowd,http://openaccess.thecvf.com/content_cvpr_2014/html/Shao_Scene-Independent_Group_Profiling_2014_CVPR_paper.html,CVPR,2014,https://github.com/amandajshao/crowd_group_profile,28,2019-01-02 -Hierarchical Boundary-Aware Neural Encoder for Video Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Baraldi_Hierarchical_Boundary-Aware_Neural_CVPR_2017_paper.html,CVPR,2017,https://github.com/Yugnaynehc/banet,33,2019-01-02 -Neural Guided Constraint Logic Programming for Program Synthesis,http://arxiv.org/abs/1809.02840v2,NIPS,2018,https://github.com/xuexue/neuralkanren,32,2019-01-02 -Ordinal Regression With Multiple Output CNN for Age Estimation,http://openaccess.thecvf.com/content_cvpr_2016/html/Niu_Ordinal_Regression_With_CVPR_2016_paper.html,CVPR,2016,https://github.com/luoyetx/OrdinalRegression,30,2019-01-02 -Unsupervised Learning of Edges,http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Unsupervised_Learning_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/happyharrycn/unsupervised_edges,29,2019-01-02 -TOM-Net: Learning Transparent Object Matting From a Single Image,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_TOM-Net_Learning_Transparent_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/guanyingc/TOM-Net,30,2019-01-02 -Harvesting Multiple Views for Marker-Less 3D Human Pose Annotations,http://openaccess.thecvf.com/content_cvpr_2017/html/Pavlakos_Harvesting_Multiple_Views_CVPR_2017_paper.html,CVPR,2017,https://github.com/geopavlakos/harvesting,27,2019-01-02 -PatchBatch: A Batch Augmented Loss for Optical Flow,http://openaccess.thecvf.com/content_cvpr_2016/html/Gadot_PatchBatch_A_Batch_CVPR_2016_paper.html,CVPR,2016,https://github.com/DediGadot/PatchBatch,27,2019-01-02 -Real-Time Monocular Depth Estimation Using Synthetic Data With Domain Adaptation via Image Style Transfer,http://openaccess.thecvf.com/content_cvpr_2018/papers/Atapour-Abarghouei_Real-Time_Monocular_Depth_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/atapour/monocularDepth-Inference,37,2019-01-02 -Deep Co-Occurrence Feature Learning for Visual Object Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Shih_Deep_Co-Occurrence_Feature_CVPR_2017_paper.html,CVPR,2017,https://github.com/yafangshih/Deep-COOC,29,2019-01-02 -"Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition",http://openaccess.thecvf.com/content_cvpr_2015/html/Zhu_Understanding_Tools_Task-Oriented_2015_CVPR_paper.html,CVPR,2015,https://github.com/xiaozhuchacha/Kinect2Toolbox,27,2019-01-02 -Quaternion Convolutional Neural Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Xuanyu_Zhu_Quaternion_Convolutional_Neural_ECCV_2018_paper.html,ECCV,2018,https://github.com/TParcollet/Quaternion-Convolutional-Neural-Networks-for-End-to-End-Automatic-Speech-Recognition,30,2019-01-02 -Learning Dynamic Memory Networks for Object Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Tianyu_Yang_Learning_Dynamic_Memory_ECCV_2018_paper.html,ECCV,2018,https://github.com/skyoung/MemTrack,32,2019-01-02 -Viewpoints and Keypoints,http://openaccess.thecvf.com/content_cvpr_2015/html/Tulsiani_Viewpoints_and_Keypoints_2015_CVPR_paper.html,CVPR,2015,https://github.com/shubhtuls/ViewpointsAndKeypoints,25,2019-01-02 -DeepCD: Learning Deep Complementary Descriptors for Patch Representations,http://openaccess.thecvf.com/content_iccv_2017/html/Yang_DeepCD_Learning_Deep_ICCV_2017_paper.html,ICCV,2017,https://github.com/shamangary/DeepCD,26,2019-01-02 -Interpretable Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Interpretable_Convolutional_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/seongjunyun/CNN-with-Dual-Local-and-Global-Attention,40,2019-01-02 -Learning to Detect Salient Objects With Image-Level Supervision,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Learning_to_Detect_CVPR_2017_paper.html,CVPR,2017,https://github.com/scott89/WSS,26,2019-01-02 -Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields,http://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Realtime_Multi-Person_2D_CVPR_2017_paper.html,CVPR,2017,https://github.com/PoseAIChallenger/mxnet_pose_for_AI_challenger,29,2019-01-02 -Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Liang_Deep_Variation-Structured_Reinforcement_CVPR_2017_paper.html,CVPR,2017,https://github.com/nexusapoorvacus/DeepVariationStructuredRL,32,2019-01-02 -State-Frequency Memory Recurrent Neural Networks,http://proceedings.mlr.press/v70/hu17c.html,ICML,2017,https://github.com/hhkunming/State-Frequency-Memory-Recurrent-Neural-Networks,27,2019-01-02 -Deep 360 Pilot: Learning a Deep Agent for Piloting Through 360deg Sports Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Deep_360_Pilot_CVPR_2017_paper.html,CVPR,2017,https://github.com/eborboihuc/Deep360Pilot-CVPR17,27,2019-01-02 -Mask-Guided Contrastive Attention Model for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_Mask-Guided_Contrastive_Attention_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/developfeng/MGCAM,41,2019-01-02 -Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon,http://papers.nips.cc/paper/7071-learning-to-prune-deep-neural-networks-via-layer-wise-optimal-brain-surgeon.pdf,NIPS,2017,https://github.com/csyhhu/L-OBS,31,2019-01-02 -Neural Message Passing for Quantum Chemistry,http://proceedings.mlr.press/v70/gilmer17a.html,ICML,2017,https://github.com/brain-research/mpnn,27,2019-01-02 -Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure,http://papers.nips.cc/paper/6760-stochastic-optimization-with-variance-reduction-for-infinite-datasets-with-finite-sum-structure.pdf,NIPS,2017,https://github.com/albietz/stochs,26,2019-01-02 -Recurrent Scene Parsing With Perspective Understanding in the Loop,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kong_Recurrent_Scene_Parsing_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/aimerykong/Recurrent-Scene-Parsing-with-Perspective-Understanding-in-the-loop,29,2019-01-02 -Disentangling by Factorising,http://proceedings.mlr.press/v80/kim18b.html,ICML,2018,https://github.com/1Konny/FactorVAE,37,2019-01-02 -Actionness Estimation Using Hybrid Fully Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Actionness_Estimation_Using_CVPR_2016_paper.html,CVPR,2016,https://github.com/wanglimin/Actionness-Estimation,26,2019-01-02 -Tangent Convolutions for Dense Prediction in 3D,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tatarchenko_Tangent_Convolutions_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tatarchm/tangent_conv,37,2019-01-02 -SketchyScene: Richly-Annotated Scene Sketches,http://openaccess.thecvf.com/content_ECCV_2018/html/Changqing_Zou_SketchyScene_Richly-Annotated_Scene_ECCV_2018_paper.html,ECCV,2018,https://github.com/SketchyScene/SketchyScene,31,2019-01-02 -Learning to Evaluate Image Captioning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cui_Learning_to_Evaluate_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/richardaecn/cvpr18-caption-eval,38,2019-01-02 -Joint distribution optimal transportation for domain adaptation,http://papers.nips.cc/paper/6963-joint-distribution-optimal-transportation-for-domain-adaptation.pdf,NIPS,2017,https://github.com/rflamary/JDOT,29,2019-01-02 -Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors,http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_SpeedAccuracy_Trade-Offs_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/rayanelleuch/Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors,26,2019-01-02 -Unconstrained 3D Face Reconstruction,http://openaccess.thecvf.com/content_cvpr_2015/html/Roth_Unconstrained_3D_Face_2015_CVPR_paper.html,CVPR,2015,https://github.com/NJUPole/CVPR2015-Unconstrained-3D-Face-Reconstruction,26,2019-01-02 -Adversarially Learned One-Class Classifier for Novelty Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sabokrou_Adversarially_Learned_One-Class_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/khalooei/ALOCC-CVPR2018,37,2019-01-02 -Layer-structured 3D Scene Inference via View Synthesis,http://openaccess.thecvf.com/content_ECCV_2018/html/Shubham_Tulsiani_Layer-structured_3D_Scene_ECCV_2018_paper.html,ECCV,2018,https://github.com/google/layered-scene-inference,28,2019-01-02 -Learning Spread-Out Local Feature Descriptors,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Learning_Spread-Out_Local_ICCV_2017_paper.html,ICCV,2017,https://github.com/ColumbiaDVMM/Spread-out_Local_Feature_Descriptor,28,2019-01-02 -Recurrent Attention Models for Depth-Based Person Identification,http://openaccess.thecvf.com/content_cvpr_2016/html/Haque_Recurrent_Attention_Models_CVPR_2016_paper.html,CVPR,2016,https://github.com/ahaque/ram_person_id,24,2018-09-16 -Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Lei_Zhu_Bi-directional_Feature_Pyramid_ECCV_2018_paper.html,ECCV,2018,https://github.com/zijundeng/BDRAR,32,2019-01-02 -Controllable Video Generation With Sparse Trajectories,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hao_Controllable_Video_Generation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zekunhao1995/ControllableVideoGen,28,2019-01-02 -First Order Generative Adversarial Networks,http://proceedings.mlr.press/v80/seward18a.html,ICML,2018,https://github.com/zalandoresearch/first_order_gan,25,2019-01-02 -Data-Driven 3D Voxel Patterns for Object Category Recognition,http://openaccess.thecvf.com/content_cvpr_2015/html/Xiang_Data-Driven_3D_Voxel_2015_CVPR_paper.html,CVPR,2015,https://github.com/yuxng/3DVP,24,2019-01-02 -Blazingly Fast Video Object Segmentation With Pixel-Wise Metric Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Blazingly_Fast_Video_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yuhuayc/fast-vos,30,2019-01-02 -Revisiting Video Saliency: A Large-Scale Benchmark and a New Model,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Revisiting_Video_Saliency_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wenguanwang/DHF1K,30,2019-01-02 -Temporal Context Network for Activity Localization in Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Temporal_Context_Network_ICCV_2017_paper.html,ICCV,2017,https://github.com/vdavid70619/TCN,24,2019-01-02 -Universal Adversarial Perturbations,http://openaccess.thecvf.com/content_cvpr_2017/html/Moosavi-Dezfooli_Universal_Adversarial_Perturbations_CVPR_2017_paper.html,CVPR,2017,https://github.com/val-iisc/fast-feature-fool,24,2019-01-02 -Shrinkage Fields for Effective Image Restoration,http://openaccess.thecvf.com/content_cvpr_2014/html/Schmidt_Shrinkage_Fields_for_2014_CVPR_paper.html,CVPR,2014,https://github.com/uschmidt83/shrinkage-fields,25,2019-01-02 -Interpretable Intuitive Physics Model,http://openaccess.thecvf.com/content_ECCV_2018/html/Tian_Ye_Interpretable_Intuitive_Physics_ECCV_2018_paper.html,ECCV,2018,https://github.com/tianye95/interpretable-intuitive-physics-model,27,2019-01-02 -Holistically-Nested Edge Detection,http://openaccess.thecvf.com/content_iccv_2015/html/Xie_Holistically-Nested_Edge_Detection_ICCV_2015_paper.html,ICCV,2015,https://github.com/s9xie/hed_release-deprecated,25,2019-01-02 -Improved Variational Autoencoders for Text Modeling using Dilated Convolutions,http://proceedings.mlr.press/v70/yang17d.html,ICML,2017,https://github.com/ryokamoi/dcnn_textvae,26,2019-01-02 -YASS: Yet Another Spike Sorter,http://papers.nips.cc/paper/6989-yass-yet-another-spike-sorter.pdf,NIPS,2017,https://github.com/paninski-lab/yass,25,2019-01-02 -Phase-Based Frame Interpolation for Video,http://openaccess.thecvf.com/content_cvpr_2015/html/Meyer_Phase-Based_Frame_Interpolation_2015_CVPR_paper.html,CVPR,2015,https://github.com/owang/PhaseBasedInterpolation,28,2019-01-02 -Going Deeper With Convolutions,http://openaccess.thecvf.com/content_cvpr_2015/html/Szegedy_Going_Deeper_With_2015_CVPR_paper.html,CVPR,2015,https://github.com/nutszebra/googlenet,25,2019-01-02 -Shading Annotations in the Wild,http://openaccess.thecvf.com/content_cvpr_2017/html/Kovacs_Shading_Annotations_in_CVPR_2017_paper.html,CVPR,2017,https://github.com/kovibalu/saw_release,24,2019-01-02 -Deep Texture Manifold for Ground Terrain Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xue_Deep_Texture_Manifold_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiaxue1993/Deep-Encoding-Pooling-Network-DEP-,25,2019-01-02 -Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Structured_Attention_Guided_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/danxuhk/StructuredAttentionDepthEstimation,46,2019-01-02 -IQA: Visual Question Answering in Interactive Environments,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gordon_IQA_Visual_Question_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/danielgordon10/thor-iqa-cvpr-2018,60,2019-01-02 -Real-Time Neural Style Transfer for Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Real-Time_Neural_Style_CVPR_2017_paper.html,CVPR,2017,https://github.com/curaai00/RT-StyleTransfer-forVideo,30,2019-01-02 -Deep Regression Tracking with Shrinkage Loss,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiankai_Lu_Deep_Regression_Tracking_ECCV_2018_paper.html,ECCV,2018,https://github.com/chaoma99/DSLT,34,2019-01-02 -Multi-Agent Diverse Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ghosh_Multi-Agent_Diverse_Generative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/arnabgho/MADGAN,23,2018-09-16 -Reducing Reparameterization Gradient Variance,http://papers.nips.cc/paper/6961-reducing-reparameterization-gradient-variance.pdf,NIPS,2017,https://github.com/andymiller/ReducedVarianceReparamGradients,24,2019-01-02 -"You Only Look Once: Unified, Real-Time Object Detection",http://openaccess.thecvf.com/content_cvpr_2016/html/Redmon_You_Only_Look_CVPR_2016_paper.html,CVPR,2016,https://github.com/andersy005/keras-yolo,26,2019-01-02 -Fast Training of Triplet-Based Deep Binary Embedding Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhuang_Fast_Training_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/xwzy/Triplet-deep-hash-pytorch,25,2019-01-02 -L0TV: A New Method for Image Restoration in the Presence of Impulse Noise,http://openaccess.thecvf.com/content_cvpr_2015/html/Yuan_L0TV_A_New_2015_CVPR_paper.html,CVPR,2015,https://github.com/peisuke/L0TV,22,2019-01-02 -Adaptive Color Attributes for Real-Time Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2014/html/Danelljan_Adaptive_Color_Attributes_2014_CVPR_paper.html,CVPR,2014,https://github.com/mostafaizz/ColorTracker,25,2019-01-02 -Domain-Adaptive Deep Network Compression,http://openaccess.thecvf.com/content_iccv_2017/html/Masana_Domain-Adaptive_Deep_Network_ICCV_2017_paper.html,ICCV,2017,https://github.com/mmasana/DALR,24,2019-01-02 -Interspecies Knowledge Transfer for Facial Keypoint Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Rashid_Interspecies_Knowledge_Transfer_CVPR_2017_paper.html,CVPR,2017,https://github.com/menorashid/animal_human_kp,25,2019-01-02 -Zero-Order Reverse Filtering,http://openaccess.thecvf.com/content_iccv_2017/html/Tao_Zero-Order_Reverse_Filtering_ICCV_2017_paper.html,ICCV,2017,https://github.com/jiangsutx/DeFilter,23,2019-01-02 -Reconstructing the World* in Six Days *(As Captured by the Yahoo 100 Million Image Dataset),http://openaccess.thecvf.com/content_cvpr_2015/html/Heinly_Reconstructing_the_World_2015_CVPR_paper.html,CVPR,2015,https://github.com/jheinly/streaming_connected_component_discovery,25,2019-01-02 -Learning High Dynamic Range From Outdoor Panoramas,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Learning_High_Dynamic_ICCV_2017_paper.html,ICCV,2017,https://github.com/jacenfox/ldr2hdr-public,26,2019-01-02 -A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering,http://papers.nips.cc/paper/6734-a-dirichlet-mixture-model-of-hawkes-processes-for-event-sequence-clustering.pdf,NIPS,2017,https://github.com/HongtengXu/Hawkes-Process-Toolkit,24,2019-01-02 -Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Multimodal_Transfer_A_CVPR_2017_paper.html,CVPR,2017,https://github.com/fullfanta/multimodal_transfer,22,2019-01-02 -Contrastive Learning for Image Captioning,http://papers.nips.cc/paper/6691-contrastive-learning-for-image-captioning.pdf,NIPS,2017,https://github.com/doubledaibo/clcaption_nips2017,26,2019-01-02 -Graph-Cut RANSAC,http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/danini/graph-cut-ransac,32,2019-01-02 -A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising,http://openaccess.thecvf.com/content_ECCV_2018/html/XU_JUN_A_Trilateral_Weighted_ECCV_2018_paper.html,ECCV,2018,https://github.com/csjunxu/TWSC-ECCV2018,30,2019-01-02 -Phrase Localization and Visual Relationship Detection With Comprehensive Image-Language Cues,http://openaccess.thecvf.com/content_iccv_2017/html/Plummer_Phrase_Localization_and_ICCV_2017_paper.html,ICCV,2017,https://github.com/BryanPlummer/pl-clc,27,2019-01-02 -Conditional Image-to-Image Translation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Conditional_Image-to-Image_Translation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/znxlwm/pytorch-Conditional-image-to-image-translation,25,2019-01-02 -Learning to Promote Saliency Detectors,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zeng_Learning_to_Promote_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zengxianyu/lps,21,2019-01-02 -LF-Net: Learning Local Features from Images,https://arxiv.org/abs/1805.09662,NIPS,2018,https://github.com/vcg-uvic/lf-net-release,55,2019-01-02 -Straight to Shapes: Real-Time Detection of Encoded Shapes,http://openaccess.thecvf.com/content_cvpr_2017/html/Jetley_Straight_to_Shapes_CVPR_2017_paper.html,CVPR,2017,https://github.com/torrvision/straighttoshapes,23,2019-01-02 -Visualizing the Loss Landscape of Neural Nets,http://arxiv.org/abs/1712.09913v2,NIPS,2018,https://github.com/tomgoldstein/loss-landscape,724,2019-01-02 -First Person Action Recognition Using Deep Learned Descriptors,http://openaccess.thecvf.com/content_cvpr_2016/html/Singh_First_Person_Action_CVPR_2016_paper.html,CVPR,2016,https://github.com/suriyasingh/EgoConvNet,21,2019-01-02 -Exploring Disentangled Feature Representation Beyond Face Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Exploring_Disentangled_Feature_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sciencefans/D2AE-Face-Generator,29,2019-01-02 -Between-Class Learning for Image Classification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tokozume_Between-Class_Learning_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mil-tokyo/bc_learning_image,26,2019-01-02 -CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Batsos_CBMV_A_Coalesced_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kbatsos/CBMV,25,2019-01-02 -Dense Human Body Correspondences Using Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Dense_Human_Body_CVPR_2016_paper.html,CVPR,2016,https://github.com/halimacc/DenseHumanBodyCorrespondences,27,2019-01-02 -Hash Embeddings for Efficient Word Representations,http://papers.nips.cc/paper/7078-hash-embeddings-for-efficient-word-representations.pdf,NIPS,2017,https://github.com/dsv77/hashembedding/,21,2018-09-16 -Exploiting Saliency for Object Segmentation From Image Level Labels,http://openaccess.thecvf.com/content_cvpr_2017/html/Oh_Exploiting_Saliency_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/coallaoh/GuidedLabelling,24,2019-01-02 -Improving Shape Deformation in Unsupervised Image-to-Image Translation,http://openaccess.thecvf.com/content_ECCV_2018/html/Aaron_Gokaslan_Improving_Shape_Deformation_ECCV_2018_paper.html,ECCV,2018,https://github.com/brownvc/ganimorph,33,2019-01-02 -Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net,http://papers.nips.cc/paper/7026-variational-walkback-learning-a-transition-operator-as-a-stochastic-recurrent-net.pdf,NIPS,2017,https://github.com/anirudh9119/walkback_nips17,23,2019-01-02 -Eye In-Painting With Exemplar Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Dolhansky_Eye_In-Painting_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhangqianhui/Exemplar-GAN-Eye-Inpainting-Tensorflow,35,2019-01-02 -EC-Net: an Edge-aware Point set Consolidation Network,http://openaccess.thecvf.com/content_ECCV_2018/html/Lequan_Yu_EC-Net_an_Edge-aware_ECCV_2018_paper.html,ECCV,2018,https://github.com/yulequan/EC-Net,27,2019-01-02 -Asymmetric Tri-training for Unsupervised Domain Adaptation,http://proceedings.mlr.press/v70/saito17a.html,ICML,2017,https://github.com/vtddggg/ATDA,24,2019-01-02 -Detecting Vanishing Points Using Global Image Context in a Non-Manhattan World,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhai_Detecting_Vanishing_Points_CVPR_2016_paper.html,CVPR,2016,https://github.com/viibridges/gc-horizon-detector,22,2019-01-02 -STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling,http://openaccess.thecvf.com/content_cvpr_2017/html/He_STD2P_RGBD_Semantic_CVPR_2017_paper.html,CVPR,2017,https://github.com/SSAW14/STD2P,22,2019-01-02 -Deep Mean-Shift Priors for Image Restoration,http://papers.nips.cc/paper/6678-deep-mean-shift-priors-for-image-restoration.pdf,NIPS,2017,https://github.com/siavashBigdeli/DMSP,20,2019-01-02 -Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Beyond_Frontal_Faces_2015_CVPR_paper.html,CVPR,2015,https://github.com/sciencefans/Beyond-Frontal-Faces,21,2019-01-02 -SimplE Embedding for Link Prediction in Knowledge Graphs,http://arxiv.org/abs/1802.04868v1,NIPS,2018,https://github.com/Mehran-k/SimplE,42,2019-01-02 -Learning Continuous Semantic Representations of Symbolic Expressions,http://proceedings.mlr.press/v70/allamanis17a.html,ICML,2017,https://github.com/mast-group/eqnet,22,2019-01-02 -CondenseNet: An Efficient DenseNet Using Learned Group Convolutions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_CondenseNet_An_Efficient_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/markdtw/condensenet-tensorflow,22,2019-01-02 -The Numerics of GANs,http://papers.nips.cc/paper/6779-the-numerics-of-gans.pdf,NIPS,2017,https://github.com/LMescheder/TheNumericsOfGANs,20,2019-01-02 -Dense Captioning With Joint Inference and Visual Context,http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Dense_Captioning_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/linjieyangsc/densecap,24,2019-01-02 -Learning Convolutional Networks for Content-Weighted Image Compression,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Convolutional_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/limuhit/ImageCompression,25,2019-01-02 -SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Faraone_SYQ_Learning_Symmetric_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/julianfaraone/SYQ,24,2019-01-02 -Weakly-Supervised Learning of Visual Relations,http://openaccess.thecvf.com/content_iccv_2017/html/Peyre_Weakly-Supervised_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/jpeyre/unrel,20,2019-01-02 -CSGNet: Neural Shape Parser for Constructive Solid Geometry,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sharma_CSGNet_Neural_Shape_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Hippogriff/CSGNet,21,2019-01-02 -Towards Accurate Multi-Person Pose Estimation in the Wild,http://openaccess.thecvf.com/content_cvpr_2017/html/Papandreou_Towards_Accurate_Multi-Person_CVPR_2017_paper.html,CVPR,2017,https://github.com/hackiey/keypoints,30,2019-01-02 -Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Nguyen_Improved_Fusion_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cvlab-tohoku/Dense-CoAttention-Network,33,2019-01-02 -Real-time 'Actor-Critic' Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Boyu_Chen_Real-time_Actor-Critic_Tracking_ECCV_2018_paper.html,ECCV,2018,https://github.com/bychen515/ACT,46,2019-01-02 -Flow-Grounded Spatial-Temporal Video Prediction from Still Images,http://openaccess.thecvf.com/content_ECCV_2018/html/Yijun_Li_Flow-Grounded_Spatial-Temporal_Video_ECCV_2018_paper.html,ECCV,2018,https://github.com/Yijunmaverick/FlowGrounded-VideoPrediction,32,2019-01-02 -Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings,http://proceedings.mlr.press/v80/co-reyes18a.html,ICML,2018,https://github.com/wyndwarrior/Sectar,29,2019-01-02 -Dual Discriminator Generative Adversarial Nets,http://papers.nips.cc/paper/6860-dual-discriminator-generative-adversarial-nets.pdf,NIPS,2017,https://github.com/tund/D2GAN,23,2019-01-02 -Partial Transfer Learning With Selective Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Partial_Transfer_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/thuml/SAN,26,2019-01-02 -Learning Single-View 3D Reconstruction with Limited Pose Supervision,http://openaccess.thecvf.com/content_ECCV_2018/html/Guandao_Yang_A_Unified_Framework_ECCV_2018_paper.html,ECCV,2018,https://github.com/stevenygd/3d-recon,33,2019-01-02 -Cross-Modal Deep Variational Hand Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Spurr_Cross-Modal_Deep_Variational_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/spurra/vae-hands-3d,26,2019-01-02 -Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search,http://proceedings.mlr.press/v80/suganuma18a.html,ICML,2018,https://github.com/sg-nm/Evolutionary-Autoencoders,23,2019-01-02 -Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization,http://openaccess.thecvf.com/content_iccv_2017/html/Coskun_Long_Short-Term_Memory_ICCV_2017_paper.html,ICCV,2017,https://github.com/Seleucia/lstmkf_ICCV2017,24,2019-01-02 -Speaker-Follower Models for Vision-and-Language Navigation,https://arxiv.org/abs/1806.02724,NIPS,2018,https://github.com/ronghanghu/speaker_follower,33,2019-01-02 -Learning Mid-level Filters for Person Re-identification,http://openaccess.thecvf.com/content_cvpr_2014/html/Zhao_Learning_Mid-level_Filters_2014_CVPR_paper.html,CVPR,2014,https://github.com/Robert0812/midfilter_reid,20,2019-01-02 -Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Liang-Chieh_Chen_Encoder-Decoder_with_Atrous_ECCV_2018_paper.html,ECCV,2018,https://github.com/qixuxiang/deeplabv3plus,28,2019-01-02 -Deep Growing Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Wang_Deep_Growing_Learning_ICCV_2017_paper.html,ICCV,2017,https://github.com/QData/deep2Read,21,2019-01-02 -When Unsupervised Domain Adaptation Meets Tensor Representations,http://openaccess.thecvf.com/content_iccv_2017/html/Lu_When_Unsupervised_Domain_ICCV_2017_paper.html,ICCV,2017,https://github.com/poppinace/TAISL,22,2019-01-02 -DropoutNet: Addressing Cold Start in Recommender Systems,http://papers.nips.cc/paper/7081-dropoutnet-addressing-cold-start-in-recommender-systems.pdf,NIPS,2017,https://github.com/layer6ai-labs/DropoutNet,27,2019-01-02 -Incremental Learning of Object Detectors Without Catastrophic Forgetting,http://openaccess.thecvf.com/content_iccv_2017/html/Shmelkov_Incremental_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/kshmelkov/incremental_detectors,24,2019-01-02 -Adversarial Feature Matching for Text Generation,http://proceedings.mlr.press/v70/zhang17b.html,ICML,2017,https://github.com/Jeff-HOU/UROP-Adversarial-Feature-Matching-for-Text-Generation,18,2019-01-02 -Explicit Inductive Bias for Transfer Learning with Convolutional Networks,http://proceedings.mlr.press/v80/li18a.html,ICML,2018,https://github.com/holyseven/TransferLearningClassification,24,2019-01-02 -Learning to Blend Photos,http://openaccess.thecvf.com/content_ECCV_2018/html/Wei-Chih_Hung_Learning_to_Blend_ECCV_2018_paper.html,ECCV,2018,https://github.com/hfslyc/LearnToBlend,42,2019-01-02 -Open Set Domain Adaptation,http://openaccess.thecvf.com/content_iccv_2017/html/Busto_Open_Set_Domain_ICCV_2017_paper.html,ICCV,2017,https://github.com/Heliot7/open-set-da,25,2019-01-02 -Learning to Pivot with Adversarial Networks,http://papers.nips.cc/paper/6699-learning-to-pivot-with-adversarial-networks.pdf,NIPS,2017,https://github.com/glouppe/paper-learning-to-pivot,21,2019-01-02 -A Generative Adversarial Approach for Zero-Shot Learning From Noisy Texts,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhu_A_Generative_Adversarial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/EthanZhu90/ZSL_GAN_CVPR18,122,2019-01-02 -Event-Based Visual Inertial Odometry,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Event-Based_Visual_Inertial_CVPR_2017_paper.html,CVPR,2017,https://github.com/daniilidis-group/event_feature_tracking,27,2019-01-02 -Hyperbolic Neural Networks,http://arxiv.org/abs/1805.09112v2,NIPS,2018,https://github.com/dalab/hyperbolic_nn,37,2019-01-02 -LEGO: Learning Edge With Geometry All at Once by Watching Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_LEGO_Learning_Edge_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhenheny/LEGO,24,2019-01-02 -Audio-Visual Event Localization in Unconstrained Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Yapeng_Tian_Audio-Visual_Event_Localization_ECCV_2018_paper.html,ECCV,2018,https://github.com/YapengTian/AVE-ECCV18,25,2019-01-02 -Learning Dynamic Siamese Network for Visual Object Tracking,http://openaccess.thecvf.com/content_iccv_2017/html/Guo_Learning_Dynamic_Siamese_ICCV_2017_paper.html,ICCV,2017,https://github.com/tsingqguo/DSiam,21,2019-01-02 -Structured Generative Adversarial Networks,http://papers.nips.cc/paper/6979-structured-generative-adversarial-networks.pdf,NIPS,2017,https://github.com/thudzj/StructuredGAN,19,2019-01-02 -Neural Code Comprehension: A Learnable Representation of Code Semantics,http://arxiv.org/abs/1806.07336v2,NIPS,2018,https://github.com/spcl/ncc,35,2019-01-02 -Im2Flow: Motion Hallucination From Static Images for Action Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gao_Im2Flow_Motion_Hallucination_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rhgao/Im2Flow,22,2019-01-02 -Deep Reinforcement Learning of Marked Temporal Point Processes,http://arxiv.org/abs/1805.09360v1,NIPS,2018,https://github.com/Networks-Learning/tpprl,24,2019-01-02 -Understanding Deep Features With Computer-Generated Imagery,http://openaccess.thecvf.com/content_iccv_2015/html/Aubry_Understanding_Deep_Features_ICCV_2015_paper.html,ICCV,2015,https://github.com/mathieuaubry/features_analysis,19,2019-01-02 -Single Shot Scene Text Retrieval,http://openaccess.thecvf.com/content_ECCV_2018/html/Lluis_Gomez_Single_Shot_Scene_ECCV_2018_paper.html,ECCV,2018,https://github.com/lluisgomez/single-shot-str,29,2019-01-02 -Deep Randomized Ensembles for Metric Learning,http://openaccess.thecvf.com/content_ECCV_2018/html/Hong_Xuan_Randomized_Ensemble_Embeddings_ECCV_2018_paper.html,ECCV,2018,https://github.com/littleredxh/DREML,30,2019-01-02 -Image Super-Resolution Using Dense Skip Connections,http://openaccess.thecvf.com/content_iccv_2017/html/Tong_Image_Super-Resolution_Using_ICCV_2017_paper.html,ICCV,2017,https://github.com/kweisamx/TensorFlow-SR-DenseNet,22,2019-01-02 -Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Hallucinated-IQA_No-Reference_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kwanyeelin/HIQA,22,2019-01-02 -Neural Architecture Search with Bayesian Optimisation and Optimal Transport,https://arxiv.org/abs/1802.07191,NIPS,2018,https://github.com/kirthevasank/nasbot,39,2019-01-02 -Joint Gap Detection and Inpainting of Line Drawings,http://openaccess.thecvf.com/content_cvpr_2017/html/Sasaki_Joint_Gap_Detection_CVPR_2017_paper.html,CVPR,2017,https://github.com/kaidlc/CVPR2017_linedrawings,19,2019-01-02 -Learning to Multitask,http://arxiv.org/abs/1805.07541v1,NIPS,2018,https://github.com/jfutoma/MGP-RNN,22,2019-01-02 -Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier,http://proceedings.mlr.press/v70/futoma17a.html,ICML,2017,https://github.com/jfutoma/MGP-RNN,22,2019-01-02 -Combined Group and Exclusive Sparsity for Deep Neural Networks,http://proceedings.mlr.press/v70/yoon17a.html,ICML,2017,https://github.com/jaehong-yoon93/CGES,21,2019-01-02 -Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Skeleton_Key_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/feiyu1990/Skeleton-key,20,2019-01-02 -Deep High Dynamic Range Imaging with Large Foreground Motions,http://openaccess.thecvf.com/content_ECCV_2018/html/Shangzhe_Wu_Deep_High_Dynamic_ECCV_2018_paper.html,ECCV,2018,https://github.com/elliottwu/DeepHDR,30,2019-01-02 -Who Let the Dogs Out? Modeling Dog Behavior From Visual Data,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_Who_Let_the_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ehsanik/dogTorch,27,2019-01-02 -GraphBit: Bitwise Interaction Mining via Deep Reinforcement Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Duan_GraphBit_Bitwise_Interaction_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/duanyq14/GraphBit,20,2019-01-02 -Stochastic Generative Hashing,http://proceedings.mlr.press/v70/dai17a.html,ICML,2017,https://github.com/doubling/Stochastic_Generative_Hashing,18,2019-01-02 -Minimal Scene Descriptions from Structure from Motion Models,http://openaccess.thecvf.com/content_cvpr_2014/html/Cao_Minimal_Scene_Descriptions_2014_CVPR_paper.html,CVPR,2014,https://github.com/caosong/minimal_scene,22,2019-01-02 -Context Selection for Embedding Models,http://papers.nips.cc/paper/7067-context-selection-for-embedding-models.pdf,NIPS,2017,https://github.com/blei-lab/context-selection-embedding,20,2019-01-02 -HICO: A Benchmark for Recognizing Human-Object Interactions in Images,http://openaccess.thecvf.com/content_iccv_2015/html/Chao_HICO_A_Benchmark_ICCV_2015_paper.html,ICCV,2015,https://github.com/ywchao/hico_benchmark,18,2019-01-02 -Fully Motion-Aware Network for Video Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Shiyao_Wang_Fully_Motion-Aware_Network_ECCV_2018_paper.html,ECCV,2018,https://github.com/wangshy31/MANet_for_Video_Object_Detection,41,2019-01-02 -DualNet: Learn Complementary Features for Image Recognition,http://openaccess.thecvf.com/content_iccv_2017/html/Hou_DualNet_Learn_Complementary_ICCV_2017_paper.html,ICCV,2017,https://github.com/ustc-vim/dualnet,17,2019-01-02 -PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_PiCANet_Learning_Pixel-Wise_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Ugness/PiCANet-Implementation,28,2019-01-02 -A Bayesian Data Augmentation Approach for Learning Deep Models,http://papers.nips.cc/paper/6872-a-bayesian-data-augmentation-approach-for-learning-deep-models.pdf,NIPS,2017,https://github.com/toantm/keras-bda,18,2019-01-02 -Attentive Semantic Video Generation Using Captions,http://openaccess.thecvf.com/content_iccv_2017/html/Marwah_Attentive_Semantic_Video_ICCV_2017_paper.html,ICCV,2017,https://github.com/Singularity42/cap2vid,18,2019-01-02 -Diversity Regularized Spatiotemporal Attention for Video-Based Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Diversity_Regularized_Spatiotemporal_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ShuangLI59/Diversity-Regularized-Spatiotemporal-Attention,25,2019-01-02 -Accumulated Stability Voting: A Robust Descriptor From Descriptors of Multiple Scales,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Accumulated_Stability_Voting_CVPR_2016_paper.html,CVPR,2016,https://github.com/shamangary/ASV,19,2019-01-02 -PieAPP: Perceptual Image-Error Assessment Through Pairwise Preference,http://openaccess.thecvf.com/content_cvpr_2018/papers/Prashnani_PieAPP_Perceptual_Image-Error_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/prashnani/PerceptualImageError,36,2019-01-02 -Link Prediction Based on Graph Neural Networks,http://arxiv.org/abs/1802.09691v2,NIPS,2018,https://github.com/muhanzhang/SEAL,41,2019-01-02 -Multi-scale Residual Network for Image Super-Resolution,http://openaccess.thecvf.com/content_ECCV_2018/html/Juncheng_Li_Multi-scale_Residual_Network_ECCV_2018_paper.html,ECCV,2018,https://github.com/MIVRC/MSRN-PyTorch,41,2019-01-02 -Learning Compact Geometric Features,http://openaccess.thecvf.com/content_iccv_2017/html/Khoury_Learning_Compact_Geometric_ICCV_2017_paper.html,ICCV,2017,https://github.com/marckhoury/CGF,19,2019-01-02 -GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints,http://openaccess.thecvf.com/content_ECCV_2018/html/Zixin_Luo_Learning_Local_Descriptors_ECCV_2018_paper.html,ECCV,2018,https://github.com/lzx551402/geodesc,32,2019-01-02 -Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow,http://openaccess.thecvf.com/content_cvpr_2014/html/Bao_Fast_Edge-Preserving_PatchMatch_2014_CVPR_paper.html,CVPR,2014,https://github.com/linchaobao/EPPM,18,2019-01-02 -Scene Parsing With Global Context Embedding,http://openaccess.thecvf.com/content_iccv_2017/html/Hung_Scene_Parsing_With_ICCV_2017_paper.html,ICCV,2017,https://github.com/hfslyc/GCPNet,20,2019-01-02 -DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors,http://arxiv.org/abs/1805.07445v3,NIPS,2018,https://github.com/dojoteef/dvae,18,2019-01-02 -Deep Metric Learning via Facility Location,http://openaccess.thecvf.com/content_cvpr_2017/html/Song_Deep_Metric_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/CongWeilin/cluster-loss-tensorflow,20,2019-01-02 -Proposal Flow,http://openaccess.thecvf.com/content_cvpr_2016/html/Ham_Proposal_Flow_CVPR_2016_paper.html,CVPR,2016,https://github.com/bsham/ProposalFlow,20,2019-01-02 -Semantic Component Analysis,http://openaccess.thecvf.com/content_iccv_2015/html/Murdock_Semantic_Component_Analysis_ICCV_2015_paper.html,ICCV,2015,https://github.com/aubry74/visual-word2vec,17,2019-01-02 -Learning Large-Scale Automatic Image Colorization,http://openaccess.thecvf.com/content_iccv_2015/html/Deshpande_Learning_Large-Scale_Automatic_ICCV_2015_paper.html,ICCV,2015,https://github.com/aditya12agd5/iccv15_lscolorization,17,2019-01-02 -Predictive-Corrective Networks for Action Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Dave_Predictive-Corrective_Networks_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/achalddave/predictive-corrective,18,2019-01-02 -MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_MDNet_A_Semantically_CVPR_2017_paper.html,CVPR,2017,https://github.com/zizhaozhang/mdnet-cvpr2017,18,2019-01-02 -Scale-Aware Alignment of Hierarchical Image Segmentation,http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Scale-Aware_Alignment_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/yuhuayc/align-hier,20,2019-01-02 -Dimensionality-Driven Learning with Noisy Labels,http://proceedings.mlr.press/v80/ma18d.html,ICML,2018,https://github.com/xingjunm/dimensionality-driven-learning,20,2019-01-02 -Estimating Mutual Information for Discrete-Continuous Mixtures,http://papers.nips.cc/paper/7180-estimating-mutual-information-for-discrete-continuous-mixtures.pdf,NIPS,2017,https://github.com/wgao9/mixed_KSG,16,2019-01-02 -Learning to Push the Limits of Efficient FFT-Based Image Deconvolution,http://openaccess.thecvf.com/content_iccv_2017/html/Kruse_Learning_to_Push_ICCV_2017_paper.html,ICCV,2017,https://github.com/uschmidt83/fourier-deconvolution-network,16,2019-01-02 -Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM,http://papers.nips.cc/paper/6850-accuracy-first-selecting-a-differential-privacy-level-for-accuracy-constrained-erm.pdf,NIPS,2017,https://github.com/steven7woo/Accuracy-First-Differential-Privacy,21,2019-01-02 -Crowd Counting With Deep Negative Correlation Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shi_Crowd_Counting_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shizenglin/Deep-NCL,20,2019-01-02 -Triplet Loss in Siamese Network for Object Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Xingping_Dong_Triplet_Loss_with_ECCV_2018_paper.html,ECCV,2018,https://github.com/shenjianbing/TripletTracking,17,2019-01-02 -Learning Generative ConvNets via Multi-Grid Modeling and Sampling,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gao_Learning_Generative_ConvNets_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ruiqigao/Multigrid_learning,17,2019-01-02 -Explainable Neural Computation via Stack Neural Module Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Ronghang_Hu_Explainable_Neural_Computation_ECCV_2018_paper.html,ECCV,2018,https://github.com/ronghanghu/snmn,29,2019-01-02 -FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Verma_FeaStNet_Feature-Steered_Graph_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nitika-verma/FeaStNet,18,2019-01-02 -Deep Future Gaze: Gaze Anticipation on Egocentric Videos Using Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Deep_Future_Gaze_CVPR_2017_paper.html,CVPR,2017,https://github.com/Mengmi/deepfuturegaze_gan,17,2019-01-02 -3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data,https://arxiv.org/abs/1807.02547,NIPS,2018,https://github.com/mariogeiger/se3cnn,33,2019-01-02 -FALKON: An Optimal Large Scale Kernel Method,http://papers.nips.cc/paper/6978-falkon-an-optimal-large-scale-kernel-method.pdf,NIPS,2017,https://github.com/LCSL/FALKON_paper,17,2019-01-02 -Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Towards_Faster_Training_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiangtaoxie/fast-MPN-COV,40,2019-01-02 -Simultaneous Feature Learning and Hash Coding With Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2015/html/Lai_Simultaneous_Feature_Learning_2015_CVPR_paper.html,CVPR,2015,https://github.com/HYPJUDY/caffe-dnnh,16,2019-01-02 -POSEidon: Face-From-Depth for Driver Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Borghi_POSEidon_Face-From-Depth_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/gdubrg/POSEidon-Biwi,20,2019-01-02 -Semantic Segmentation With Boundary Neural Fields,http://openaccess.thecvf.com/content_cvpr_2016/html/Bertasius_Semantic_Segmentation_With_CVPR_2016_paper.html,CVPR,2016,https://github.com/gberta/BNF_globalization,19,2019-01-02 -InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations,http://papers.nips.cc/paper/6971-infogail-interpretable-imitation-learning-from-visual-demonstrations.pdf,NIPS,2017,https://github.com/ermongroup/infogail,20,2019-01-02 -Neural system identification for large populations separating “what” and “where”,http://papers.nips.cc/paper/6942-neural-system-identification-for-large-populations-separating-what-and-where.pdf,NIPS,2017,https://github.com/david-klindt/NIPS2017,17,2019-01-02 -Zero-Inflated Exponential Family Embeddings,http://proceedings.mlr.press/v70/liu17a.html,ICML,2017,https://github.com/blei-lab/zero-inflated-embedding,20,2019-01-02 -Visual Question Reasoning on General Dependency Tree,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Visual_Question_Reasoning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/bezorro/ACMN-Pytorch,17,2019-01-02 -Deep Unsupervised Similarity Learning Using Partially Ordered Sets,http://openaccess.thecvf.com/content_cvpr_2017/html/Bautista_Deep_Unsupervised_Similarity_CVPR_2017_paper.html,CVPR,2017,https://github.com/asanakoy/deep_unsupervised_posets,17,2019-01-02 -Disentangling Factors of Variation with Cycle-Consistent Variational Auto-Encoders,http://openaccess.thecvf.com/content_ECCV_2018/html/Ananya_Harsh_Jha_Disentangling_Factors_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/ananyahjha93/cycle-consistent-vae,19,2019-01-02 -Unpaired Image-To-Image Translation Using Cycle-Consistent Adversarial Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Unpaired_Image-To-Image_Translation_ICCV_2017_paper.html,ICCV,2017,https://github.com/adepierre/Caffe_CycleGAN,20,2019-01-02 -Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Zero-Shot_Visual_Recognition_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zjuchenlong/sp-aen.cvpr18,20,2019-01-02 -Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ding_Weakly-Supervised_Action_Segmentation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Zephyr-D/TCFPN-ISBA,16,2019-01-02 -Label Distribution Learning Forests,http://papers.nips.cc/paper/6685-label-distribution-learning-forests.pdf,NIPS,2017,https://github.com/shenwei1231/caffe-LDLForests,16,2019-01-02 -Shallow Updates for Deep Reinforcement Learning,http://papers.nips.cc/paper/6906-shallow-updates-for-deep-reinforcement-learning.pdf,NIPS,2017,https://github.com/Shallow-Updates-for-Deep-RL/Shallow_Updates_for_Deep_RL,15,2019-01-02 -Learning Spherical Convolution for Fast Features from 360° Imagery,http://papers.nips.cc/paper/6656-learning-spherical-convolution-for-fast-features-from-360-imagery.pdf,NIPS,2017,https://github.com/sammy-su/Spherical-Convolution,22,2019-01-02 -Bottom-Up and Top-Down Reasoning With Hierarchical Rectified Gaussians,http://openaccess.thecvf.com/content_cvpr_2016/html/Hu_Bottom-Up_and_Top-Down_CVPR_2016_paper.html,CVPR,2016,https://github.com/peiyunh/rg-mpii,16,2019-01-02 -"Chained Multi-Stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection",http://openaccess.thecvf.com/content_iccv_2017/html/Zolfaghari_Chained_Multi-Stream_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/mzolfaghari/chained-multistream-networks,19,2019-01-02 -BIER - Boosting Independent Embeddings Robustly,http://openaccess.thecvf.com/content_iccv_2017/html/Opitz_BIER_-_Boosting_ICCV_2017_paper.html,ICCV,2017,https://github.com/mop/bier,18,2019-01-02 -Seeing 3D Chairs: Exemplar Part-based 2D-3D Alignment using a Large Dataset of CAD Models,http://openaccess.thecvf.com/content_cvpr_2014/html/Aubry_Seeing_3D_Chairs_2014_CVPR_paper.html,CVPR,2014,https://github.com/mathieuaubry/seeing3Dchairs,15,2019-01-02 -Deep One-Class Classification,http://proceedings.mlr.press/v80/ruff18a.html,ICML,2018,https://github.com/lukasruff/Deep-SVDD,34,2019-01-02 -Coded Sparse Matrix Multiplication,http://proceedings.mlr.press/v80/wang18e.html,ICML,2018,https://github.com/ksopyla/CudaDotProd,16,2019-01-02 -Product Sparse Coding,http://openaccess.thecvf.com/content_cvpr_2014/html/Ge_Product_Sparse_Coding_2014_CVPR_paper.html,CVPR,2014,https://github.com/ksopyla/CudaDotProd,16,2019-01-02 -Learning Descriptor Networks for 3D Shape Synthesis and Analysis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xie_Learning_Descriptor_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jianwen-xie/3DDescriptorNet,19,2019-01-02 -Automatic Discovery of the Statistical Types of Variables in a Dataset,http://proceedings.mlr.press/v70/valera17a.html,ICML,2017,https://github.com/ivaleraM/DataTypes,15,2019-01-02 -3D Object Reconstruction From Hand-Object Interactions,http://openaccess.thecvf.com/content_iccv_2015/html/Tzionas_3D_Object_Reconstruction_ICCV_2015_paper.html,ICCV,2015,https://github.com/dimtziwnas/InHandScanningICCV15_Reconstruction,15,2019-01-02 -Structure From Motion With Objects,http://openaccess.thecvf.com/content_cvpr_2016/html/Crocco_Structure_From_Motion_CVPR_2016_paper.html,CVPR,2016,https://github.com/danylaksono/Android-SfM-client,17,2019-01-02 -EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth From Light Field Images,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shin_EPINET_A_Fully-Convolutional_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chshin10/epinet,18,2019-01-02 -Deep Learning with Topological Signatures,http://papers.nips.cc/paper/6761-deep-learning-with-topological-signatures.pdf,NIPS,2017,https://github.com/c-hofer/nips2017,17,2019-01-02 -Conditional Image-Text Embedding Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Bryan_Plummer_Conditional_Image-Text_Embedding_ECCV_2018_paper.html,ECCV,2018,https://github.com/BryanPlummer/cite,18,2019-01-02 -Functional Gradient Boosting based on Residual Network Perception,http://proceedings.mlr.press/v80/nitanda18a.html,ICML,2018,https://github.com/anitan0925/ResFGB,16,2019-01-02 -Deep Multitask Architecture for Integrated 2D and 3D Human Sensing,http://openaccess.thecvf.com/content_cvpr_2017/html/Popa_Deep_Multitask_Architecture_CVPR_2017_paper.html,CVPR,2017,https://github.com/alinionutpopa/dmhs,16,2019-01-02 -Action Sets: Weakly Supervised Action Segmentation Without Ordering Constraints,http://openaccess.thecvf.com/content_cvpr_2018/papers/Richard_Action_Sets_Weakly_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/alexanderrichard/action-sets,14,2019-01-02 -Grounding Referring Expressions in Images by Variational Context,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Grounding_Referring_Expressions_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yuleiniu/vc,15,2019-01-02 -Automatic Spatially-Aware Fashion Concept Discovery,http://openaccess.thecvf.com/content_iccv_2017/html/Han_Automatic_Spatially-Aware_Fashion_ICCV_2017_paper.html,ICCV,2017,https://github.com/xthan/fashion-200k,20,2019-01-02 -Single-Image Crowd Counting via Multi-Column Convolutional Neural Network,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Single-Image_Crowd_Counting_CVPR_2016_paper.html,CVPR,2016,https://github.com/uestcchicken/crowd-counting-MCNN,19,2019-01-02 -Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems,http://openaccess.thecvf.com/content_iccv_2017/html/Meinhardt_Learning_Proximal_Operators_ICCV_2017_paper.html,ICCV,2017,https://github.com/tum-vision/learn_prox_ops,15,2019-01-02 -A Spectral Approach to Gradient Estimation for Implicit Distributions,http://proceedings.mlr.press/v80/shi18a.html,ICML,2018,https://github.com/thjashin/spectral-stein-grad,17,2019-01-02 -Toward Characteristic-Preserving Image-based Virtual Try-On Network,http://openaccess.thecvf.com/content_ECCV_2018/html/Bochao_Wang_Toward_Characteristic-Preserving_Image-based_ECCV_2018_paper.html,ECCV,2018,https://github.com/sergeywong/cp-vton,29,2019-01-02 -Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cui_Large_Scale_Fine-Grained_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/richardaecn/cvpr18-inaturalist-transfer,31,2019-01-02 -Weakly- and Semi-Supervised Panoptic Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Anurag_Arnab_Weakly-_and_Semi-Supervised_ECCV_2018_paper.html,ECCV,2018,https://github.com/qizhuli/Weakly-Supervised-Panoptic-Segmentation,46,2019-01-02 -Quantized Convolutional Neural Networks for Mobile Devices,http://openaccess.thecvf.com/content_cvpr_2016/html/Wu_Quantized_Convolutional_Neural_CVPR_2016_paper.html,CVPR,2016,https://github.com/OluwoleOyetoke/Computer_Vision_Using_TensorFlowLite,20,2019-01-02 -Fully-Adaptive Feature Sharing in Multi-Task Networks With Applications in Person Attribute Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Lu_Fully-Adaptive_Feature_Sharing_CVPR_2017_paper.html,CVPR,2017,https://github.com/luyongxi/deep_share,19,2019-01-02 -StyleBank: An Explicit Representation for Neural Image Style Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_StyleBank_An_Explicit_CVPR_2017_paper.html,CVPR,2017,https://github.com/jxcodetw/Stylebank,16,2019-01-02 -ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_ISTA-Net_Interpretable_Optimization-Inspired_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jianzhangcs/ISTA-Net,22,2019-01-02 -Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes,http://openaccess.thecvf.com/content_cvpr_2017/html/Golestaneh_Spatially-Varying_Blur_Detection_CVPR_2017_paper.html,CVPR,2017,https://github.com/isalirezag/HiFST,16,2019-01-02 -Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition,http://openaccess.thecvf.com/content_ECCV_2018/html/Huang_Predicting_Gaze_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/hyf015/egocentric-gaze-prediction,16,2019-01-02 -Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation,http://openaccess.thecvf.com/content_ECCV_2018/html/Helge_Rhodin_Unsupervised_Geometry-Aware_Representation_ECCV_2018_paper.html,ECCV,2018,https://github.com/hrhodin/UnsupervisedGeometryAwareRepresentationLearning,37,2019-01-02 -RoomNet: End-To-End Room Layout Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Lee_RoomNet_End-To-End_Room_ICCV_2017_paper.html,ICCV,2017,https://github.com/GitBoSun/roomnet,17,2019-01-02 -Federated Multi-Task Learning,http://papers.nips.cc/paper/7029-federated-multi-task-learning.pdf,NIPS,2017,https://github.com/gingsmith/fmtl,16,2019-01-02 -Revisiting Deep Intrinsic Image Decompositions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Fan_Revisiting_Deep_Intrinsic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/fqnchina/IntrinsicImage,17,2019-01-02 -Few-Shot Learning Through an Information Retrieval Lens,http://papers.nips.cc/paper/6820-few-shot-learning-through-an-information-retrieval-lens.pdf,NIPS,2017,https://github.com/eleniTriantafillou/few_shot_mAP_public,16,2019-01-02 -Learning Temporal Embeddings for Complex Video Analysis,http://openaccess.thecvf.com/content_iccv_2015/html/Ramanathan_Learning_Temporal_Embeddings_ICCV_2015_paper.html,ICCV,2015,https://github.com/eevignesh/videovector,14,2019-01-02 -Streaming Weak Submodularity: Interpreting Neural Networks on the Fly,http://papers.nips.cc/paper/6993-streaming-weak-submodularity-interpreting-neural-networks-on-the-fly.pdf,NIPS,2017,https://github.com/eelenberg/streak,14,2019-01-02 -Structure-Measure: A New Way to Evaluate Foreground Maps,http://openaccess.thecvf.com/content_iccv_2017/html/Fan_Structure-Measure_A_New_ICCV_2017_paper.html,ICCV,2017,https://github.com/DengPingFan/S-measure,15,2019-01-02 -Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Stacked_Conditional_Generative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/DeepInsight-PCALab/ST-CGAN,20,2019-01-02 -Structured Feature Selection,http://openaccess.thecvf.com/content_iccv_2015/html/Gao_Structured_Feature_Selection_ICCV_2015_paper.html,ICCV,2015,https://github.com/csliangdu/FSASL,17,2019-01-02 -Convolutional Sequence to Sequence Model for Human Dynamics,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Convolutional_Sequence_to_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chaneyddtt/Convolutional-Sequence-to-Sequence-Model-for-Human-Dynamics,15,2019-01-02 -Bayesian Optimization of Combinatorial Structures,http://proceedings.mlr.press/v80/baptista18a.html,ICML,2018,https://github.com/baptistar/BOCS,18,2019-01-02 -Off-policy evaluation for slate recommendation,http://papers.nips.cc/paper/6954-off-policy-evaluation-for-slate-recommendation.pdf,NIPS,2017,https://github.com/adith387/slates_semisynth_expts,15,2019-01-02 -Interactive Segmentation on RGBD Images via Cue Selection,http://openaccess.thecvf.com/content_cvpr_2016/html/Feng_Interactive_Segmentation_on_CVPR_2016_paper.html,CVPR,2016,https://github.com/ZVsion/rgbd_image_segmentation,14,2019-01-02 -Weakly Supervised Affordance Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Sawatzky_Weakly_Supervised_Affordance_CVPR_2017_paper.html,CVPR,2017,https://github.com/ykztawas/Weakly-Supervised-Affordance-Detection,13,2019-01-02 -3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration,http://openaccess.thecvf.com/content_ECCV_2018/html/Zi_Jian_Yew_3DFeat-Net_Weakly_Supervised_ECCV_2018_paper.html,ECCV,2018,https://github.com/yewzijian/3DFeatNet,27,2019-01-02 -Towards Human-Machine Cooperation: Self-Supervised Sample Mining for Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Towards_Human-Machine_Cooperation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yanxp/SSM,13,2019-01-02 -Captioning Images With Diverse Objects,http://openaccess.thecvf.com/content_cvpr_2017/html/Venugopalan_Captioning_Images_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/vsubhashini/noc,15,2019-01-02 -NAG: Network for Adversary Generation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mopuri_NAG_Network_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/val-iisc/nag,16,2019-01-02 -Variational Dropout Sparsifies Deep Neural Networks,http://proceedings.mlr.press/v70/molchanov17a.html,ICML,2017,https://github.com/soskek/variational_dropout_sparsifies_dnn,15,2019-01-02 -Fast Video Object Segmentation by Reference-Guided Mask Propagation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Oh_Fast_Video_Object_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/seoungwugoh/RGMP,27,2019-01-02 -Oriented Edge Forests for Boundary Detection,http://openaccess.thecvf.com/content_cvpr_2015/html/Hallman_Oriented_Edge_Forests_2015_CVPR_paper.html,CVPR,2015,https://github.com/samhallman/oef,13,2019-01-02 -Learning to See by Moving,http://openaccess.thecvf.com/content_iccv_2015/html/Agrawal_Learning_to_See_ICCV_2015_paper.html,ICCV,2015,https://github.com/pulkitag/learning-to-see-by-moving,14,2019-01-02 -Multi-Scale Weighted Nuclear Norm Image Restoration,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yair_Multi-Scale_Weighted_Nuclear_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/noamyairTC/MSWNNM,14,2019-01-02 -"Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies",http://openaccess.thecvf.com/content_cvpr_2018/papers/Joo_Total_Capture_A_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Myzhencai/Total-Capture,17,2019-01-02 -Recurrent 3D Pose Sequence Machines,http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Recurrent_3D_Pose_CVPR_2017_paper.html,CVPR,2017,https://github.com/MudeLin/RPSM,15,2019-01-02 -Hierarchical Relational Networks for Group Activity Recognition and Retrieval,http://openaccess.thecvf.com/content_ECCV_2018/html/Mostafa_Ibrahim_Hierarchical_Relational_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/mostafa-saad/hierarchical-relational-network,22,2019-01-02 -Collaborative and Adversarial Network for Unsupervised Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Collaborative_and_Adversarial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mahfuj9346449/iCAN,22,2019-01-02 -Wasserstein Generative Adversarial Networks,http://proceedings.mlr.press/v70/arjovsky17a.html,ICML,2017,https://github.com/luslab/scRNAseq-WGAN-GP,15,2019-01-02 -ReconNet: Non-Iterative Reconstruction of Images From Compressively Sensed Measurements,http://openaccess.thecvf.com/content_cvpr_2016/html/Kulkarni_ReconNet_Non-Iterative_Reconstruction_CVPR_2016_paper.html,CVPR,2016,https://github.com/KuldeepKulkarni/ReconNet,15,2019-01-02 -Adversarial Attack on Graph Structured Data,http://proceedings.mlr.press/v80/dai18b.html,ICML,2018,https://github.com/Hanjun-Dai/graph_adversarial_attack,17,2019-01-02 -To Trust Or Not To Trust A Classifier,http://arxiv.org/abs/1805.11783v1,NIPS,2018,https://github.com/google/TrustScore,23,2019-01-02 -Efficient Neural Audio Synthesis,http://proceedings.mlr.press/v80/kalchbrenner18a.html,ICML,2018,https://github.com/fedden/TensorFlow-Efficient-Neural-Audio-Synthesis,15,2019-01-02 -Visual Coreference Resolution in Visual Dialog using Neural Module Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Satwik_Kottur_Visual_Coreference_Resolution_ECCV_2018_paper.html,ECCV,2018,https://github.com/facebookresearch/corefnmn,25,2019-01-02 -"ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events",http://papers.nips.cc/paper/6932-extremeweather-a-large-scale-climate-dataset-for-semi-supervised-detection-localization-and-understanding-of-extreme-weather-events.pdf,NIPS,2017,https://github.com/eracah/hur-detect,13,2019-01-02 -Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach,http://papers.nips.cc/paper/7023-estimating-accuracy-from-unlabeled-data-a-probabilistic-logic-approach.pdf,NIPS,2017,https://github.com/eaplatanios/makina,16,2019-01-02 -Spherical convolutions and their application in molecular modelling,http://papers.nips.cc/paper/6935-spherical-convolutions-and-their-application-in-molecular-modelling.pdf,NIPS,2017,https://github.com/deepfold/NIPS2017,14,2019-01-02 -Multi-Information Source Optimization,http://papers.nips.cc/paper/7016-multi-information-source-optimization.pdf,NIPS,2017,https://github.com/deepfold/NIPS2017,14,2019-01-02 -Learning 3D Shape Completion From Laser Scan Data With Weak Supervision,http://openaccess.thecvf.com/content_cvpr_2018/papers/Stutz_Learning_3D_Shape_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/davidstutz/cvpr2018-shape-completion,17,2019-01-02 -VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation,http://openaccess.thecvf.com/content_iccv_2017/html/Gan_VQS_Linking_Segmentations_ICCV_2017_paper.html,ICCV,2017,https://github.com/Cold-Winter/vqs,14,2019-01-02 -Neural Face Editing With Intrinsic Image Disentangling,http://openaccess.thecvf.com/content_cvpr_2017/html/Shu_Neural_Face_Editing_CVPR_2017_paper.html,CVPR,2017,https://github.com/zhixinshu/NeuralFaceEditing,14,2019-01-02 -Convexified Convolutional Neural Networks,http://proceedings.mlr.press/v70/zhang17f.html,ICML,2017,https://github.com/zhangyuc/CCNN,12,2019-01-02 -Adversarial Complementary Learning for Weakly Supervised Object Localization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Adversarial_Complementary_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xiaomengyc/ACoL,39,2019-01-02 -Awesome Typography: Statistics-Based Text Effects Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Awesome_Typography_Statistics-Based_CVPR_2017_paper.html,CVPR,2017,https://github.com/williamyang1991/Text-Effects-Transfer,17,2019-01-02 -"Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs",http://papers.nips.cc/paper/6614-hunt-for-the-unique-stable-sparse-and-fast-feature-learning-on-graphs.pdf,NIPS,2017,https://github.com/vermaMachineLearning/FGSD,13,2019-01-02 -Consensus Convolutional Sparse Coding,http://openaccess.thecvf.com/content_iccv_2017/html/Choudhury_Consensus_Convolutional_Sparse_ICCV_2017_paper.html,ICCV,2017,https://github.com/vccimaging/CCSC_code_ICCV2017,13,2019-01-02 -Reflection Removal Using Ghosting Cues,http://openaccess.thecvf.com/content_cvpr_2015/html/Shih_Reflection_Removal_Using_2015_CVPR_paper.html,CVPR,2015,https://github.com/thongnguyendev/single_image,14,2019-01-02 -Streaming Sparse Gaussian Process Approximations,http://papers.nips.cc/paper/6922-streaming-sparse-gaussian-process-approximations.pdf,NIPS,2017,https://github.com/thangbui/streaming_sparse_gp,17,2019-01-02 -Image Transformer,http://proceedings.mlr.press/v80/parmar18a.html,ICML,2018,https://github.com/ssingal05/ImageTransformer,14,2019-01-02 -Semantic Filtering,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Semantic_Filtering_CVPR_2016_paper.html,CVPR,2016,https://github.com/shenshen-hungry/Semantic-CNN,16,2019-01-02 -Objects that Sound,http://openaccess.thecvf.com/content_ECCV_2018/html/Relja_Arandjelovic_Objects_that_Sound_ECCV_2018_paper.html,ECCV,2018,https://github.com/rohitrango/objects-that-sound,20,2019-01-02 -Arbitrary Style Transfer With Deep Feature Reshuffle,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gu_Arbitrary_Style_Transfer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/msracver/Style-Feature-Reshuffle,17,2019-01-02 -StoryGraphs: Visualizing Character Interactions as a Timeline,http://openaccess.thecvf.com/content_cvpr_2014/html/Tapaswi_StoryGraphs_Visualizing_Character_2014_CVPR_paper.html,CVPR,2014,https://github.com/makarandtapaswi/StoryGraphs_CVPR2014,14,2019-01-02 -Deep Supervised Discrete Hashing,http://papers.nips.cc/paper/6842-deep-supervised-discrete-hashing.pdf,NIPS,2017,https://github.com/liqi-casia/DSDH-HashingCode,16,2019-01-02 -Convolutional Neural Networks for No-Reference Image Quality Assessment,http://openaccess.thecvf.com/content_cvpr_2014/html/Kang_Convolutional_Neural_Networks_2014_CVPR_paper.html,CVPR,2014,https://github.com/lidq92/CNNIQA,16,2019-01-02 -Realistic Dynamic Facial Textures From a Single Image Using GANs,http://openaccess.thecvf.com/content_iccv_2017/html/Olszewski_Realistic_Dynamic_Facial_ICCV_2017_paper.html,ICCV,2017,https://github.com/leehomyc/ICCV-2017-Paper,14,2019-01-02 -Unrolled Memory Inner-Products: An Abstract GPU Operator for Efficient Vision-Related Computations,http://openaccess.thecvf.com/content_iccv_2017/html/Lin_Unrolled_Memory_Inner-Products_ICCV_2017_paper.html,ICCV,2017,https://github.com/johnjohnlin/UMI,12,2019-01-02 -CTAP: Complementary Temporal Action Proposal Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Jiyang_Gao_CTAP_Complementary_Temporal_ECCV_2018_paper.html,ECCV,2018,https://github.com/jiyanggao/CTAP,18,2019-01-02 -Deep Cross-Modal Hashing,http://openaccess.thecvf.com/content_cvpr_2017/html/Jiang_Deep_Cross-Modal_Hashing_CVPR_2017_paper.html,CVPR,2017,https://github.com/jiangqy/DCMH-CVPR2017,22,2019-01-02 -Coordinated Multi-Agent Imitation Learning,http://proceedings.mlr.press/v70/le17a.html,ICML,2017,https://github.com/hoangminhle/MultiAgent-ImitationLearning,12,2019-01-02 -Convolutional Neural Network Architecture for Geometric Matching,http://openaccess.thecvf.com/content_cvpr_2017/html/Rocco_Convolutional_Neural_Network_CVPR_2017_paper.html,CVPR,2017,https://github.com/hjweide/convnet-for-geometric-matching,14,2019-01-02 -Parallax-tolerant Image Stitching,http://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Parallax-tolerant_Image_Stitching_2014_CVPR_paper.html,CVPR,2014,https://github.com/gain2217/Robust_Elastic_Warping,20,2019-01-02 -Decouple Learning for Parameterized Image Operators,http://openaccess.thecvf.com/content_ECCV_2018/html/Qingnan_Fan_Learning_to_Learn_ECCV_2018_paper.html,ECCV,2018,https://github.com/fqnchina/DecoupleLearning,12,2019-01-02 -Local Spectral Graph Convolution for Point Set Feature Learning,http://openaccess.thecvf.com/content_ECCV_2018/html/Chu_Wang_Local_Spectral_Graph_ECCV_2018_paper.html,ECCV,2018,https://github.com/fate3439/LocalSpecGCN,21,2019-01-02 -Low-Shot Learning With Large-Scale Diffusion,http://openaccess.thecvf.com/content_cvpr_2018/papers/Douze_Low-Shot_Learning_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/facebookresearch/low-shot-with-diffusion,19,2019-01-02 -Glimpse Clouds: Human Activity Recognition From Unstructured Feature Points,http://openaccess.thecvf.com/content_cvpr_2018/papers/Baradel_Glimpse_Clouds_Human_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/fabienbaradel/glimpse_clouds,18,2019-01-02 -Learning and Using the Arrow of Time,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wei_Learning_and_Using_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/donglaiw/AoT_TCAM,14,2019-01-02 -Nonparametric Part Transfer for Fine-grained Recognition,http://openaccess.thecvf.com/content_cvpr_2014/html/Goring_Nonparametric_Part_Transfer_2014_CVPR_paper.html,CVPR,2014,https://github.com/cvjena/finegrained-cvpr2014,13,2019-01-02 -Multigrid Neural Architectures,http://openaccess.thecvf.com/content_cvpr_2017/html/Ke_Multigrid_Neural_Architectures_CVPR_2017_paper.html,CVPR,2017,https://github.com/buttomnutstoast/Multigrid-Neural-Architectures,12,2019-01-02 -Attributes2Classname: A Discriminative Model for Attribute-Based Unsupervised Zero-Shot Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Demirel_Attributes2Classname_A_Discriminative_ICCV_2017_paper.html,ICCV,2017,https://github.com/berkandemirel/attributes2classname,14,2019-01-02 -Gesture Recognition: Focus on the Hands,http://openaccess.thecvf.com/content_cvpr_2018/papers/Narayana_Gesture_Recognition_Focus_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/beckabec/HandDetection,12,2019-01-02 -IM2CAD,http://openaccess.thecvf.com/content_cvpr_2017/html/Izadinia_IM2CAD_CVPR_2017_paper.html,CVPR,2017,https://github.com/yyong119/IM2CAD,11,2019-01-02 -Deep Spatial-Semantic Attention for Fine-Grained Sketch-Based Image Retrieval,http://openaccess.thecvf.com/content_iccv_2017/html/Song_Deep_Spatial-Semantic_Attention_ICCV_2017_paper.html,ICCV,2017,https://github.com/yuchuochuo1023/Deep_SBIR_tf,16,2019-01-02 -Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace,http://proceedings.mlr.press/v80/lee18a.html,ICML,2018,https://github.com/yoonholee/MT-net,13,2019-01-02 -Min-Entropy Latent Model for Weakly Supervised Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wan_Min-Entropy_Latent_Model_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Winfrand/MELM,13,2019-01-02 -Joint Learning of Object and Action Detectors,http://openaccess.thecvf.com/content_iccv_2017/html/Kalogeiton_Joint_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/vkalogeiton/joint-object-action-learning,13,2019-01-02 -Generalized Deep Image to Image Regression,http://openaccess.thecvf.com/content_cvpr_2017/html/Santhanam_Generalized_Deep_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/venkai/RBDN,11,2019-01-02 -HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_HashGAN_Deep_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/thuml/HashGAN,22,2019-01-02 -Future Person Localization in First-Person Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yagi_Future_Person_Localization_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/takumayagi/fpl,12,2019-01-02 -Sliced Wasserstein Distance for Learning Gaussian Mixture Models,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kolouri_Sliced_Wasserstein_Distance_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/skolouri/swgmm,17,2019-01-02 -Light Field Blind Motion Deblurring,http://openaccess.thecvf.com/content_cvpr_2017/html/Srinivasan_Light_Field_Blind_CVPR_2017_paper.html,CVPR,2017,https://github.com/pratulsrinivasan/Light_Field_Blind_Motion_Deblurring,13,2019-01-02 -Hierarchical Multi-Label Classification Networks,http://proceedings.mlr.press/v80/wehrmann18a.html,ICML,2018,https://github.com/omoju/receiptdID,11,2019-01-02 -Neural Sign Language Translation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Camgoz_Neural_Sign_Language_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/neccam/nslt,15,2019-01-02 -Scalable Multitask Representation Learning for Scene Classification,http://openaccess.thecvf.com/content_cvpr_2014/html/Lapin_Scalable_Multitask_Representation_2014_CVPR_paper.html,CVPR,2014,https://github.com/mlapin/cvpr14mtl,11,2019-01-02 -Asynchronous Stochastic Gradient Descent with Delay Compensation,http://proceedings.mlr.press/v70/zheng17b.html,ICML,2017,https://github.com/Microsoft/Delayed-Compensation-Asynchronous-Stochastic-Gradient-Descent-for-Multiverso,13,2019-01-02 -Learning Rich Features for Image Manipulation Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Learning_Rich_Features_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/LarryJiang134/Image_manipulation_detection,27,2019-01-02 -Hierarchical Novelty Detection for Visual Object Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_Hierarchical_Novelty_Detection_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kibok90/cvpr2018-hnd,17,2019-01-02 -Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification,http://papers.nips.cc/paper/7125-maximizing-subset-accuracy-with-recurrent-neural-networks-in-multi-label-classification.pdf,NIPS,2017,https://github.com/JinseokNam/mlc2seq,12,2019-01-02 -Differential Angular Imaging for Material Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Xue_Differential_Angular_Imaging_CVPR_2017_paper.html,CVPR,2017,https://github.com/jiaxue1993/DAIN,12,2019-01-02 -Where to Buy It: Matching Street Clothing Photos in Online Shops,http://openaccess.thecvf.com/content_iccv_2015/html/Kiapour_Where_to_Buy_ICCV_2015_paper.html,ICCV,2015,https://github.com/jfuentescpp/where_to_buy_it,14,2019-01-02 -On Fairness and Calibration,http://papers.nips.cc/paper/7151-on-fairness-and-calibration.pdf,NIPS,2017,https://github.com/gpleiss/equalized_odds_and_calibration,11,2019-01-02 -Learning to Forecast and Refine Residual Motion for Image-to-Video Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Long_Zhao_Learning_to_Forecast_ECCV_2018_paper.html,ECCV,2018,https://github.com/garyzhao/FRGAN,14,2019-01-02 -Convolutional Image Captioning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Aneja_Convolutional_Image_Captioning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/eladhoffer/captionGeneration.torch,11,2019-01-02 -Deep Expander Networks: Efficient Deep Networks from Graph Theory,http://openaccess.thecvf.com/content_ECCV_2018/html/Ameya_Prabhu_Deep_Expander_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/DrImpossible/Deep-Expander-Networks,19,2019-01-02 -From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur,http://openaccess.thecvf.com/content_cvpr_2017/html/Gong_From_Motion_Blur_CVPR_2017_paper.html,CVPR,2017,https://github.com/donggong1/motion-flow-syn,20,2019-01-02 -Face Aging With Identity-Preserved Conditional Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Face_Aging_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/dawei6875797/Face-Aging-with-Identity-Preserved-Conditional-Generative-Adversarial-Networks,23,2019-01-02 -Similarity Learning With Spatial Constraints for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Similarity_Learning_With_CVPR_2016_paper.html,CVPR,2016,https://github.com/dapengchen123/SCSP,11,2019-01-02 -Joint Optimization Framework for Learning With Noisy Labels,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tanaka_Joint_Optimization_Framework_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/DaikiTanaka-UT/JointOptimization,12,2019-01-02 -Predictive State Recurrent Neural Networks,http://papers.nips.cc/paper/7186-predictive-state-recurrent-neural-networks.pdf,NIPS,2017,https://github.com/cmdowney/psrnn,13,2019-01-02 -A Large-Scale Car Dataset for Fine-Grained Categorization and Verification,http://openaccess.thecvf.com/content_cvpr_2015/html/Yang_A_Large-Scale_Car_2015_CVPR_paper.html,CVPR,2015,https://github.com/bogger/caffe-multigpu,11,2019-01-02 -Dynamic Multimodal Instance Segmentation Guided by Natural Language Queries,http://openaccess.thecvf.com/content_ECCV_2018/html/Edgar_Margffoy-Tuay_Dynamic_Multimodal_Instance_ECCV_2018_paper.html,ECCV,2018,https://github.com/BCV-Uniandes/query-objseg,25,2019-01-02 -Learning Transferable Architectures for Scalable Image Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zoph_Learning_Transferable_Architectures_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/aussetg/nasnet.pytorch,12,2019-01-02 -Learning Conditioned Graph Structures for Interpretable Visual Question Answering,,NIPS,2018,https://github.com/aimbrain/vqa-project,57,2019-01-02 -Learning Diverse Image Colorization,http://openaccess.thecvf.com/content_cvpr_2017/html/Deshpande_Learning_Diverse_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/aditya12agd5/divcolor,15,2019-01-02 -Open Set Domain Adaptation by Backpropagation,http://openaccess.thecvf.com/content_ECCV_2018/html/Kuniaki_Saito_Adversarial_Open_Set_ECCV_2018_paper.html,ECCV,2018,https://github.com/YU1ut/openset-DA,15,2019-01-02 -Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks,https://arxiv.org/abs/1802.04034,NIPS,2018,https://github.com/ytsmiling/lmt,16,2019-01-02 -Mix and Match Networks: Encoder-Decoder Alignment for Zero-Pair Image Translation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Mix_and_Match_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yaxingwang/Mix-and-match-networks,12,2019-01-02 -Learning by Asking Questions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Misra_Learning_by_Asking_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yanghoonkim/question_generation,13,2019-01-02 -DESIRE: Distant Future Prediction in Dynamic Scenes With Interacting Agents,http://openaccess.thecvf.com/content_cvpr_2017/html/Lee_DESIRE_Distant_Future_CVPR_2017_paper.html,CVPR,2017,https://github.com/yadrimz/DESIRE,11,2019-01-02 -Densely Connected Attention Propagation for Reading Comprehension,https://nips.cc/Conferences/2018/Schedule?showEvent=11481,NIPS,2018,https://github.com/vanzytay/NIPS2018_DECAPROP,30,2019-01-02 -VegFru: A Domain-Specific Dataset for Fine-Grained Visual Categorization,http://openaccess.thecvf.com/content_iccv_2017/html/Hou_VegFru_A_Domain-Specific_ICCV_2017_paper.html,ICCV,2017,https://github.com/ustc-vim/vegfru,12,2019-01-02 -Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction,http://proceedings.mlr.press/v80/qi18a.html,ICML,2018,https://github.com/SiyuanQi/generalized-earley-parser,12,2019-01-02 -Multimodal Explanations: Justifying Decisions and Pointing to the Evidence,http://openaccess.thecvf.com/content_cvpr_2018/papers/Park_Multimodal_Explanations_Justifying_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Seth-Park/MultimodalExplanations,11,2019-01-02 -Pose Proposal Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Sekii_Pose_Proposal_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/salihkaragoz/MultiPerson-pose-estimation,15,2019-01-02 -Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory,http://proceedings.mlr.press/v80/amit18a.html,ICML,2018,https://github.com/ron-amit/meta-learning-adjusting-priors,11,2019-01-02 -f-GANs in an Information Geometric Nutshell,http://papers.nips.cc/paper/6649-f-gans-in-an-information-geometric-nutshell.pdf,NIPS,2017,https://github.com/qulizhen/fgan_info_geometric,10,2019-01-02 -Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin,http://papers.nips.cc/paper/7255-attend-and-predict-understanding-gene-regulation-by-selective-attention-on-chromatin.pdf,NIPS,2017,https://github.com/QData/AttentiveChrome,12,2019-01-02 -Adversarial Time-to-Event Modeling,http://proceedings.mlr.press/v80/chapfuwa18a.html,ICML,2018,https://github.com/paidamoyo/adversarial_time_to_event,12,2019-01-02 -Anonymous Walk Embeddings,http://proceedings.mlr.press/v80/ivanov18a.html,ICML,2018,https://github.com/nd7141/AWE,22,2019-01-02 -Learning Type-Aware Embeddings for Fashion Compatibility,http://openaccess.thecvf.com/content_ECCV_2018/html/Mariya_Vasileva_Learning_Type-Aware_Embeddings_ECCV_2018_paper.html,ECCV,2018,https://github.com/mvasil/fashion-compatibility,17,2019-01-02 -Learning to Understand Image Blur,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Learning_to_Understand_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Lotuslisa/Understand_Image_Blur,14,2019-01-02 -Scalable Log Determinants for Gaussian Process Kernel Learning,http://papers.nips.cc/paper/7212-scalable-log-determinants-for-gaussian-process-kernel-learning.pdf,NIPS,2017,https://github.com/kd383/GPML_SLD,9,2019-01-02 -Personalizing Human Video Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2016/html/Charles_Personalizing_Human_Video_CVPR_2016_paper.html,CVPR,2016,https://github.com/jjcharles/personalized_pose,10,2019-01-02 -High-Order Attention Models for Visual Question Answering,http://papers.nips.cc/paper/6957-high-order-attention-models-for-visual-question-answering.pdf,NIPS,2017,https://github.com/idansc/HighOrderAtten,11,2019-01-02 -Learned Contextual Feature Reweighting for Image Geo-Localization,http://openaccess.thecvf.com/content_cvpr_2017/html/Kim_Learned_Contextual_Feature_CVPR_2017_paper.html,CVPR,2017,https://github.com/hyojinie/crn,14,2019-01-02 -AON: Towards Arbitrarily-Oriented Text Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cheng_AON_Towards_Arbitrarily-Oriented_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/huizhang0110/AON,26,2019-01-02 -Joint Pose and Expression Modeling for Facial Expression Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Joint_Pose_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/FFZhang1231/Facial-expression-recognition,15,2019-01-02 -Accelerating Natural Gradient with Higher-Order Invariance,http://proceedings.mlr.press/v80/song18a.html,ICML,2018,https://github.com/ermongroup/higher_order_invariance,11,2019-01-02 -Fully-Convolutional Point Networks for Large-Scale Point Clouds,http://openaccess.thecvf.com/content_ECCV_2018/html/Dario_Rethage_Fully-Convolutional_Point_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/drethage/fully-convolutional-point-network,20,2019-01-02 -Learning Cross-Modal Deep Representations for Robust Pedestrian Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Learning_Cross-Modal_Deep_CVPR_2017_paper.html,CVPR,2017,https://github.com/danxuhk/CMT-CNN,10,2019-01-02 -Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective,http://openaccess.thecvf.com/content_iccv_2017/html/Oh_Adversarial_Image_Perturbation_ICCV_2017_paper.html,ICCV,2017,https://github.com/coallaoh/AIP,11,2019-01-02 -Finding Influential Training Samples for Gradient Boosted Decision Trees,http://proceedings.mlr.press/v80/sharchilev18a.html,ICML,2018,https://github.com/bsharchilev/influence_boosting,13,2019-01-02 -Non-Local Deep Features for Salient Object Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Luo_Non-Local_Deep_Features_CVPR_2017_paper.html,CVPR,2017,https://github.com/AceCoooool/NLFD-pytorch,15,2019-01-02 -Max-value Entropy Search for Efficient Bayesian Optimization,http://proceedings.mlr.press/v70/wang17e.html,ICML,2017,https://github.com/zi-w/Max-value-Entropy-Search,11,2019-01-02 -CVAE-GAN: Fine-Grained Image Generation Through Asymmetric Training,http://openaccess.thecvf.com/content_iccv_2017/html/Bao_CVAE-GAN_Fine-Grained_Image_ICCV_2017_paper.html,ICCV,2017,https://github.com/yanzhicong/VAE-GAN,14,2019-01-02 -Removing Rain From Single Images via a Deep Detail Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Fu_Removing_Rain_From_CVPR_2017_paper.html,CVPR,2017,https://github.com/XMU-smartdsp/Removing_Rain,12,2019-01-02 -Learning Superpixels With Segmentation-Aware Affinity Loss,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tu_Learning_Superpixels_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wctu/SEAL,20,2019-01-02 -Surface Normals in the Wild,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Surface_Normals_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/umich-vl/surface_normals,15,2019-01-02 -Appearance-Based Gaze Estimation in the Wild,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Appearance-Based_Gaze_Estimation_2015_CVPR_paper.html,CVPR,2015,https://github.com/trakaros/MPIIGaze,10,2019-01-02 -Fisher GAN,http://papers.nips.cc/paper/6845-fisher-gan.pdf,NIPS,2017,https://github.com/tomsercu/FisherGAN,11,2019-01-02 -Practical Data-Dependent Metric Compression with Provable Guarantees,http://papers.nips.cc/paper/6855-practical-data-dependent-metric-compression-with-provable-guarantees.pdf,NIPS,2017,https://github.com/talwagner/quadsketch,9,2019-01-02 -High Quality Structure From Small Motion for Rolling Shutter Cameras,http://openaccess.thecvf.com/content_iccv_2015/html/Im_High_Quality_Structure_ICCV_2015_paper.html,ICCV,2015,https://github.com/sunghoonim/SfSM,9,2019-01-02 -Deep Diffeomorphic Transformer Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Detlefsen_Deep_Diffeomorphic_Transformer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/SkafteNicki/ddtn,13,2019-01-02 -Predicting Human Activities Using Stochastic Grammar,http://openaccess.thecvf.com/content_iccv_2017/html/Qi_Predicting_Human_Activities_ICCV_2017_paper.html,ICCV,2017,https://github.com/SiyuanQi/grammar-activity-prediction,11,2019-01-02 -Synthesizing Robust Adversarial Examples,http://proceedings.mlr.press/v80/athalye18b.html,ICML,2018,https://github.com/prabhant/synthesizing-robust-adversarial-examples,13,2019-01-02 -Learning Motion Patterns in Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Tokmakov_Learning_Motion_Patterns_CVPR_2017_paper.html,CVPR,2017,https://github.com/pirahansiah/opencv,9,2019-01-02 -AMNet: Memorability Estimation With Attention,http://openaccess.thecvf.com/content_cvpr_2018/papers/Fajtl_AMNet_Memorability_Estimation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ok1zjf/AMNet,12,2019-01-02 -Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models,https://arxiv.org/abs/1808.04768,NIPS,2018,https://github.com/neitzal/adaptive-skip-intervals,12,2019-01-02 -Learning a Discriminative Feature Network for Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Learning_a_Discriminative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lxtGH/dfn_seg,26,2019-01-02 -Gradient descent GAN optimization is locally stable,http://papers.nips.cc/paper/7142-gradient-descent-gan-optimization-is-locally-stable.pdf,NIPS,2017,https://github.com/locuslab/gradient_regularized_gan,12,2019-01-02 -Hashing as Tie-Aware Learning to Rank,http://openaccess.thecvf.com/content_cvpr_2018/papers/He_Hashing_as_Tie-Aware_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kunhe/TALR,15,2019-01-02 -Visually Indicated Sounds,http://openaccess.thecvf.com/content_cvpr_2016/html/Owens_Visually_Indicated_Sounds_CVPR_2016_paper.html,CVPR,2016,https://github.com/kanchen-usc/VIG,9,2019-01-02 -Attentional Correlation Filter Network for Adaptive Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2017/html/Choi_Attentional_Correlation_Filter_CVPR_2017_paper.html,CVPR,2017,https://github.com/jongwon20000/ACFN,10,2019-01-02 -Automatic Content-Aware Color and Tone Stylization,http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Automatic_Content-Aware_Color_CVPR_2016_paper.html,CVPR,2016,https://github.com/jinyu121/ACACTS,12,2019-01-02 -Attention in Convolutional LSTM for Gesture Recognition,https://nips.cc/Conferences/2018/Schedule?showEvent=11207,NIPS,2018,https://github.com/GuangmingZhu/AttentionConvLSTM,32,2019-01-02 -Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization,http://papers.nips.cc/paper/6611-breaking-the-nonsmooth-barrier-a-scalable-parallel-method-for-composite-optimization.pdf,NIPS,2017,https://github.com/fabianp/ProxASAGA,9,2019-01-02 -Rethinking the Form of Latent States in Image Captioning,http://openaccess.thecvf.com/content_ECCV_2018/html/Bo_Dai_Rethinking_the_Form_ECCV_2018_paper.html,ECCV,2018,https://github.com/doubledaibo/2dcaption_eccv2018,15,2019-01-02 -Higher-Order Integration of Hierarchical Convolutional Activations for Fine-Grained Visual Categorization,http://openaccess.thecvf.com/content_iccv_2017/html/Cai_Higher-Order_Integration_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/cssjcai/hihca,11,2019-01-02 -Confident Multiple Choice Learning,http://proceedings.mlr.press/v70/lee17b.html,ICML,2017,https://github.com/chhwang/cmcl,10,2019-01-02 -Do Deep Neural Networks Suffer from Crowding?,http://papers.nips.cc/paper/7146-do-deep-neural-networks-suffer-from-crowding.pdf,NIPS,2017,https://github.com/CBMM/eccentricity,9,2019-01-02 -Robust Image Filtering Using Joint Static and Dynamic Guidance,http://openaccess.thecvf.com/content_cvpr_2015/html/Ham_Robust_Image_Filtering_2015_CVPR_paper.html,CVPR,2015,https://github.com/bsham/SDFilter,10,2019-01-02 -Learning Dynamics of Linear Denoising Autoencoders,http://proceedings.mlr.press/v80/pretorius18a.html,ICML,2018,https://github.com/arnupretorius/lindaedynamics_icml2018,9,2019-01-02 -Variational Autoencoders for Deforming 3D Mesh Models,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tan_Variational_Autoencoders_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/aldehydecho/Mesh-VAE,13,2019-01-02 -Region Ranking SVM for Image Classification,http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Region_Ranking_SVM_CVPR_2016_paper.html,CVPR,2016,https://github.com/zijunwei/Region-Ranking-SVM,8,2019-01-02 -Disentangled Representation Learning GAN for Pose-Invariant Face Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Tran_Disentangled_Representation_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/zhangjunh/DR-GAN-by-pytorch,21,2019-01-02 -A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting,http://openaccess.thecvf.com/content_cvpr_2017/html/Queau_A_Non-Convex_Variational_CVPR_2017_paper.html,CVPR,2017,https://github.com/yqueau/robust_ps,9,2019-01-02 -Online multiclass boosting,http://papers.nips.cc/paper/6693-online-multiclass-boosting.pdf,NIPS,2017,https://github.com/yhjung88/OnlineBoostingWithVFDT,8,2019-01-02 -A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation,https://arxiv.org/abs/1809.01361,NIPS,2018,https://github.com/XenderLiu/UFDN,51,2019-01-02 -Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Anderson_Bottom-Up_and_Top-Down_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Wentong-DST/up-down-captioner,13,2019-01-02 -Salient Object Detection Driven by Fixation Prediction,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Salient_Object_Detection_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wenguanwang/ASNet,9,2019-01-02 -Cost efficient gradient boosting,http://papers.nips.cc/paper/6753-cost-efficient-gradient-boosting.pdf,NIPS,2017,https://github.com/svenpeter42/LightGBM-CEGB,8,2019-01-02 -Excitation Backprop for RNNs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Bargal_Excitation_Backprop_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sbargal/Caffe-ExcitationBP-RNNs,9,2019-01-02 -DeepNav: Learning to Navigate Large Cities,http://openaccess.thecvf.com/content_cvpr_2017/html/Brahmbhatt_DeepNav_Learning_to_CVPR_2017_paper.html,CVPR,2017,https://github.com/samarth-robo/deepnav_cvpr17,8,2019-01-02 -Fast Information-theoretic Bayesian Optimisation,http://proceedings.mlr.press/v80/ru18a.html,ICML,2018,https://github.com/rubinxin/FITBO,8,2019-01-02 -DeepPermNet: Visual Permutation Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Santa_Cruz_DeepPermNet_Visual_Permutation_CVPR_2017_paper.html,CVPR,2017,https://github.com/rfsantacruz/deep-perm-net,10,2019-01-02 -Curriculum Dropout,http://openaccess.thecvf.com/content_iccv_2017/html/Morerio_Curriculum_Dropout_ICCV_2017_paper.html,ICCV,2017,https://github.com/pmorerio/curriculum-dropout,9,2019-01-02 -Input Switched Affine Networks: An RNN Architecture Designed for Interpretability,http://proceedings.mlr.press/v70/foerster17a.html,ICML,2017,https://github.com/philipperemy/tensorflow-isan-rnn,8,2019-01-02 -Deep Variational Reinforcement Learning for POMDPs,http://proceedings.mlr.press/v80/igl18a.html,ICML,2018,https://github.com/oxwhirl/Deep-Variational-Reinforcement-Learning,8,2018-09-16 -Gaze Embeddings for Zero-Shot Image Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Karessli_Gaze_Embeddings_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/Noura-kr/CVPR17,8,2019-01-02 -Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation,http://papers.nips.cc/paper/6821-formal-guarantees-on-the-robustness-of-a-classifier-against-adversarial-manipulation.pdf,NIPS,2017,https://github.com/max-andr/cross-lipschitz,11,2019-01-02 -Boosting Domain Adaptation by Discovering Latent Domains,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mancini_Boosting_Domain_Adaptation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mancinimassimiliano/latent_domains_DA,11,2019-01-02 -Affinity Clustering: Hierarchical Clustering at Scale,http://papers.nips.cc/paper/7262-affinity-clustering-hierarchical-clustering-at-scale.pdf,NIPS,2017,https://github.com/MahsaDerakhshan/AffinityClustering,8,2019-01-02 -Revisiting IM2GPS in the Deep Learning Era,http://openaccess.thecvf.com/content_iccv_2017/html/Vo_Revisiting_IM2GPS_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/lugiavn/revisiting-im2gps,10,2019-01-02 -Partial Person Re-Identification,http://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Partial_Person_Re-Identification_ICCV_2015_paper.html,ICCV,2015,https://github.com/lingxiao-he/Deep-Spatial-Feature-Reconstruction-for-Partial-Person-Re-identification,9,2019-01-02 -Benchmarking Denoising Algorithms With Real Photographs,http://openaccess.thecvf.com/content_cvpr_2017/html/Plotz_Benchmarking_Denoising_Algorithms_CVPR_2017_paper.html,CVPR,2017,https://github.com/lbasek/image-denoising-benchmark,14,2019-01-02 -Cross-View Image Synthesis Using Conditional GANs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Regmi_Cross-View_Image_Synthesis_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kregmi/cross-view-image-synthesis,12,2019-01-02 -Boosting Object Proposals: From Pascal to COCO,http://openaccess.thecvf.com/content_iccv_2015/html/Pont-Tuset_Boosting_Object_Proposals_ICCV_2015_paper.html,ICCV,2015,https://github.com/jponttuset/BOP,8,2019-01-02 -Neural Aggregation Network for Video Face Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Neural_Aggregation_Network_CVPR_2017_paper.html,CVPR,2017,https://github.com/jinyanxu/Neural-Aggregation-Network-for-Video-Face-Recognition,14,2019-01-02 -Unsupervised Learning From Narrated Instruction Videos,http://openaccess.thecvf.com/content_cvpr_2016/html/Alayrac_Unsupervised_Learning_From_CVPR_2016_paper.html,CVPR,2016,https://github.com/jalayrac/instructionVideos,7,2019-01-02 -Introspective Neural Networks for Generative Modeling,http://openaccess.thecvf.com/content_iccv_2017/html/Lazarow_Introspective_Neural_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/intermilan/inng,8,2019-01-02 -A Hierarchical Approach for Generating Descriptive Image Paragraphs,http://openaccess.thecvf.com/content_cvpr_2017/html/Krause_A_Hierarchical_Approach_CVPR_2017_paper.html,CVPR,2017,https://github.com/InnerPeace-Wu/im2p-tensorflow,9,2019-01-02 -Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_a_Discriminative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hubeihubei/DFL-CNN-pytorch,13,2019-01-02 -Recovering 3D Planes from a Single Image via Convolutional Neural Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Fengting_Yang_Recovering_3D_Planes_ECCV_2018_paper.html,ECCV,2018,https://github.com/fuy34/planerecover,16,2019-01-02 -Analyzing Uncertainty in Neural Machine Translation,http://proceedings.mlr.press/v80/ott18a.html,ICML,2018,https://github.com/facebookresearch/analyzing-uncertainty-nmt,9,2019-01-02 -A Multilayer-Based Framework for Online Background Subtraction With Freely Moving Cameras,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_A_Multilayer-Based_Framework_ICCV_2017_paper.html,ICCV,2017,https://github.com/EthanZhu90/MultilayerBSMC_ICCV17,11,2019-01-02 -"Plan, Attend, Generate: Planning for Sequence-to-Sequence Models",http://papers.nips.cc/paper/7131-plan-attend-generate-planning-for-sequence-to-sequence-models.pdf,NIPS,2017,https://github.com/Dutil/PAG,8,2019-01-02 -Unsupervised Learning of Visual Representations Using Videos,http://openaccess.thecvf.com/content_iccv_2015/html/Wang_Unsupervised_Learning_of_ICCV_2015_paper.html,ICCV,2015,https://github.com/coreylynch/unsupervised-triplet-embedding,8,2019-01-02 -Convolutional Channel Features,http://openaccess.thecvf.com/content_iccv_2015/html/Yang_Convolutional_Channel_Features_ICCV_2015_paper.html,ICCV,2015,https://github.com/byangderek/CCF,8,2019-01-02 -Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network,http://openaccess.thecvf.com/content_cvpr_2016/html/Molchanov_Online_Detection_and_CVPR_2016_paper.html,CVPR,2016,https://github.com/breadbread1984/R3DCNN,16,2019-01-02 -Pairwise Matching Through Max-Weight Bipartite Belief Propagation,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Pairwise_Matching_Through_CVPR_2016_paper.html,CVPR,2016,https://github.com/zzhang1987/HungarianBP,8,2019-01-02 -Detecting and Correcting for Label Shift with Black Box Predictors,http://proceedings.mlr.press/v80/lipton18a.html,ICML,2018,https://github.com/zackchase/label-shift,7,2019-01-02 -Attention-Aware Face Hallucination via Deep Reinforcement Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Attention-Aware_Face_Hallucination_CVPR_2017_paper.html,CVPR,2017,https://github.com/ykshi/facehallucination,8,2019-01-02 -Conditional Prior Networks for Optical Flow,http://openaccess.thecvf.com/content_ECCV_2018/html/Yanchao_Yang_Conditional_Prior_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/YanchaoYang/Conditional-Prior-Networks,7,2019-01-02 -Fine-Grained Visual Categorization using Meta-Learning Optimization with Sample Selection of Auxiliary Data,http://openaccess.thecvf.com/content_ECCV_2018/html/Yabin_Zhang_Fine-Grained_Visual_Categorization_ECCV_2018_paper.html,ECCV,2018,https://github.com/YabinZhang1994/MetaFGNet,13,2019-01-02 -Diverse Image Annotation,http://openaccess.thecvf.com/content_cvpr_2017/html/Wu_Diverse_Image_Annotation_CVPR_2017_paper.html,CVPR,2017,https://github.com/wubaoyuan/DIA,6,2019-01-02 -Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images,http://openaccess.thecvf.com/content_iccv_2017/html/Orekondy_Towards_a_Visual_ICCV_2017_paper.html,ICCV,2017,https://github.com/tribhuvanesh/vpa,8,2019-01-02 -Live Repetition Counting,http://openaccess.thecvf.com/content_iccv_2015/html/Levy_Live_Repetition_Counting_ICCV_2015_paper.html,ICCV,2015,https://github.com/tomrunia/DeepRepICCV2015,8,2019-01-02 -Reflectance Adaptive Filtering Improves Intrinsic Image Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Nestmeyer_Reflectance_Adaptive_Filtering_CVPR_2017_paper.html,CVPR,2017,https://github.com/tnestmeyer/reflectance-filtering,8,2019-01-02 -Weakly Supervised Learning of Deep Metrics for Stereo Reconstruction,http://openaccess.thecvf.com/content_iccv_2017/html/Tulyakov_Weakly_Supervised_Learning_ICCV_2017_paper.html,ICCV,2017,https://github.com/tlkvstepan/mc-cnn-ws,7,2019-01-02 -Decoupled Parallel Backpropagation with Convergence Guarantee,http://proceedings.mlr.press/v80/huo18a.html,ICML,2018,https://github.com/slowbull/DDG,9,2019-01-02 -Generative Adversarial Learning Towards Fast Weakly Supervised Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Generative_Adversarial_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shenyunhang/GAL-fWSD,7,2019-01-02 -A Memory Network Approach for Story-Based Temporal Summarization of 360° Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_A_Memory_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sangho-vision/PFMN,6,2019-01-02 -oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis,http://proceedings.mlr.press/v80/ainsworth18a.html,ICML,2018,https://github.com/samuela/oi-vae,9,2019-01-02 -Model-Powered Conditional Independence Test,http://papers.nips.cc/paper/6888-model-powered-conditional-independence-test.pdf,NIPS,2017,https://github.com/rajatsen91/CCIT,8,2019-01-02 -Generative Probabilistic Novelty Detection with Adversarial Autoencoders,http://arxiv.org/abs/1807.02588v1,NIPS,2018,https://github.com/podgorskiy/GPND,16,2019-01-02 -Clipped Action Policy Gradient,http://proceedings.mlr.press/v80/fujita18a.html,ICML,2018,https://github.com/pfnet-research/capg,12,2019-01-02 -Learning to Explain: An Information-Theoretic Perspective on Model Interpretation,http://proceedings.mlr.press/v80/chen18j.html,ICML,2018,https://github.com/nickvosk/acl2015-dataset-learning-to-explain-entity-relationships,7,2019-01-02 -Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled,http://openaccess.thecvf.com/content_cvpr_2016/html/Koller_Deep_Hand_How_CVPR_2016_paper.html,CVPR,2016,https://github.com/neccam/TF-DeepHand,8,2019-01-02 -A Two-Step Disentanglement Method,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hadad_A_Two-Step_Disentanglement_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/naamahadad/A-Two-Step-Disentanglement-Method,7,2019-01-02 -Lost Relatives of the Gumbel Trick,http://proceedings.mlr.press/v70/balog17a.html,ICML,2017,https://github.com/matejbalog/gumbel-relatives,7,2019-01-02 -Where to Look: Focus Regions for Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2016/html/Shih_Where_to_Look_CVPR_2016_paper.html,CVPR,2016,https://github.com/kevjshih/wtl_vqa,7,2019-01-02 -Detecting Migrating Birds at Night,http://openaccess.thecvf.com/content_cvpr_2016/html/Huang_Detecting_Migrating_Birds_CVPR_2016_paper.html,CVPR,2016,https://github.com/jbhuang0604/BirdDetection,7,2019-01-02 -Cross-Domain Self-Supervised Multi-Task Feature Learning Using Synthetic Imagery,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ren_Cross-Domain_Self-Supervised_Multi-Task_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jason718/game-feature-learning,19,2019-01-02 -Supervised Discrete Hashing,http://openaccess.thecvf.com/content_cvpr_2015/html/Shen_Supervised_Discrete_Hashing_2015_CVPR_paper.html,CVPR,2015,https://github.com/goukoutaki/FSDH,7,2019-01-02 -PacGAN: The power of two samples in generative adversarial networks,http://arxiv.org/abs/1712.04086v2,NIPS,2018,https://github.com/fjxmlzn/PacGAN,10,2019-01-02 -Optimized Pre-Processing for Discrimination Prevention,http://papers.nips.cc/paper/6988-optimized-pre-processing-for-discrimination-prevention.pdf,NIPS,2017,https://github.com/fair-preprocessing/nips2017,9,2019-01-02 -Five-Point Fundamental Matrix Estimation for Uncalibrated Cameras,http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Five-Point_Fundamental_Matrix_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/danini/five-point-fundamental,8,2019-01-02 -Semantic Video Segmentation by Gated Recurrent Flow Propagation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Nilsson_Semantic_Video_Segmentation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/D-Nilsson/GRFP,9,2019-01-02 -RPAN: An End-To-End Recurrent Pose-Attention Network for Action Recognition in Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Du_RPAN_An_End-To-End_ICCV_2017_paper.html,ICCV,2017,https://github.com/agethen/RPAN,17,2019-01-02 -Geometry-Aware Scene Text Detection With Instance Transformation Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Geometry-Aware_Scene_Text_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zlmzju/itn,22,2019-01-02 -Investigating Haze-relevant Features in A Learning Framework for Image Dehazing,http://openaccess.thecvf.com/content_cvpr_2014/html/Tang_Investigating_Haze-relevant_Features_2014_CVPR_paper.html,CVPR,2014,https://github.com/zlinker/haze_2014,7,2019-01-02 -Progressive Attention Guided Recurrent Network for Salient Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Progressive_Attention_Guided_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhangxiaoning666/PAGR,7,2019-01-02 -Recurrent Attentional Networks for Saliency Detection,http://openaccess.thecvf.com/content_cvpr_2016/html/Kuen_Recurrent_Attentional_Networks_CVPR_2016_paper.html,CVPR,2016,https://github.com/zhangxiaoning666/PAGR,7,2019-01-02 -Practical Hash Functions for Similarity Estimation and Dimensionality Reduction,http://papers.nips.cc/paper/7239-practical-hash-functions-for-similarity-estimation-and-dimensionality-reduction.pdf,NIPS,2017,https://github.com/zera/Nips_MT,6,2019-01-02 -Low-Shot Learning With Imprinted Weights,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Low-Shot_Learning_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/YU1ut/imprinted-weights,19,2019-01-02 -Reconstructing PASCAL VOC,http://openaccess.thecvf.com/content_cvpr_2014/html/Vicente_Reconstructing_PASCAL_VOC_2014_CVPR_paper.html,CVPR,2014,https://github.com/yihui-he/reconstructing-pascal-voc,6,2019-01-02 -SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters,http://openaccess.thecvf.com/content_ECCV_2018/html/Yifan_Xu_SpiderCNN_Deep_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/xyf513/SpiderCNN,15,2019-01-02 -Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kuen_Stochastic_Downsampling_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xternalz/SDPoint,7,2019-01-02 -Scalable Planning with Tensorflow for Hybrid Nonlinear Domains,http://papers.nips.cc/paper/7207-scalable-planning-with-tensorflow-for-hybrid-nonlinear-domains.pdf,NIPS,2017,https://github.com/wuga214/TOOLBOX-Learning-and-Planning-through-Backpropagation,6,2019-01-02 -AttnGAN: Fine-Grained Text to Image Generation With Attentional Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_AttnGAN_Fine-Grained_Text_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Wentong-DST/attn-gan,7,2019-01-02 -Deep Crisp Boundaries,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Deep_Crisp_Boundaries_CVPR_2017_paper.html,CVPR,2017,https://github.com/Wangyupei/CED,9,2019-01-02 -Pooled Motion Features for First-Person Videos,http://openaccess.thecvf.com/content_cvpr_2015/html/Ryoo_Pooled_Motion_Features_2015_CVPR_paper.html,CVPR,2015,https://github.com/USCDataScience/hadoop-pot,6,2019-01-02 -Efficient and Robust Color Consistency for Community Photo Collections,http://openaccess.thecvf.com/content_cvpr_2016/html/Park_Efficient_and_Robust_CVPR_2016_paper.html,CVPR,2016,https://github.com/syncle/photo_consistency,7,2019-01-02 -Tensor Biclustering,http://papers.nips.cc/paper/6730-tensor-biclustering.pdf,NIPS,2017,https://github.com/SoheilFeizi/Tensor-Biclustering,6,2019-01-02 -Generalizing to Unseen Domains via Adversarial Data Augmentation,http://arxiv.org/abs/1805.12018v1,NIPS,2018,https://github.com/ricvolpi/generalize-unseen-domains,36,2019-01-02 -Unsupervised Pixel-Level Domain Adaptation With Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Bousmalis_Unsupervised_Pixel-Level_Domain_CVPR_2017_paper.html,CVPR,2017,https://github.com/rhythm92/Unsupervised-Pixel-Level-Domain-Adaptation-with-GAN,6,2019-01-02 -Following Gaze in Video,http://openaccess.thecvf.com/content_iccv_2017/html/Recasens_Following_Gaze_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/recasens/Gaze-Following,8,2019-01-02 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Object Stacking,http://openaccess.thecvf.com/content_ECCV_2018/html/Oliver_Groth_ShapeStacks_Learning_Vision-Based_ECCV_2018_paper.html,ECCV,2018,https://github.com/ogroth/shapestacks,11,2019-01-02 -Riemannian approach to batch normalization,http://papers.nips.cc/paper/7107-riemannian-approach-to-batch-normalization.pdf,NIPS,2017,https://github.com/MinhyungCho/riemannian-batch-normalization,6,2019-01-02 -End-To-End Learning of Geometry and Context for Deep Stereo Regression,http://openaccess.thecvf.com/content_iccv_2017/html/Kendall_End-To-End_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/liuruijin17/RickLiuGC,9,2019-01-02 -Improving Training of Deep Neural Networks via Singular Value Bounding,http://openaccess.thecvf.com/content_cvpr_2017/html/Jia_Improving_Training_of_CVPR_2017_paper.html,CVPR,2017,https://github.com/kui-jia/svb,6,2019-01-02 -Bayesian inference on random simple graphs with power law degree distributions,http://proceedings.mlr.press/v70/lee17a.html,ICML,2017,https://github.com/juho-lee/powerlawgraph,6,2019-01-02 -Reasoning About Fine-Grained Attribute Phrases Using Reference Games,http://openaccess.thecvf.com/content_iccv_2017/html/Su_Reasoning_About_Fine-Grained_ICCV_2017_paper.html,ICCV,2017,https://github.com/jongchyisu/attribute_phrases,7,2019-01-02 -Deep Learning Under Privileged Information Using Heteroscedastic Dropout,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lambert_Deep_Learning_Under_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/johnwlambert/dlupi-heteroscedastic-dropout,14,2019-01-02 -Multi-Label Image Recognition by Recurrently Discovering Attentional Regions,http://openaccess.thecvf.com/content_iccv_2017/html/Wang_Multi-Label_Image_Recognition_ICCV_2017_paper.html,ICCV,2017,https://github.com/James-Yip/AttentionImageClass,20,2019-01-02 -Centered Weight Normalization in Accelerating Training of Deep Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Centered_Weight_Normalization_ICCV_2017_paper.html,ICCV,2017,https://github.com/huangleiBuaa/CenteredWN,6,2019-01-02 -Adversarial Learning with Local Coordinate Coding,http://proceedings.mlr.press/v80/cao18a.html,ICML,2018,https://github.com/guoyongcs/LCCGAN,7,2019-01-02 -On GANs and GMMs,http://arxiv.org/abs/1805.12462v1,NIPS,2018,https://github.com/eitanrich/gans-n-gmms,10,2019-01-02 -Building a Regular Decision Boundary With Deep Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Oyallon_Building_a_Regular_CVPR_2017_paper.html,CVPR,2017,https://github.com/edouardoyallon/deep_separation_contraction,6,2019-01-02 -Learning a Descriptor-Specific 3D Keypoint Detector,http://openaccess.thecvf.com/content_iccv_2015/html/Salti_Learning_a_Descriptor-Specific_ICCV_2015_paper.html,ICCV,2015,https://github.com/CVLAB-Unibo/Keypoint-Learning,10,2019-01-02 -Towards Open-Set Identity Preserving Face Synthesis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Bao_Towards_Open-Set_Identity_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chloeguoqing/Towards-Open-Set-Identity-Preserving-Face-Synthesis,9,2019-01-02 -Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification,http://openaccess.thecvf.com/content_cvpr_2016/html/Hou_Patch-Based_Convolutional_Neural_CVPR_2016_paper.html,CVPR,2016,https://github.com/cheersyouran/cancer-detector,9,2019-01-02 -Piecewise Flat Embedding for Image Segmentation,http://openaccess.thecvf.com/content_iccv_2015/html/Yu_Piecewise_Flat_Embedding_ICCV_2015_paper.html,ICCV,2015,https://github.com/chaoweifang/PFE,7,2019-01-02 -Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems,http://papers.nips.cc/paper/6838-analyzing-hidden-representations-in-end-to-end-automatic-speech-recognition-systems.pdf,NIPS,2017,https://github.com/boknilev/asr-repr-analysis,6,2019-01-02 -A generic decentralized trust management framework,http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2012/MSC/MSC-2012-22.pdf,SPE,2013,https://github.com/amitport/graphpack,6,2019-01-02 -Personalized Image Aesthetics,http://openaccess.thecvf.com/content_iccv_2017/html/Ren_Personalized_Image_Aesthetics_ICCV_2017_paper.html,ICCV,2017,https://github.com/alanspike/personalizedImageAesthetics,7,2019-01-02 -Banach Wasserstein GAN,http://arxiv.org/abs/1806.06621v1,NIPS,2018,https://github.com/adler-j/bwgan,7,2019-01-02 -Towards Open World Recognition,http://openaccess.thecvf.com/content_cvpr_2015/html/Bendale_Towards_Open_World_2015_CVPR_paper.html,CVPR,2015,https://github.com/abhijitbendale/OWR,6,2019-01-02 -Collaborative Hashing,http://openaccess.thecvf.com/content_cvpr_2014/html/Liu_Collaborative_Hashing_2014_CVPR_paper.html,CVPR,2014,https://github.com/27359794/lsh-collab-filtering,6,2019-01-02 -Learning Facial Action Units From Web Images With Scalable Weakly Supervised Clustering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhao_Learning_Facial_Action_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zkl20061823/WSC,8,2019-01-02 -AutoLoc: Weakly-supervised Temporal Action Localization in Untrimmed Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Shou_AutoLoc_Weakly-supervised_Temporal_ECCV_2018_paper.html,ECCV,2018,https://github.com/zhengshou/AutoLoc,12,2019-01-02 -Dynamic Conditional Networks for Few-Shot Learning,http://openaccess.thecvf.com/content_ECCV_2018/html/Fang_Zhao_Dynamic_Conditional_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/ZhaoJ9014/Dynamic-Conditional-Networks-for-Few-Shot-Learning.pytorch,8,2019-01-02 -Mining Semantic Affordances of Visual Object Categories,http://openaccess.thecvf.com/content_cvpr_2015/html/Chao_Mining_Semantic_Affordances_2015_CVPR_paper.html,CVPR,2015,https://github.com/ywchao/semantic_affordance,5,2019-01-02 -Unsupervised Monocular Depth Estimation With Left-Right Consistency,http://openaccess.thecvf.com/content_cvpr_2017/html/Godard_Unsupervised_Monocular_Depth_CVPR_2017_paper.html,CVPR,2017,https://github.com/yukitsuji/monodepth_chainer,7,2019-01-02 -Viraliency: Pooling Local Virality,http://openaccess.thecvf.com/content_cvpr_2017/html/Alameda-Pineda_Viraliency_Pooling_Local_CVPR_2017_paper.html,CVPR,2017,https://github.com/xavirema/lena_pooling,5,2019-01-02 -Specular-to-Diffuse Translation for Multi-View Reconstruction,http://openaccess.thecvf.com/content_ECCV_2018/html/Shihao_Wu_Specular-to-Diffuse_Translation_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/wsh312/S2Dnet,8,2019-01-02 -Learning Algorithms for Active Learning,http://proceedings.mlr.press/v70/bachman17a.html,ICML,2017,https://github.com/vtphan/Code4Brownies,5,2019-01-02 -Deep TextSpotter: An End-To-End Trainable Scene Text Localization and Recognition Framework,http://openaccess.thecvf.com/content_iccv_2017/html/Busta_Deep_TextSpotter_An_ICCV_2017_paper.html,ICCV,2017,https://github.com/VeitL/OCR,13,2019-01-02 -Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition,http://papers.nips.cc/paper/6713-learning-koopman-invariant-subspaces-for-dynamic-mode-decomposition.pdf,NIPS,2017,https://github.com/thetak11/learning-kis,7,2019-01-02 -"High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach",http://proceedings.mlr.press/v80/pearce18a.html,ICML,2018,https://github.com/TeaPearce/Deep_Learning_Prediction_Intervals,11,2019-01-02 -Sparse convolutional coding for neuronal assembly detection,http://papers.nips.cc/paper/6958-sparse-convolutional-coding-for-neuronal-assembly-detection.pdf,NIPS,2017,https://github.com/sccfnad/Sparse-convolutional-coding-for-neuronal-assembly-detection,6,2019-01-02 -Point to Set Similarity Based Deep Feature Learning for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Point_to_Set_CVPR_2017_paper.html,CVPR,2017,https://github.com/samaonline/Point-to-Set-Similarity-Based-Deep-Feature-Learning-for-Person-Re-identification,5,2019-01-02 -Self-Organized Text Detection With Minimal Post-Processing via Border Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Wu_Self-Organized_Text_Detection_ICCV_2017_paper.html,ICCV,2017,https://github.com/saicoco/tf-sotd,12,2019-01-02 -Click Here: Human-Localized Keypoints as Guidance for Viewpoint Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Szeto_Click_Here_Human-Localized_ICCV_2017_paper.html,ICCV,2017,https://github.com/rszeto/click-here-cnn,5,2019-01-02 -Regret Minimization in MDPs with Options without Prior Knowledge,http://papers.nips.cc/paper/6909-regret-minimization-in-mdps-with-options-without-prior-knowledge.pdf,NIPS,2017,https://github.com/RonanFR/UCRL,8,2019-01-02 -Learning to Separate Object Sounds by Watching Unlabeled Video,http://openaccess.thecvf.com/content_ECCV_2018/html/Ruohan_Gao_Learning_to_Separate_ECCV_2018_paper.html,ECCV,2018,https://github.com/rhgao/separating-object-sounds,23,2019-01-02 -Ultra Large-Scale Feature Selection using Count-Sketches,http://proceedings.mlr.press/v80/aghazadeh18a.html,ICML,2018,https://github.com/rdspring1/MISSION,6,2019-01-02 -Transfer Learning via Learning to Transfer,http://proceedings.mlr.press/v80/wei18a.html,ICML,2018,https://github.com/QuebecAI/webcam-transfer-learning-v1,5,2019-01-02 -The World of Fast Moving Objects,http://openaccess.thecvf.com/content_cvpr_2017/html/Rozumnyi_The_World_of_CVPR_2017_paper.html,CVPR,2017,https://github.com/qixuanHou/Mapping-My-Break,5,2019-01-02 -What Makes an Object Memorable?,http://openaccess.thecvf.com/content_iccv_2015/html/Dubey_What_Makes_an_ICCV_2015_paper.html,ICCV,2015,https://github.com/qixuanHou/Mapping-My-Break,5,2019-01-02 -Bilevel Programming for Hyperparameter Optimization and Meta-Learning,http://proceedings.mlr.press/v80/franceschi18a.html,ICML,2018,https://github.com/prolearner/hyper-representation,6,2019-01-02 -Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Long_Attention_Clusters_Purely_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/pomonam/AttentionCluster,10,2019-01-02 -Inner Space Preserving Generative Pose Machine,http://openaccess.thecvf.com/content_ECCV_2018/html/Shuangjun_Liu_Inner_Space_Preserving_ECCV_2018_paper.html,ECCV,2018,https://github.com/ostadabbas/isp-gpm,6,2019-01-02 -Blind Justice: Fairness with Encrypted Sensitive Attributes,http://proceedings.mlr.press/v80/kilbertus18a.html,ICML,2018,https://github.com/nikikilbertus/blind-justice,5,2019-01-02 -Human Pose Estimation With Parsing Induced Learner,http://openaccess.thecvf.com/content_cvpr_2018/papers/Nie_Human_Pose_Estimation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/NieXC/pytorch-pil,11,2019-01-02 -SubUNets: End-To-End Hand Shape and Continuous Sign Language Recognition,http://openaccess.thecvf.com/content_iccv_2017/html/Camgoz_SubUNets_End-To-End_Hand_ICCV_2017_paper.html,ICCV,2017,https://github.com/neccam/SubUNets,7,2019-01-02 -Assessing Generative Models via Precision and Recall,http://arxiv.org/abs/1806.00035v1,NIPS,2018,https://github.com/msmsajjadi/precision-recall-distributions,13,2019-01-02 -Multimodal Generative Models for Scalable Weakly-Supervised Learning,http://arxiv.org/abs/1802.05335v2,NIPS,2018,https://github.com/mhw32/multimodal-vae-public,4,2019-01-02 -Tell Me What You See and I will Show You Where It Is,http://openaccess.thecvf.com/content_cvpr_2014/html/Xu_Tell_Me_What_2014_CVPR_paper.html,CVPR,2014,https://github.com/MarkipTheMudkip/in-class-project-2,6,2019-01-02 -Long-Term Correlation Tracking,http://openaccess.thecvf.com/content_cvpr_2015/html/Ma_Long-Term_Correlation_Tracking_2015_CVPR_paper.html,CVPR,2015,https://github.com/malreddysid/long-term-correlation-tracking,6,2019-01-02 -Learning a Discriminative Null Space for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Learning_a_Discriminative_CVPR_2016_paper.html,CVPR,2016,https://github.com/lzrobots/NullSpace_ReID,8,2019-01-02 -Cross-Modality Binary Code Learning via Fusion Similarity Hashing,http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Cross-Modality_Binary_Code_CVPR_2017_paper.html,CVPR,2017,https://github.com/LynnHongLiu/FSH,5,2019-01-02 -Dynamic-Structured Semantic Propagation Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liang_Dynamic-Structured_Semantic_Propagation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/limberc/DSSPN,5,2018-10-01 -The Description Length of Deep Learning models,https://arxiv.org/abs/1802.07044,NIPS,2018,https://github.com/leonardblier/descriptionlengthdeeplearning,5,2019-01-02 -Visual Tracking Using Attention-Modulated Disintegration and Integration,http://openaccess.thecvf.com/content_cvpr_2016/html/Choi_Visual_Tracking_Using_CVPR_2016_paper.html,CVPR,2016,https://github.com/jongwon20000/SCT,5,2019-01-02 -Gradually Updated Neural Networks for Large-Scale Image Recognition,http://proceedings.mlr.press/v80/qiao18b.html,ICML,2018,https://github.com/joe-siyuan-qiao/GUNN,7,2019-01-02 -HiDDeN: Hiding Data with Deep Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Jiren_Zhu_HiDDeN_Hiding_Data_ECCV_2018_paper.html,ECCV,2018,https://github.com/jirenz/HiDDeN,21,2019-01-02 -Robust Adversarial Reinforcement Learning,http://proceedings.mlr.press/v70/pinto17a.html,ICML,2017,https://github.com/Jekyll1021/RARL,6,2019-01-02 -K-Medoids For K-Means Seeding,http://papers.nips.cc/paper/7104-k-medoids-for-k-means-seeding.pdf,NIPS,2017,https://github.com/idiap/zentas,6,2019-01-02 -Orthogonally Decoupled Variational Gaussian Processes,http://arxiv.org/abs/1809.08820v1,NIPS,2018,https://github.com/hughsalimbeni/orth_decoupled_var_gps,6,2019-01-02 -Unsupervised holistic image generation from key local patches,http://openaccess.thecvf.com/content_ECCV_2018/html/Donghoon_Lee_Unsupervised_holistic_image_ECCV_2018_paper.html,ECCV,2018,https://github.com/hellbell/KeyPatchGan,6,2019-01-02 -Testing and Learning on Distributions with Symmetric Noise Invariance,http://papers.nips.cc/paper/6733-testing-and-learning-on-distributions-with-symmetric-noise-invariance.pdf,NIPS,2017,https://github.com/hcllaw/phase_learn,5,2019-01-02 -Dense Semantic Correspondence Where Every Pixel is a Classifier,http://openaccess.thecvf.com/content_iccv_2015/html/Bristow_Dense_Semantic_Correspondence_ICCV_2015_paper.html,ICCV,2015,https://github.com/hbristow/epic,5,2019-01-02 -Learning Steady-States of Iterative Algorithms over Graphs,http://proceedings.mlr.press/v80/dai18a.html,ICML,2018,https://github.com/Hanjun-Dai/steady_state_embedding,7,2019-01-02 -"Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference",http://papers.nips.cc/paper/7268-sticking-the-landing-simple-lower-variance-gradient-estimators-for-variational-inference.pdf,NIPS,2017,https://github.com/geoffroeder/iwae,5,2019-01-02 -Beyond Local Search: Tracking Objects Everywhere With Instance-Specific Proposals,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhu_Beyond_Local_Search_CVPR_2016_paper.html,CVPR,2016,https://github.com/GaoCode/EBT,5,2019-01-02 -NeuralFDR: Learning Discovery Thresholds from Hypothesis Features,http://papers.nips.cc/paper/6752-neuralfdr-learning-discovery-thresholds-from-hypothesis-features.pdf,NIPS,2017,https://github.com/fxia22/NeuralFDR,5,2019-01-02 -Inter and Intra Topic Structure Learning with Word Embeddings,http://proceedings.mlr.press/v80/zhao18a.html,ICML,2018,https://github.com/ethanhezhao/WEDTM,5,2019-01-02 -Modeling Sparse Deviations for Compressed Sensing using Generative Models,http://proceedings.mlr.press/v80/dhar18a.html,ICML,2018,https://github.com/ermongroup/sparse_gen,9,2019-01-02 -Diving into the shallows: a computational perspective on large-scale shallow learning,http://papers.nips.cc/paper/6968-diving-into-the-shallows-a-computational-perspective-on-large-scale-shallow-learning.pdf,NIPS,2017,https://github.com/EigenPro/EigenPro-tensorflow,5,2019-01-02 -Rotation Equivariant Vector Field Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Marcos_Rotation_Equivariant_Vector_ICCV_2017_paper.html,ICCV,2017,https://github.com/dmarcosg/RotEqNet,5,2019-01-02 -Neural Architecture Optimization,http://arxiv.org/abs/1808.07233v3,NIPS,2018,https://github.com/dicarlolab/archconvnets,5,2019-01-02 -"Pixels, Voxels, and Views: A Study of Shape Representations for Single View 3D Object Shape Prediction",http://openaccess.thecvf.com/content_cvpr_2018/papers/Shin_Pixels_Voxels_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/daeyun/object-shapes-cvpr18,9,2019-01-02 -Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web Prior,http://openaccess.thecvf.com/content_ECCV_2018/html/Sijia_Cai_Weakly-supervised_Video_Summarization_ECCV_2018_paper.html,ECCV,2018,https://github.com/cssjcai/vesd,5,2019-01-02 -Recursive Sampling for the Nystrom Method,http://papers.nips.cc/paper/6973-recursive-sampling-for-the-nystrom-method.pdf,NIPS,2017,https://github.com/cnmusco/recursive-nystrom,5,2019-01-02 -Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations,http://proceedings.mlr.press/v80/chen18g.html,ICML,2018,https://github.com/chentingpc/kdcode-lm,8,2019-01-02 -Constraint-Aware Deep Neural Network Compression,http://openaccess.thecvf.com/content_ECCV_2018/html/Changan_Chen_Constraints_Matter_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/ChanganVR/ConstraintAwareCompression,9,2019-01-02 -Functional Faces: Groupwise Dense Correspondence Using Functional Maps,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Functional_Faces_Groupwise_CVPR_2016_paper.html,CVPR,2016,https://github.com/cazhang/funcFaces,5,2019-01-02 -The Mirage of Action-Dependent Baselines in Reinforcement Learning,http://proceedings.mlr.press/v80/tucker18a.html,ICML,2018,https://github.com/brain-research/mirage-rl,7,2019-01-02 -Learning From Video and Text via Large-Scale Discriminative Clustering,http://openaccess.thecvf.com/content_iccv_2017/html/Miech_Learning_From_Video_ICCV_2017_paper.html,ICCV,2017,https://github.com/antoine77340/iccv17learning,5,2019-01-02 -Don’t Just Assume Look and Answer: Overcoming Priors for Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Agrawal_Dont_Just_Assume_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/AishwaryaAgrawal/GVQA,7,2019-01-02 -Cognitive Mapping and Planning for Visual Navigation,http://openaccess.thecvf.com/content_cvpr_2017/html/Gupta_Cognitive_Mapping_and_CVPR_2017_paper.html,CVPR,2017,https://github.com/agiantwhale/cognitive-mapping-agent,9,2019-01-02 -Forecasting Human Dynamics From Static Images,http://openaccess.thecvf.com/content_cvpr_2017/html/Chao_Forecasting_Human_Dynamics_CVPR_2017_paper.html,CVPR,2017,https://github.com/ywchao/skeleton2d3d,6,2019-01-02 -Improving Human Action Recognition by Non-Action Classification,http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Improving_Human_Action_CVPR_2016_paper.html,CVPR,2016,https://github.com/yangwangx/NonActionShot,4,2019-01-02 -Zero-Shot Recognition Using Dual Visual-Semantic Mapping Paths,http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Zero-Shot_Recognition_Using_CVPR_2017_paper.html,CVPR,2017,https://github.com/YanaLee/Zero-Shot-Recognition-using-Dual-Visual-Semantic-Mapping-Paths,4,2019-01-02 -Low-Rank Matrix Factorization Under General Mixture Noise Distributions,http://openaccess.thecvf.com/content_iccv_2015/html/Cao_Low-Rank_Matrix_Factorization_ICCV_2015_paper.html,ICCV,2015,https://github.com/xiangyongcao/PMoEP,4,2019-01-02 -Efficient Minimal-Surface Regularization of Perspective Depth Maps in Variational Stereo,http://openaccess.thecvf.com/content_cvpr_2015/html/Graber_Efficient_Minimal-Surface_Regularization_2015_CVPR_paper.html,CVPR,2015,https://github.com/VLOGroup/surface-area-regularization,4,2019-01-02 -Transferable Adversarial Perturbations,http://openaccess.thecvf.com/content_ECCV_2018/html/Bruce_Hou_Transferable_Adversarial_Perturbations_ECCV_2018_paper.html,ECCV,2018,https://github.com/vinayprabhu/Gainsboro-box-attacks-,4,2019-01-02 -Pose-Aware Person Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Kumar_Pose-Aware_Person_Recognition_CVPR_2017_paper.html,CVPR,2017,https://github.com/vijaykumar01/person_recognition,4,2019-01-02 -Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images,http://openaccess.thecvf.com/content_cvpr_2018/papers/Orekondy_Connecting_Pixels_to_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tribhuvanesh/visual_redactions,4,2019-01-02 -Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Yingjie_Yao_Joint_Representation_and_ECCV_2018_paper.html,ECCV,2018,https://github.com/tourmaline612/RTINet,4,2019-01-02 -Predicting Salient Face in Multiple-Face Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Predicting_Salient_Face_CVPR_2017_paper.html,CVPR,2017,https://github.com/tonysy/salient-face-in-MUVFET,4,2019-01-02 -Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification,http://openaccess.thecvf.com/content_ECCV_2018/html/Eric_Muller-Budack_Geolocation_Estimation_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/TIBHannover/GeoEstimation,4,2019-01-02 -Superdifferential Cuts for Binary Energies,http://openaccess.thecvf.com/content_cvpr_2015/html/Taniai_Superdifferential_Cuts_for_2015_CVPR_paper.html,CVPR,2015,https://github.com/t-taniai/SDC_CVPR2015,4,2019-01-02 -Global optimization of Lipschitz functions,http://proceedings.mlr.press/v70/malherbe17a.html,ICML,2017,https://github.com/Sycor4x/lipo,5,2019-01-02 -Pose Induction for Novel Object Categories,http://openaccess.thecvf.com/content_iccv_2015/html/Tulsiani_Pose_Induction_for_ICCV_2015_paper.html,ICCV,2015,https://github.com/shubhtuls/poseInduction,4,2019-01-02 -Multi-View Convolutional Neural Networks for 3D Shape Recognition,http://openaccess.thecvf.com/content_iccv_2015/html/Su_Multi-View_Convolutional_Neural_ICCV_2015_paper.html,ICCV,2015,https://github.com/shawnxu1318/MVCNN-Multi-View-Convolutional-Neural-Networks,7,2019-01-02 -Learning Cooperative Visual Dialog Agents With Deep Reinforcement Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Das_Learning_Cooperative_Visual_ICCV_2017_paper.html,ICCV,2017,https://github.com/schopra8/Cooperative_Vis_Diag_RL,4,2019-01-02 -Estimating the Success of Unsupervised Image to Image Translation,http://openaccess.thecvf.com/content_ECCV_2018/html/Lior_Wolf_Estimating_the_Success_ECCV_2018_paper.html,ECCV,2018,https://github.com/sagiebenaim/gan_bound,5,2019-01-02 -Bottleneck Conditional Density Estimation,http://proceedings.mlr.press/v70/shu17a.html,ICML,2017,https://github.com/RuiShu/bcde,4,2019-01-02 -Quadrature-based features for kernel approximation,http://arxiv.org/abs/1802.03832v3,NIPS,2018,https://github.com/quffka/quffka,4,2019-01-02 -Towards Realistic Predictors,http://openaccess.thecvf.com/content_ECCV_2018/html/Pei_Wang_Towards_Realistic_Predictors_ECCV_2018_paper.html,ECCV,2018,https://github.com/peiwang062/towards-realistic-predictors,7,2019-01-02 -ROAM: A Rich Object Appearance Model With Application to Rotoscoping,http://openaccess.thecvf.com/content_cvpr_2017/html/Miksik_ROAM_A_Rich_CVPR_2017_paper.html,CVPR,2017,https://github.com/omiksik/roam,5,2019-01-02 -Tracking Emerges by Colorizing Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Carl_Vondrick_Self-supervised_Tracking_by_ECCV_2018_paper.html,ECCV,2018,https://github.com/Oh-Yoojin/Tracking-Emerges-by-Colorizing-Videos,4,2019-01-02 -Multi-way Interacting Regression via Factorization Machines,http://papers.nips.cc/paper/6853-multi-way-interacting-regression-via-factorization-machines.pdf,NIPS,2017,https://github.com/moonfolk/MiFM,4,2019-01-02 -Conic Scan-and-Cover algorithms for nonparametric topic modeling,http://papers.nips.cc/paper/6977-conic-scan-and-cover-algorithms-for-nonparametric-topic-modeling.pdf,NIPS,2017,https://github.com/moonfolk/Geometric-Topic-Modeling,5,2019-01-02 -Active Decision Boundary Annotation With Deep Generative Models,http://openaccess.thecvf.com/content_iccv_2017/html/Huijser_Active_Decision_Boundary_ICCV_2017_paper.html,ICCV,2017,https://github.com/MiriamHu/ActiveBoundary,5,2019-01-02 -Differentially Private Database Release via Kernel Mean Embeddings,http://proceedings.mlr.press/v80/balog18a.html,ICML,2018,https://github.com/matejbalog/RKHS-private-database,4,2019-01-02 -Mutual Information Neural Estimation,http://proceedings.mlr.press/v80/belghazi18a.html,ICML,2018,https://github.com/MasanoriYamada/Mine_pytorch,39,2019-01-02 -Simultaneous Deep Transfer Across Domains and Tasks,http://openaccess.thecvf.com/content_iccv_2015/html/Tzeng_Simultaneous_Deep_Transfer_ICCV_2015_paper.html,ICCV,2015,https://github.com/mahfujau/domain_adaptation_iccv15,6,2019-01-02 -Inference Suboptimality in Variational Autoencoders,http://proceedings.mlr.press/v80/cremer18a.html,ICML,2018,https://github.com/lxuechen/inference-suboptimality,4,2019-01-02 -Classification from Pairwise Similarity and Unlabeled Data,http://proceedings.mlr.press/v80/bao18a.html,ICML,2018,https://github.com/levelfour/SU_Classification,9,2019-01-02 -Globally Optimal Manhattan Frame Estimation in Real-Time,http://openaccess.thecvf.com/content_cvpr_2016/html/Joo_Globally_Optimal_Manhattan_CVPR_2016_paper.html,CVPR,2016,https://github.com/Kyungdon/mf_estimation,7,2019-01-02 -DVQA: Understanding Data Visualizations via Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kafle_DVQA_Understanding_Data_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kushalkafle/DVQA_dataset,7,2019-01-02 -Prior-Less Compressible Structure From Motion,http://openaccess.thecvf.com/content_cvpr_2016/html/Kong_Prior-Less_Compressible_Structure_CVPR_2016_paper.html,CVPR,2016,https://github.com/kongchen1992/compressible-sfm,4,2019-01-02 -Statistically-motivated Second-order Pooling,http://openaccess.thecvf.com/content_ECCV_2018/html/Kaicheng_Yu_Statistically-motivated_Second-order_Pooling_ECCV_2018_paper.html,ECCV,2018,https://github.com/kcyu2014/smsop,9,2019-01-02 -Object Co-Skeletonization With Co-Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Jerripothula_Object_Co-Skeletonization_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/jkoteswarrao/Object-Co-skeletonization-with-Co-segmentation,5,2019-01-02 -Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lyu_Multi-Oriented_Scene_Text_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JK-Rao/Corner_Segmentation_TextDetection,10,2019-01-02 -Salient Region Detection via High-Dimensional Color Transform,http://openaccess.thecvf.com/content_cvpr_2014/html/Kim_Salient_Region_Detection_2014_CVPR_paper.html,CVPR,2014,https://github.com/jhkim89/Saliency-HDCT,6,2019-01-02 -Joint Discovery of Object States and Manipulation Actions,http://openaccess.thecvf.com/content_iccv_2017/html/Alayrac_Joint_Discovery_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/jalayrac/object-states-action,4,2019-01-02 -From Red Wine to Red Tomato: Composition With Context,http://openaccess.thecvf.com/content_cvpr_2017/html/Misra_From_Red_Wine_CVPR_2017_paper.html,CVPR,2017,https://github.com/imisra/composing_cvpr17,4,2019-01-02 -Light Structure from Pin Motion: Simple and Accurate Point Light Calibration for Physics-based Modeling,http://openaccess.thecvf.com/content_ECCV_2018/html/Hiroaki_Santo_Light_Structure_from_ECCV_2018_paper.html,ECCV,2018,https://github.com/hiroaki-santo/light-structure-from-pin-motion,7,2019-01-02 -Cross-Stitch Networks for Multi-Task Learning,http://openaccess.thecvf.com/content_cvpr_2016/html/Misra_Cross-Stitch_Networks_for_CVPR_2016_paper.html,CVPR,2016,https://github.com/helloyide/Cross-stitch-Networks-for-Multi-task-Learning,8,2019-01-02 -Discover and Learn New Objects From Documentaries,http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Discover_and_Learn_CVPR_2017_paper.html,CVPR,2017,https://github.com/hellock/documentary-learning,5,2019-01-02 -From Bayesian Sparsity to Gated Recurrent Nets,http://papers.nips.cc/paper/7139-from-bayesian-sparsity-to-gated-recurrent-nets.pdf,NIPS,2017,https://github.com/hehaodele/SBL-LSTM-Net,8,2019-01-02 -Efficient Deep Learning for Stereo Matching,http://openaccess.thecvf.com/content_cvpr_2016/html/Luo_Efficient_Deep_Learning_CVPR_2016_paper.html,CVPR,2016,https://github.com/haojeng-wang/dl_stereo_matching,7,2019-01-02 -End-to-End Incremental Learning,http://openaccess.thecvf.com/content_ECCV_2018/html/Francisco_M._Castro_End-to-End_Incremental_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/fmcp/EndToEndIncrementalLearning,10,2019-01-02 -Breaking the Activation Function Bottleneck through Adaptive Parameterization,https://arxiv.org/abs/1805.08574,NIPS,2018,https://github.com/flennerhag/alstm,6,2019-01-02 -Robust Physical-World Attacks on Deep Learning Visual Classification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Eykholt_Robust_Physical-World_Attacks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/evtimovi/robust_physical_perturbations,11,2019-01-02 -Understanding Black-box Predictions via Influence Functions,http://proceedings.mlr.press/v70/koh17a.html,ICML,2017,https://github.com/eolecvk/InfluenceFunctions,5,2019-01-02 -"Decoupling ""when to update"" from ""how to update""",http://papers.nips.cc/paper/6697-decoupling-when-to-update-from-how-to-update.pdf,NIPS,2017,https://github.com/emalach/UpdateByDisagreement,5,2019-01-02 -Deep Recurrent Neural Network-Based Identification of Precursor microRNAs,http://papers.nips.cc/paper/6882-deep-recurrent-neural-network-based-identification-of-precursor-micrornas.pdf,NIPS,2017,https://github.com/eleventh83/deepMiRGene,4,2019-01-02 -Differentially private Bayesian learning on distributed data,http://papers.nips.cc/paper/6915-differentially-private-bayesian-learning-on-distributed-data.pdf,NIPS,2017,https://github.com/DPBayes/dca-nips2017,5,2019-01-02 -Grad-CAM: Visual Explanations From Deep Networks via Gradient-Based Localization,http://openaccess.thecvf.com/content_iccv_2017/html/Selvaraju_Grad-CAM_Visual_Explanations_ICCV_2017_paper.html,ICCV,2017,https://github.com/cydonia999/Grad-CAM-in-TensorFlow,5,2019-01-02 -Guarantees for Greedy Maximization of Non-submodular Functions with Applications,http://proceedings.mlr.press/v70/bian17a.html,ICML,2017,https://github.com/bianan/non-submodular-max,4,2019-01-02 -Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains,http://openaccess.thecvf.com/content_cvpr_2018/papers/Pang_Zoom_and_Learn_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Artifineuro/zole,6,2019-01-02 -Question Asking as Program Generation,http://papers.nips.cc/paper/6705-question-asking-as-program-generation.pdf,NIPS,2017,https://github.com/anselmrothe/question_dataset,5,2019-01-02 -Logo Synthesis and Manipulation With Clustered Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sage_Logo_Synthesis_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/alex-sage/logo-gen,10,2019-01-02 -Learning Face Age Progression: A Pyramid Architecture of GANs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Learning_Face_Age_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ajithvallabai/Pyramid-Architecture-of-GANs,11,2019-01-02 -BourGAN: Generative Networks with Metric Embeddings,https://arxiv.org/abs/1805.07674,NIPS,2018,https://github.com/a554b554/BourGAN,8,2019-01-02 -Statistical Recurrent Models on Manifold valued Data,http://arxiv.org/abs/1805.11204v1,NIPS,2018,https://github.com/zhenxingjian/SPD-SRU,3,2019-01-02 -Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization,http://proceedings.mlr.press/v80/zhang18g.html,ICML,2018,https://github.com/zhangjiong724/spectral-RNN,3,2019-01-02 -Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving,http://openaccess.thecvf.com/content_ECCV_2018/html/Peiliang_LI_Stereo_Vision-based_Semantic_ECCV_2018_paper.html,ECCV,2018,https://github.com/zhanghanduo/stereo_semantic_mapping,5,2019-01-02 -A Unified View of Multi-Label Performance Measures,http://proceedings.mlr.press/v70/wu17a.html,ICML,2017,https://github.com/YuriWu/LIMO,2,2019-01-02 -Robust Saliency Detection via Regularized Random Walks Ranking,http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Robust_Saliency_Detection_2015_CVPR_paper.html,CVPR,2015,https://github.com/yuanyc06/rr,3,2019-01-02 -A Joint Sequence Fusion Model for Video Question Answering and Retrieval,http://openaccess.thecvf.com/content_ECCV_2018/html/Youngjae_Yu_A_Joint_Sequence_ECCV_2018_paper.html,ECCV,2018,https://github.com/yj-yu/lsmdc,11,2019-01-02 -SegStereo: Exploiting Semantic Information for Disparity Estimation,http://openaccess.thecvf.com/content_ECCV_2018/html/Guorun_Yang_SegStereo_Exploiting_Semantic_ECCV_2018_paper.html,ECCV,2018,https://github.com/yangguorun/SegStereo,16,2019-01-02 -Gaze Prediction in Dynamic 360° Immersive Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Gaze_Prediction_in_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xuyanyu-shh/VR-EyeTracking,3,2019-01-02 -Saliency Detection in 360° Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Ziheng_Zhang_Saliency_Detection_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/xuyanyu-shh/Saliency-detection-in-360-video,9,2019-01-02 -Image Super-Resolution via Dual-State Recurrent Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Han_Image_Super-Resolution_via_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/WeiHan3/dsrn,1,2019-01-02 -Ring Loss: Convex Feature Normalization for Face Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zheng_Ring_Loss_Convex_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/vsatyakumar/Ring-Loss-Keras,3,2019-01-02 -Multi-Label Cross-Modal Retrieval,http://openaccess.thecvf.com/content_iccv_2015/html/Ranjan_Multi-Label_Cross-Modal_Retrieval_ICCV_2015_paper.html,ICCV,2015,https://github.com/Viresh-R/ml-CCA,4,2019-01-02 -Feedback-Prop: Convolutional Neural Network Inference Under Partial Evidence,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Feedback-Prop_Convolutional_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/uvavision/feedbackprop,4,2019-01-02 -Rolling-Shutter-Aware Differential SfM and Image Rectification,http://openaccess.thecvf.com/content_iccv_2017/html/Zhuang_Rolling-Shutter-Aware_Differential_SfM_ICCV_2017_paper.html,ICCV,2017,https://github.com/ThomasZiegler/RS-aware-differential-SfM,5,2019-01-02 -Learning to Branch,http://proceedings.mlr.press/v80/balcan18a.html,ICML,2018,https://github.com/StoneyJackson/github-workflow-activity,3,2019-01-02 -Sidekick Policy Learning for Active Visual Exploration,http://openaccess.thecvf.com/content_ECCV_2018/html/Santhosh_Kumar_Ramakrishnan_Sidekick_Policy_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/srama2512/sidekicks,5,2019-01-02 -Spatially-Adaptive Filter Units for Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tabernik_Spatially-Adaptive_Filter_Units_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/skokec/DAU-ConvNet,3,2019-01-02 -Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs,http://papers.nips.cc/paper/7049-near-optimal-edge-evaluation-in-explicit-generalized-binomial-graphs.pdf,NIPS,2017,https://github.com/sanjibac/matlab_learning_collision_checking,3,2019-01-02 -Large Margin Object Tracking With Circulant Feature Maps,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Large_Margin_Object_CVPR_2017_paper.html,CVPR,2017,https://github.com/sallymmx/LMCF,3,2019-01-02 -Adversarial Surrogate Losses for Ordinal Regression,http://papers.nips.cc/paper/6659-adversarial-surrogate-losses-for-ordinal-regression.pdf,NIPS,2017,https://github.com/rizalzaf/adversarial-ordinal,3,2019-01-02 -DenseCap: Fully Convolutional Localization Networks for Dense Captioning,http://openaccess.thecvf.com/content_cvpr_2016/html/Johnson_DenseCap_Fully_Convolutional_CVPR_2016_paper.html,CVPR,2016,https://github.com/rampage644/densecap-tensorflow,4,2019-01-02 -Encoder Based Lifelong Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Rannen_Encoder_Based_Lifelong_ICCV_2017_paper.html,ICCV,2017,https://github.com/rahafaljundi/Encoder-Based-Lifelong-learning,4,2019-01-02 -Counting Everyday Objects in Everyday Scenes,http://openaccess.thecvf.com/content_cvpr_2017/html/Chattopadhyay_Counting_Everyday_Objects_CVPR_2017_paper.html,CVPR,2017,https://github.com/prithv1/cvpr2017_counting,3,2019-01-02 -Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System,http://papers.nips.cc/paper/6849-toward-goal-driven-neural-network-models-for-the-rodent-whisker-trigeminal-system.pdf,NIPS,2017,https://github.com/neuroailab/whisker_model,3,2019-01-02 -Alternating Direction Graph Matching,http://openaccess.thecvf.com/content_cvpr_2017/html/Le-Huu_Alternating_Direction_Graph_CVPR_2017_paper.html,CVPR,2017,https://github.com/netw0rkf10w/adgm,4,2019-01-02 -Deep Burst Denoising,http://openaccess.thecvf.com/content_ECCV_2018/html/Clement_Godard_Deep_Burst_Denoising_ECCV_2018_paper.html,ECCV,2018,https://github.com/mrharicot/deep_burst_denoising,3,2019-01-02 -Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC,http://proceedings.mlr.press/v70/cong17a.html,ICML,2017,https://github.com/mingyuanzhou/DeepLDA_TLASGR_MCMC,3,2019-01-02 -Diverse and Coherent Paragraph Generation from Images,http://openaccess.thecvf.com/content_ECCV_2018/html/Moitreya_Chatterjee_Diverse_and_Coherent_ECCV_2018_paper.html,ECCV,2018,https://github.com/metro-smiles/CapG_RevG_Code,5,2019-01-02 -Lip Reading Sentences in the Wild,http://openaccess.thecvf.com/content_cvpr_2017/html/Chung_Lip_Reading_Sentences_CVPR_2017_paper.html,CVPR,2017,https://github.com/lsrock1/WLSNet_pytorch,5,2019-01-02 -Unsupervised Generation of a Viewpoint Annotated Car Dataset From Videos,http://openaccess.thecvf.com/content_iccv_2015/html/Sedaghat_Unsupervised_Generation_of_ICCV_2015_paper.html,ICCV,2015,https://github.com/lmb-freiburg/unsup-car-dataset,5,2019-01-02 -Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems,http://papers.nips.cc/paper/6798-expectation-propagation-with-stochastic-kinetic-model-in-complex-interaction-systems.pdf,NIPS,2017,https://github.com/lefangcs/Expectation-Propagation-with-Stochastic-Kinetic-Model-in-Complex-Interaction-Systems,3,2019-01-02 -Simultaneous Video Defogging and Stereo Reconstruction,http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Simultaneous_Video_Defogging_2015_CVPR_paper.html,CVPR,2015,https://github.com/Lashuk1729/DIP-Project-Video-Dehazing,3,2019-01-02 -Hyperspectral Super-Resolution by Coupled Spectral Unmixing,http://openaccess.thecvf.com/content_iccv_2015/html/Lanaras_Hyperspectral_Super-Resolution_by_ICCV_2015_paper.html,ICCV,2015,https://github.com/lanha/SupResPALM,3,2019-01-02 -Aesthetic Critiques Generation for Photos,http://openaccess.thecvf.com/content_iccv_2017/html/Chang_Aesthetic_Critiques_Generation_ICCV_2017_paper.html,ICCV,2017,https://github.com/kunghunglu/DeepPhotoCritic-ICCV17,3,2019-01-02 -Force From Motion: Decoding Physical Sensation in a First Person Video,http://openaccess.thecvf.com/content_cvpr_2016/html/Park_Force_From_Motion_CVPR_2016_paper.html,CVPR,2016,https://github.com/jyhjinghwang/Force_from_Motion_Gravity_Models,3,2019-01-02 -CLEAR: Cumulative LEARning for One-Shot One-Class Image Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kozerawski_CLEAR_Cumulative_LEARning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JKozerawski/CLEAR-osoc,3,2019-01-02 -Loss Max-Pooling for Semantic Image Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Bulo_Loss_Max-Pooling_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/jjkke88/LMP,3,2019-01-02 -Deepcode: Feedback Codes via Deep Learning,http://arxiv.org/abs/1807.00801v1,NIPS,2018,https://github.com/hyejikim1/Deepcode,4,2019-01-02 -Disentangling Factors of Variation by Mixing Them,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Disentangling_Factors_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/HuQyang/Disentangling-Factors-of-Variation-by-Mixing-Them,5,2019-01-02 -Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization,http://openaccess.thecvf.com/content_cvpr_2015/html/Oh_Fast_Randomized_Singular_2015_CVPR_paper.html,CVPR,2015,https://github.com/HlG4399/FRSVT,5,2019-01-02 -Learning Answer Embeddings for Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Learning_Answer_Embeddings_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hexiang-hu/answer_embedding,3,2019-01-02 -Context-Aware Gaussian Fields for Non-Rigid Point Set Registration,http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Context-Aware_Gaussian_Fields_CVPR_2016_paper.html,CVPR,2016,https://github.com/gwang-cv/CA-LapGF-Demo,3,2019-01-02 -Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach,http://openaccess.thecvf.com/content_cvpr_2017/html/Patrini_Making_Deep_Neural_CVPR_2017_paper.html,CVPR,2017,https://github.com/GarrettLee/label_noise_correction,5,2019-01-02 -Oriented Object Proposals,http://openaccess.thecvf.com/content_iccv_2015/html/He_Oriented_Object_Proposals_ICCV_2015_paper.html,ICCV,2015,https://github.com/frutuozo29/WebServiceRESTFul,3,2019-01-02 -Segment Graph Based Image Filtering: Fast Structure-Preserving Smoothing,http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Segment_Graph_Based_ICCV_2015_paper.html,ICCV,2015,https://github.com/feihuzhang/SGF,5,2019-01-02 -A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control,http://papers.nips.cc/paper/7177-a-framework-for-multi-armedbandit-testing-with-online-fdr-control.pdf,NIPS,2017,https://github.com/fanny-yang/MABFDR,3,2019-01-02 -kNN Hashing With Factorized Neighborhood Representation,http://openaccess.thecvf.com/content_iccv_2015/html/Ding_kNN_Hashing_With_ICCV_2015_paper.html,ICCV,2015,https://github.com/dooook/kNN-hashing,3,2019-01-02 -Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care,http://proceedings.mlr.press/v80/schwab18a.html,ICML,2018,https://github.com/d909b/DSMT-Nets,3,2019-01-02 -Minimum Barrier Salient Object Detection at 80 FPS,http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Minimum_Barrier_Salient_ICCV_2015_paper.html,ICCV,2015,https://github.com/coderSkyChen/MBS_Cplus_c-,3,2019-01-02 -Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning,http://papers.nips.cc/paper/7154-unifying-pac-and-regret-uniform-pac-bounds-for-episodic-reinforcement-learning.pdf,NIPS,2017,https://github.com/chrodan/FiniteEpisodicRL.jl,3,2019-01-02 -High-Resolution Image Synthesis and Semantic Manipulation With Conditional GANs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_High-Resolution_Image_Synthesis_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chenxli/High-Resolution-Image-Synthesis-and-Semantic-Manipulation-with-Conditional-GANsl-,8,2019-01-02 -Parallel Bayesian Network Structure Learning,http://proceedings.mlr.press/v80/gao18b.html,ICML,2018,https://github.com/bign8/PyStruct,3,2019-01-02 -Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms,http://papers.nips.cc/paper/6652-continuous-dr-submodular-maximization-structure-and-algorithms.pdf,NIPS,2017,https://github.com/bianan,3,2018-09-16 -On Structured Prediction Theory with Calibrated Convex Surrogate Losses,http://papers.nips.cc/paper/6634-on-structured-prediction-theory-with-calibrated-convex-surrogate-losses.pdf,NIPS,2017,https://github.com/aosokin/consistentSurrogates_derivations,4,2019-01-02 -Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings,http://openaccess.thecvf.com/content_iccv_2017/html/Thewlis_Unsupervised_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/alldbi/Factorized-Spatial-Embeddings,6,2019-01-02 -Compatible Reward Inverse Reinforcement Learning,http://papers.nips.cc/paper/6800-compatible-reward-inverse-reinforcement-learning.pdf,NIPS,2017,https://github.com/albertometelli/crirl,3,2019-01-02 -Tensor Belief Propagation,http://proceedings.mlr.press/v70/wrigley17a.html,ICML,2017,https://github.com/akxlr/tbp,6,2019-01-02 -Convergent Tree Backup and Retrace with Function Approximation,http://proceedings.mlr.press/v80/touati18a.html,ICML,2018,https://github.com/ahmed-touati/convergent-off-policy,3,2019-01-02 -Efficient Globally Optimal 2D-To-3D Deformable Shape Matching,http://openaccess.thecvf.com/content_cvpr_2016/html/Lahner_Efficient_Globally_Optimal_CVPR_2016_paper.html,CVPR,2016,https://github.com/zorah/Elastic2D3D,2,2019-01-02 -Batched High-dimensional Bayesian Optimization via Structural Kernel Learning,http://proceedings.mlr.press/v70/wang17h.html,ICML,2017,https://github.com/zi-w/Structural-Kernel-Learning-for-HDBBO,2,2019-01-02 -Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Dynamic_Scene_Deblurring_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhjwustc/cvpr18_rnn_deblur_matcaffe,6,2019-01-02 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Interventions,http://papers.nips.cc/paper/7164-permutation-based-causal-inference-algorithms-with-interventions.pdf,NIPS,2017,https://github.com/yuhaow/sp-intervention,2,2019-01-02 -An Egocentric Look at Video Photographer Identity,http://openaccess.thecvf.com/content_cvpr_2016/html/Hoshen_An_Egocentric_Look_CVPR_2016_paper.html,CVPR,2016,https://github.com/Yedid/ego,2,2019-01-02 -Learning to Super-Resolve Blurry Face and Text Images,http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Learning_to_Super-Resolve_ICCV_2017_paper.html,ICCV,2017,https://github.com/xuxy09/joint_SR_Deblur,2,2019-01-02 -Joint Person Segmentation and Identification in Synchronized First- and Third-person Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Mingze_Xu_Joint_Person_Segmentation_ECCV_2018_paper.html,ECCV,2018,https://github.com/xumingze0308/firstthird-eccv2018,2,2019-01-02 -Learning Non-Maximum Suppression,http://openaccess.thecvf.com/content_cvpr_2017/html/Hosang_Learning_Non-Maximum_Suppression_CVPR_2017_paper.html,CVPR,2017,https://github.com/XingchenYu/pedestrian_detection_iosapp,3,2019-01-02 -Inferring Forces and Learning Human Utilities From Videos,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhu_Inferring_Forces_and_CVPR_2016_paper.html,CVPR,2016,https://github.com/xiaozhuchacha/ChairPerson,2,2019-01-02 -Weakly Supervised Object Localization With Progressive Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Weakly_Supervised_Object_CVPR_2016_paper.html,CVPR,2016,https://github.com/wupeng78/Weakly-Supervised-Object-Localization-with-Progressive-Domain-Adaptation-CVPR-2016-,2,2019-01-02 -AOD-Net: All-In-One Dehazing Network,http://openaccess.thecvf.com/content_iccv_2017/html/Li_AOD-Net_All-In-One_Dehazing_ICCV_2017_paper.html,ICCV,2017,https://github.com/weber0522bb/AODnet-by-pytorch,6,2019-01-02 -CIDEr: Consensus-Based Image Description Evaluation,http://openaccess.thecvf.com/content_cvpr_2015/html/Vedantam_CIDEr_Consensus-Based_Image_2015_CVPR_paper.html,CVPR,2015,https://github.com/vrama91/cider-matlab,2,2019-01-02 -A Weighted Sparse Sampling and Smoothing Frame Transition Approach for Semantic Fast-Forward First-Person Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Silva_A_Weighted_Sparse_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/verlab/SemanticFastForward_CVPR_2018,2,2019-01-02 -Black Box FDR,http://proceedings.mlr.press/v80/tansey18a.html,ICML,2018,https://github.com/tansey/bb-fdr,4,2019-01-02 -Joint Recovery of Dense Correspondence and Cosegmentation in Two Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Taniai_Joint_Recovery_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/t-taniai/TSS_CVPR2016_Demo,2,2019-01-02 -Conditional Neural Processes,http://proceedings.mlr.press/v80/garnelo18a.html,ICML,2018,https://github.com/suyashnigam/ConditionalNeuralProcesses,2,2019-01-02 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Learning From Online Textual Documents With Noise Suppression,http://openaccess.thecvf.com/content_cvpr_2016/html/Qiao_Less_Is_More_CVPR_2016_paper.html,CVPR,2016,https://github.com/rqiao/zsl_noise_suppression,2,2019-01-02 -Information Constraints on Auto-Encoding Variational Bayes,http://arxiv.org/abs/1805.08672v2,NIPS,2018,https://github.com/romain-lopez/HCV,3,2019-01-02 -Composite Functional Gradient Learning of Generative Adversarial Models,http://proceedings.mlr.press/v80/johnson18a.html,ICML,2018,https://github.com/riejohnson/cfg-gan,2,2019-01-02 -Learning for Active 3D Mapping,http://openaccess.thecvf.com/content_iccv_2017/html/Zimmermann_Learning_for_Active_ICCV_2017_paper.html,ICCV,2017,https://github.com/RheoDesign/AAVS-Beijing,2,2019-01-02 -Efficient Algorithms for Moral Lineage Tracing,http://openaccess.thecvf.com/content_iccv_2017/html/Rempfler_Efficient_Algorithms_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/rempfler/efficient-mlt,2,2019-01-02 -AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms,http://papers.nips.cc/paper/6893-aide-an-algorithm-for-measuring-the-accuracy-of-probabilistic-inference-algorithms.pdf,NIPS,2017,https://github.com/probcomp/nips2017-aide-experiments,2,2019-01-02 -Scalable Levy Process Priors for Spectral Kernel Learning,http://papers.nips.cc/paper/6983-scalable-levy-process-priors-for-spectral-kernel-learning.pdf,NIPS,2017,https://github.com/pjang23/levy-spectral-kernel-learning,2,2019-01-02 -DeLS-3D: Deep Localization and Segmentation With a 3D Semantic Map,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_DeLS-3D_Deep_Localization_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/pengwangucla/DeLS-3D,4,2019-01-02 -Simultaneous Stereo Video Deblurring and Scene Flow Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Pan_Simultaneous_Stereo_Video_CVPR_2017_paper.html,CVPR,2017,https://github.com/panpanfei/data-Simultaneous-Stereo-Video-Deblurring-and-Scene-Flow-Estimation,2,2019-01-02 -A Simple yet Effective Baseline for 3D Human Pose Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Martinez_A_Simple_yet_ICCV_2017_paper.html,ICCV,2017,https://github.com/nulledge/bilinear,4,2019-01-02 -Towards Effective Low-Bitwidth Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhuang_Towards_Effective_Low-Bitwidth_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nowgood/QuantizeCNNModel,5,2019-01-02 -Recognizing Human Actions as the Evolution of Pose Estimation Maps,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Recognizing_Human_Actions_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nkliuyifang/Skeleton-based-Human-Action-Recognition,4,2019-01-02 -Moral Lineage Tracing,http://openaccess.thecvf.com/content_cvpr_2016/html/Jug_Moral_Lineage_Tracing_CVPR_2016_paper.html,CVPR,2016,https://github.com/mpi-inf-cia/moral-lineage-tracing,2,2019-01-02 -Interpolation on the Manifold of K Component GMMs,http://openaccess.thecvf.com/content_iccv_2015/html/Kim_Interpolation_on_the_ICCV_2015_paper.html,ICCV,2015,https://github.com/MLman/kgmm_interpolation,2,2019-01-02 -Teaching Categories to Human Learners With Visual Explanations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Aodha_Teaching_Categories_to_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/macaodha/explain_teach,3,2019-01-02 -A Framework for Evaluating 6-DOF Object Trackers,http://openaccess.thecvf.com/content_ECCV_2018/html/Mathieu_Garon_A_Framework_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/lvsn/6DOF_tracking_evaluation,4,2019-01-02 -Contour Knowledge Transfer for Salient Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Xin_Li_Contour_Knowledge_Transfer_ECCV_2018_paper.html,ECCV,2018,https://github.com/lixin666/C2SNet,5,2019-01-02 -Multi-Layered Gradient Boosting Decision Trees,,NIPS,2018,https://github.com/limberc/ML-GBDT,2,2019-01-02 -Learning Background-Aware Correlation Filters for Visual Tracking,http://openaccess.thecvf.com/content_iccv_2017/html/Galoogahi_Learning_Background-Aware_Correlation_ICCV_2017_paper.html,ICCV,2017,https://github.com/LCAR979/BACF,2,2019-01-02 -Count-Based Exploration with Neural Density Models,http://proceedings.mlr.press/v70/ostrovski17a.html,ICML,2017,https://github.com/kristychoi/pixel_exploration,2,2019-01-02 -Using Locally Corresponding CAD Models for Dense 3D Reconstructions From a Single Image,http://openaccess.thecvf.com/content_cvpr_2017/html/Kong_Using_Locally_Corresponding_CVPR_2017_paper.html,CVPR,2017,https://github.com/kongchen1992/LDCgraph,2,2019-01-02 -Compositional Learning for Human Object Interaction,http://openaccess.thecvf.com/content_ECCV_2018/html/Keizo_Kato_Compositional_Learning_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/kkatocmu/Compositional_Learning,2,2019-01-02 -CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions,http://proceedings.mlr.press/v80/tian18a.html,ICML,2018,https://github.com/kjtian/CoVeR,2,2019-01-02 -Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_Optical_Flow_Guided_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kitsune999/Optical-Flow-Guided-Feature,6,2019-01-02 -Adaptive As-Natural-As-Possible Image Stitching,http://openaccess.thecvf.com/content_cvpr_2015/html/Lin_Adaptive_As-Natural-As-Possible_Image_2015_CVPR_paper.html,CVPR,2015,https://github.com/KANU51/ANAP,2,2019-01-02 -"Look, Listen and Learn",http://openaccess.thecvf.com/content_iccv_2017/html/Arandjelovic_Look_Listen_and_ICCV_2017_paper.html,ICCV,2017,https://github.com/Kajiyu/LLLNet,8,2019-01-02 -Learning and Memorization,http://proceedings.mlr.press/v80/chatterjee18a.html,ICML,2018,https://github.com/jre2/AnkiRPG,2,2019-01-02 -Convex Global 3D Registration With Lagrangian Duality,http://openaccess.thecvf.com/content_cvpr_2017/html/Briales_Convex_Global_3D_CVPR_2017_paper.html,CVPR,2017,https://github.com/jbriales/CVPR17,6,2019-01-02 -Device Placement Optimization with Reinforcement Learning,http://proceedings.mlr.press/v70/mirhoseini17a.html,ICML,2017,https://github.com/indrajeet95/Device-Placement-Optimization-with-Reinforcement-Learning,4,2019-01-02 -Lifelong Learning via Progressive Distillation and Retrospection,http://openaccess.thecvf.com/content_ECCV_2018/html/Saihui_Hou_Progressive_Lifelong_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/hshustc/ECCV18_Lifelong_Learning,3,2019-01-02 -Fitting Low-Rank Tensors in Constant Time,http://papers.nips.cc/paper/6841-fitting-low-rank-tensors-in-constant-time.pdf,NIPS,2017,https://github.com/hayasick/CTFT,2,2019-01-02 -Asynchronous Distributed Variational Gaussian Processes for Regression,,ICML,2017,https://github.com/hao-peng/ADVGP,3,2019-01-02 -Hide-And-Seek: Forcing a Network to Be Meticulous for Weakly-Supervised Object and Action Localization,http://openaccess.thecvf.com/content_iccv_2017/html/Singh_Hide-And-Seek_Forcing_a_ICCV_2017_paper.html,ICCV,2017,https://github.com/goddoe/hide-and-seek,2,2019-01-02 -"Fast, Sample-Efficient Algorithms for Structured Phase Retrieval",http://papers.nips.cc/paper/7077-fast-sample-efficient-algorithms-for-structured-phase-retrieval.pdf,NIPS,2017,https://github.com/GauriJagatap/model-copram,2,2019-01-02 -Reversible Recurrent Neural Networks,,NIPS,2018,https://github.com/gan3sh500/revrnn,12,2019-01-02 -Deep View Morphing,http://openaccess.thecvf.com/content_cvpr_2017/html/Ji_Deep_View_Morphing_CVPR_2017_paper.html,CVPR,2017,https://github.com/Gamrix/cs231n_proj,2,2019-01-02 -Learning Dual Convolutional Neural Networks for Low-Level Vision,http://openaccess.thecvf.com/content_cvpr_2018/papers/Pan_Learning_Dual_Convolutional_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/galad-loth/DualCNN-TF,7,2019-01-02 -Leveraging Node Attributes for Incomplete Relational Data,http://proceedings.mlr.press/v70/zhao17a.html,ICML,2017,https://github.com/ethanhezhao/NARM,2,2019-01-02 -Learning Spatial Regularization With Image-Level Supervisions for Multi-Label Image Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Learning_Spatial_Regularization_CVPR_2017_paper.html,CVPR,2017,https://github.com/Enjia/Spatial-Regularization-Network-in-Tensorflow,6,2019-01-02 -Generative Hierarchical Learning of Sparse FRAME Models,http://openaccess.thecvf.com/content_cvpr_2017/html/Xie_Generative_Hierarchical_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/enijkamp/HS-FRAME,2,2019-01-02 -Low-Dimensionality Calibration Through Local Anisotropic Scaling for Robust Hand Model Personalization,http://openaccess.thecvf.com/content_iccv_2017/html/Remelli_Low-Dimensionality_Calibration_Through_ICCV_2017_paper.html,ICCV,2017,https://github.com/edoRemelli/hadjust,2,2019-01-02 -Image Retrieval Using Scene Graphs,http://openaccess.thecvf.com/content_cvpr_2015/html/Johnson_Image_Retrieval_Using_2015_CVPR_paper.html,CVPR,2015,https://github.com/econser/py_irsg_orig,2,2019-01-02 -Stochastic Gradient Monomial Gamma Sampler,http://proceedings.mlr.press/v70/zhang17a.html,ICML,2017,https://github.com/dreasysnail/SGMGT,2,2019-01-02 -Generalized Semantic Preserving Hashing for N-Label Cross-Modal Retrieval,http://openaccess.thecvf.com/content_cvpr_2017/html/Mandal_Generalized_Semantic_Preserving_CVPR_2017_paper.html,CVPR,2017,https://github.com/devraj89/Generalized-Semantic-Preserving-Hashing-for-N-Label-Cross-Modal-Retrieval,4,2019-01-02 -AdaNet: Adaptive Structural Learning of Artificial Neural Networks,http://proceedings.mlr.press/v70/cortes17a.html,ICML,2017,https://github.com/davidabek1/adanet,3,2019-01-02 -Sub-sampled Cubic Regularization for Non-convex Optimization,http://proceedings.mlr.press/v70/kohler17a.html,ICML,2017,https://github.com/dalab/subsampled_cubic_regularization,4,2019-01-02 -HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning,http://openaccess.thecvf.com/content_ECCV_2018/html/Thomas_Robert_HybridNet_Classification_and_ECCV_2018_paper.html,ECCV,2018,https://github.com/dakshitagrawal97/HybridNet,5,2019-01-02 -Online Sketching Hashing,http://openaccess.thecvf.com/content_cvpr_2015/html/Leng_Online_Sketching_Hashing_2015_CVPR_paper.html,CVPR,2015,https://github.com/cvpr2015-submission/online-sketching-hashing,2,2019-01-02 -Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising,http://openaccess.thecvf.com/content_iccv_2015/html/Xu_Patch_Group_Based_ICCV_2015_paper.html,ICCV,2015,https://github.com/csjunxu/PGPD-ICCV2015,2,2019-01-02 -Single Image Water Hazard Detection using FCN with Reflection Attention Units,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaofeng_Han_Single_Image_Water_ECCV_2018_paper.html,ECCV,2018,https://github.com/Cow911/SingleImageWaterHazardDetectionWithRAU,4,2019-01-02 -Dropout Inference in Bayesian Neural Networks with Alpha-divergences,http://proceedings.mlr.press/v70/li17a.html,ICML,2017,https://github.com/cosmozhang/BBalpha_pytorch,2,2019-01-02 -LaVAN: Localized and Visible Adversarial Noise,http://proceedings.mlr.press/v80/karmon18a.html,ICML,2018,https://github.com/ChesterAiGo/LaVAN_python-tf-,2,2019-01-02 -Generalized Max Pooling,http://openaccess.thecvf.com/content_cvpr_2014/html/Murray_Generalized_Max_Pooling_2014_CVPR_paper.html,CVPR,2014,https://github.com/celisun/Generalized-pooling-functions-CNN,2,2019-01-02 -Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization,http://openaccess.thecvf.com/content_cvpr_2016/html/Lu_Tensor_Robust_Principal_CVPR_2016_paper.html,CVPR,2016,https://github.com/canyilu/Tensor-Robust-Principal-Component-Analysis-TRPCA,4,2019-01-02 -A Wavefront Marching Method for Solving the Eikonal Equation on Cartesian Grids,http://openaccess.thecvf.com/content_iccv_2015/html/Cancela_A_Wavefront_Marching_ICCV_2015_paper.html,ICCV,2015,https://github.com/braisCB/WMM,2,2019-01-02 -From Patches to Images: A Nonparametric Generative Model,http://proceedings.mlr.press/v70/ji17a.html,ICML,2017,https://github.com/bnpy/hdp-grid-image-restoration,2,2019-01-02 -Learning Longer-term Dependencies in RNNs with Auxiliary Losses,http://proceedings.mlr.press/v80/trinh18a.html,ICML,2018,https://github.com/belepi93/rnn-auxiliary-loss,5,2019-01-02 -Learning to Localize Sound Source in Visual Scenes,http://openaccess.thecvf.com/content_cvpr_2018/papers/Senocak_Learning_to_Localize_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ardasnck/learning_to_localize_sound,5,2019-01-02 -Multi-Task Learning for Contextual Bandits,http://papers.nips.cc/paper/7070-multi-task-learning-for-contextual-bandits.pdf,NIPS,2017,https://github.com/aniketde/MultiTaskLearningContextualBandits,2,2019-01-02 -Importance Weighted Transfer of Samples in Reinforcement Learning,http://proceedings.mlr.press/v80/tirinzoni18a.html,ICML,2018,https://github.com/AndreaTirinzoni/iw-transfer-rl,3,2019-01-02 -Configurable Markov Decision Processes,http://proceedings.mlr.press/v80/metelli18a.html,ICML,2018,https://github.com/albertometelli/Configurable-Markov-Decision-Processes-ICML-2018,4,2019-01-02 -Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design,http://proceedings.mlr.press/v80/lyu18a.html,ICML,2018,https://github.com/Alaya-in-Matrix/MACE,6,2019-01-02 -High Order Tensor Formulation for Convolutional Sparse Coding,http://openaccess.thecvf.com/content_iccv_2017/html/Bibi_High_Order_Tensor_ICCV_2017_paper.html,ICCV,2017,https://github.com/adelbibi/Tensor_CSC,2,2019-01-02 -Beyond Filters: Compact Feature Map for Portable Deep Model,http://proceedings.mlr.press/v70/wang17m.html,ICML,2017,https://github.com/a4338324/ICML-2017,2,2019-01-02 -Minimum Delay Moving Object Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Lao_Minimum_Delay_Moving_CVPR_2017_paper.html,CVPR,2017,https://github.com/zsameem/realtime-mdmod,1,2019-01-02 -Saliency Pattern Detection by Ranking Structured Trees,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Saliency_Pattern_Detection_ICCV_2017_paper.html,ICCV,2017,https://github.com/zhulei2016/RST-saliency,3,2019-01-02 -A Modulation Module for Multi-task Learning with Applications in Image Retrieval,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiangyun_Zhao_A_Modulation_Module_ECCV_2018_paper.html,ECCV,2018,https://github.com/Zhaoxiangyun/Multi-Task-Modulation-Module,6,2019-01-02 -Unrolling the Shutter: CNN to Correct Motion Distortions,http://openaccess.thecvf.com/content_cvpr_2017/html/Rengarajan_Unrolling_the_Shutter_CVPR_2017_paper.html,CVPR,2017,https://github.com/yogeshbalaji/CVPR17_Unrolling_the_shutter,2,2019-01-02 -Self-Occlusions and Disocclusions in Causal Video Object Segmentation,http://openaccess.thecvf.com/content_iccv_2015/html/Yang_Self-Occlusions_and_Disocclusions_ICCV_2015_paper.html,ICCV,2015,https://github.com/ycyang12/SODVS,1,2019-01-02 -Stochastic Video Generation with a Learned Prior,http://proceedings.mlr.press/v80/denton18a.html,ICML,2018,https://github.com/yamata2/stochastic-video-generation,2,2019-01-02 -DSLR-Quality Photos on Mobile Devices With Deep Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Ignatov_DSLR-Quality_Photos_on_ICCV_2017_paper.html,ICCV,2017,https://github.com/wuyx/CNN---DSLR-Quality-Photos-on-Mobile-Devices-with-Deep-Convolutional-Networks,1,2019-01-02 -Discovering Potential Correlations via Hypercontractivity,http://papers.nips.cc/paper/7044-discovering-potential-correlations-via-hypercontractivity.pdf,NIPS,2017,https://github.com/wgao9/hypercontractivity,1,2019-01-02 -Primary Object Segmentation in Videos via Alternate Convex Optimization of Foreground and Background Distributions,http://openaccess.thecvf.com/content_cvpr_2016/html/Jang_Primary_Object_Segmentation_CVPR_2016_paper.html,CVPR,2016,https://github.com/wdjang/ACO,1,2019-01-02 -Contour Box: Rejecting Object Proposals Without Explicit Closed Contours,http://openaccess.thecvf.com/content_iccv_2015/html/Lu_Contour_Box_Rejecting_ICCV_2015_paper.html,ICCV,2015,https://github.com/WangHong-yang/contour-box,1,2019-01-02 -Learning Object Interactions and Descriptions for Semantic Image Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Learning_Object_Interactions_CVPR_2017_paper.html,CVPR,2017,https://github.com/wanggrun/IDW-CNN-V2,2,2019-01-02 -Gradient Descent for Spiking Neural Networks,http://arxiv.org/abs/1706.04698v2,NIPS,2018,https://github.com/vikram-mm/Spiking-Neural-Network---Theano-Framework,2,2019-01-02 -DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding,http://proceedings.mlr.press/v80/moreau18a.html,ICML,2018,https://github.com/tomMoral/Dicod,3,2019-01-02 -Adaptive Batch Size for Safe Policy Gradients,http://papers.nips.cc/paper/6950-adaptive-batch-size-for-safe-policy-gradients.pdf,NIPS,2017,https://github.com/T3p/adaptive-batch-size,1,2019-01-02 -Deep Affordance-Grounded Sensorimotor Object Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Thermos_Deep_Affordance-Grounded_Sensorimotor_CVPR_2017_paper.html,CVPR,2017,https://github.com/spthermo/Sensorimotor,1,2019-01-02 -On clustering network-valued data,http://papers.nips.cc/paper/7282-on-clustering-network-valued-data.pdf,NIPS,2017,https://github.com/soumendu041/clustering-network-valued-data,1,2019-01-02 -Computing the Stereo Matching Cost With a Convolutional Neural Network,http://openaccess.thecvf.com/content_cvpr_2015/html/Zbontar_Computing_the_Stereo_2015_CVPR_paper.html,CVPR,2015,https://github.com/soonyk/mc-cnn,1,2019-01-02 -A Projection Free Method for Generalized Eigenvalue Problem With a Nonsmooth Regularizer,http://openaccess.thecvf.com/content_iccv_2015/html/Hwang_A_Projection_Free_ICCV_2015_paper.html,ICCV,2015,https://github.com/shwang54/iccv2015_sjh,1,2019-01-02 -Stochastic Wasserstein Barycenters,http://proceedings.mlr.press/v80/claici18a.html,ICML,2018,https://github.com/sebastian-claici/StochasticWassersteinBarycenters,1,2019-01-02 -Collaborative Deep Learning in Fixed Topology Networks,http://papers.nips.cc/paper/7172-collaborative-deep-learning-in-fixed-topology-networks.pdf,NIPS,2017,https://github.com/SCSLabISU/CDSGD,1,2019-01-02 -Weakly Supervised Dense Video Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Shen_Weakly_Supervised_Dense_CVPR_2017_paper.html,CVPR,2017,https://github.com/SCLinDennis/Weakly-Supervised-Dense-Video-Captioning,2,2019-01-02 -Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation,,NIPS,2018,https://github.com/rwenqi/NBD-GLRA,7,2019-01-02 -Deep Visual-Semantic Alignments for Generating Image Descriptions,http://openaccess.thecvf.com/content_cvpr_2015/html/Karpathy_Deep_Visual-Semantic_Alignments_2015_CVPR_paper.html,CVPR,2015,https://github.com/rszeto/eecs-692-replication-project,1,2019-01-02 -Efficient and Consistent Adversarial Bipartite Matching,http://proceedings.mlr.press/v80/fathony18a.html,ICML,2018,https://github.com/rizalzaf/bipartite-mat,1,2019-01-02 -Gated Feedback Refinement Network for Dense Image Labeling,http://openaccess.thecvf.com/content_cvpr_2017/html/Islam_Gated_Feedback_Refinement_CVPR_2017_paper.html,CVPR,2017,https://github.com/rezaulnkarim/RefinementTest,1,2019-01-02 -Coupled End-to-End Transfer Learning With Generalized Fisher Information,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Coupled_End-to-End_Transfer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/RankingCNN/Coupled-End-to-End-Transfer-Learning-With-Generalized-Fisher-Information,1,2019-01-02 -Expert Gate: Lifelong Learning With a Network of Experts,http://openaccess.thecvf.com/content_cvpr_2017/html/Aljundi_Expert_Gate_Lifelong_CVPR_2017_paper.html,CVPR,2017,https://github.com/rahafaljundi/Expert-Gate,4,2019-01-02 -Task-driven Webpage Saliency,http://openaccess.thecvf.com/content_ECCV_2018/html/Quanlong_Zheng_Task-driven_Webpage_Saliency_ECCV_2018_paper.html,ECCV,2018,https://github.com/quanlzheng/Task-driven-Webpage-Saliency,2,2019-01-02 -A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks,,NIPS,2018,https://github.com/pokaxpoka/deep_Mahalanobis_detector,32,2019-01-02 -Follow the Moving Leader in Deep Learning,http://proceedings.mlr.press/v70/zheng17a.html,ICML,2017,https://github.com/patniharshit/Follow-the-Moving-Leader-in-Deep-Learning,1,2019-01-02 -Unsupervised Semantic Parsing of Video Collections,http://openaccess.thecvf.com/content_iccv_2015/html/Sener_Unsupervised_Semantic_Parsing_ICCV_2015_paper.html,ICCV,2015,https://github.com/ozansener/ICCV2015,1,2019-01-02 -Feature Selective Networks for Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhai_Feature_Selective_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/noido/feature_selective_networks,1,2019-01-02 -Generative Local Metric Learning for Kernel Regression,http://papers.nips.cc/paper/6839-generative-local-metric-learning-for-kernel-regression.pdf,NIPS,2017,https://github.com/nohyung/Nadaraya-Watson-Regression-Metric,1,2019-01-02 -Functional Map of the World,http://openaccess.thecvf.com/content_cvpr_2018/papers/Christie_Functional_Map_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nichochar/zapmap,1,2019-01-02 -Distributionally Robust Graphical Models,,NIPS,2018,https://github.com/Narendhar123/Linear-Regression-Algoritham-,1,2018-10-14 -Robust Budget Allocation via Continuous Submodular Functions,http://proceedings.mlr.press/v70/staib17a.html,ICML,2017,https://github.com/mstaib/robust-budget-allocation-code,1,2019-01-02 -Differentially Private Clustering in High-Dimensional Euclidean Spaces,http://proceedings.mlr.press/v70/balcan17a.html,ICML,2017,https://github.com/mouwenlong/dp-clustering-icml17,1,2019-01-02 -Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Minjun_Li_Unsupervised_Image-to-Image_Translation_ECCV_2018_paper.html,ECCV,2018,https://github.com/minjunli/SCAN,1,2018-10-14 -CartoonGAN: Generative Adversarial Networks for Photo Cartoonization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_CartoonGAN_Generative_Adversarial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MingtaoGuo/CartoonGAN-tensorflow,2,2019-01-02 -Model evidence from nonequilibrium simulations,http://papers.nips.cc/paper/6772-model-evidence-from-nonequilibrium-simulations.pdf,NIPS,2017,https://github.com/michaelhabeck/paths,1,2019-01-02 -On Calibration of Modern Neural Networks,http://proceedings.mlr.press/v70/guo17a.html,ICML,2017,https://github.com/markdtw/temperature-scaling-tensorflow,1,2019-01-02 -CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces,,NIPS,2018,https://github.com/maple-research-lab/CapProNet,3,2019-01-02 -Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees,http://papers.nips.cc/paper/6679-greedy-algorithms-for-cone-constrained-optimization-with-convergence-guarantees.pdf,NIPS,2017,https://github.com/locatelf/cone-greedy,1,2019-01-02 -Defense Against Universal Adversarial Perturbations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Akhtar_Defense_Against_Universal_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/liujianee/Pertrubation_Rectifying_Network,1,2019-01-02 -Inhomogeneous Hypergraph Clustering with Applications,http://papers.nips.cc/paper/6825-inhomogeneous-hypergraph-clustering-with-applications.pdf,NIPS,2017,https://github.com/lipan00123/InHclustering,2,2019-01-02 -SPFTN: A Self-Paced Fine-Tuning Network for Segmenting Objects in Weakly Labelled Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_SPFTN_A_Self-Paced_CVPR_2017_paper.html,CVPR,2017,https://github.com/LeYangNwpu/SPFTN,1,2019-01-02 -Maximum Causal Tsallis Entropy Imitation Learning,http://arxiv.org/abs/1805.08336v2,NIPS,2018,https://github.com/kyungjaelee/MCTEIL,1,2018-10-14 -Matrix Norm Estimation from a Few Entries,http://papers.nips.cc/paper/7221-matrix-norm-estimation-from-a-few-entries.pdf,NIPS,2017,https://github.com/khetan2/Schatten_norm_estimation,1,2019-01-02 -Learning to Group Objects,http://openaccess.thecvf.com/content_cvpr_2014/html/Yanulevskaya_Learning_to_Group_2014_CVPR_paper.html,CVPR,2014,https://github.com/KamilWo/PHP_OOP,1,2019-01-02 -Latent Trees for Estimating Intensity of Facial Action Units,http://openaccess.thecvf.com/content_cvpr_2015/html/Kaltwang_Latent_Trees_for_2015_CVPR_paper.html,CVPR,2015,https://github.com/kaltwang/2015latent,1,2019-01-02 -Laplacian Patch-Based Image Synthesis,http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Laplacian_Patch-Based_Image_CVPR_2016_paper.html,CVPR,2016,https://github.com/KAIST-VCLAB/laplacianinpainting,1,2019-01-02 -Bidirectional Retrieval Made Simple,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wehrmann_Bidirectional_Retrieval_Made_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jwehrmann/chain-vse,3,2019-01-02 -"Online Detection of Action Start in Untrimmed, Streaming Videos",http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Shou_Online_Detection_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/junting/odas,2,2019-01-02 -MarioQA: Answering Questions by Watching Gameplay Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Mun_MarioQA_Answering_Questions_ICCV_2017_paper.html,ICCV,2017,https://github.com/JonghwanMun/MarioQA,5,2019-01-02 -ScaleNet: Guiding Object Proposal Generation in Supermarkets and Beyond,http://openaccess.thecvf.com/content_iccv_2017/html/Qiao_ScaleNet_Guiding_Object_ICCV_2017_paper.html,ICCV,2017,https://github.com/joe-siyuan-qiao/ScaleNet,1,2019-01-02 -Video-Story Composition via Plot Analysis,http://openaccess.thecvf.com/content_cvpr_2016/html/Choi_Video-Story_Composition_via_CVPR_2016_paper.html,CVPR,2016,https://github.com/jinsc37/Video-Story-CVPR16,1,2019-01-02 -Objects2action: Classifying and Localizing Actions Without Any Video Example,http://openaccess.thecvf.com/content_iccv_2015/html/Jain_Objects2action_Classifying_and_ICCV_2015_paper.html,ICCV,2015,https://github.com/JingPG2014/objects2action,1,2019-01-02 -Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy,http://proceedings.mlr.press/v80/yang18c.html,ICML,2018,https://github.com/jiaseny/kdsd,1,2018-09-16 -Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Yu_Video_Paragraph_Captioning_CVPR_2016_paper.html,CVPR,2016,https://github.com/JaywongWang/Video-Paragraph-Captioning,1,2019-01-02 -Fast Algorithms for Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Lavin_Fast_Algorithms_for_CVPR_2016_paper.html,CVPR,2016,https://github.com/istoony/winograd-convolutional-nn,3,2019-01-02 -Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models,http://openaccess.thecvf.com/content_ECCV_2018/html/Dong_Su_Is_Robustness_the_ECCV_2018_paper.html,ECCV,2018,https://github.com/IBM/ImageNet-Robustness,1,2019-01-02 -Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives,,NIPS,2018,https://github.com/IBM/Contrastive-Explanation-Method,3,2019-01-02 -DRACO: Byzantine-resilient Distributed Training via Redundant Gradients,http://proceedings.mlr.press/v80/chen18l.html,ICML,2018,https://github.com/hwang595/Draco,5,2019-01-02 -Learning Spatiotemporal Features With 3D Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2015/html/Tran_Learning_Spatiotemporal_Features_ICCV_2015_paper.html,ICCV,2015,https://github.com/hunter-87/read-c3d-features-numpy,1,2019-01-02 -Priv’IT: Private and Sample Efficient Identity Testing,http://proceedings.mlr.press/v70/cai17a.html,ICML,2017,https://github.com/hoonose/privit,1,2019-01-02 -Deep Adaptive Image Clustering,http://openaccess.thecvf.com/content_iccv_2017/html/Chang_Deep_Adaptive_Image_ICCV_2017_paper.html,ICCV,2017,https://github.com/HongtaoYang/DAC-tensorflow,6,2019-01-02 -Directionally Convolutional Networks for 3D Shape Segmentation,http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Directionally_Convolutional_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/HaotianMXu/3D-Shape-Segmentation-with-Deep-Neural-Networks,1,2019-01-02 -Fast and Effective L0 Gradient Minimization by Region Fusion,http://openaccess.thecvf.com/content_iccv_2015/html/Nguyen_Fast_and_Effective_ICCV_2015_paper.html,ICCV,2015,https://github.com/guqifeng/L0_norm,2,2019-01-02 -Context-Aware Synthesis for Video Frame Interpolation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Niklaus_Context-Aware_Synthesis_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/GeorgeBohw/interpolation,1,2019-01-02 -Geodesic Distance Descriptors,http://openaccess.thecvf.com/content_cvpr_2017/html/Shamai_Geodesic_Distance_Descriptors_CVPR_2017_paper.html,CVPR,2017,https://github.com/fuyangliu/3D-Model-Descriptor,1,2019-01-02 -Generative Modeling of Audible Shapes for Object Perception,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Generative_Modeling_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/FredHuangBia/Sound_ICCV,1,2019-01-02 -Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages,,NIPS,2018,https://github.com/forest-snow/mtanchor_demo,3,2019-01-02 -Online control of the false discovery rate with decaying memory,http://papers.nips.cc/paper/7148-online-control-of-the-false-discovery-rate-with-decaying-memory.pdf,NIPS,2017,https://github.com/fanny-yang/OnlineFDRCode,1,2019-01-02 -COLA: Decentralized Linear Learning,,NIPS,2018,https://github.com/epfml/cola,5,2019-01-02 -Structured Uncertainty Prediction Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Dorta_Structured_Uncertainty_Prediction_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/EhtashamBillah/Acute-Lymphoblastic-Leukemia-cell-classification-using-Bayesian-Convolutional-Neural-Networks,1,2019-01-02 -S3Pool: Pooling With Stochastic Spatial Sampling,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhai_S3Pool_Pooling_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/edgarmedina1801/S3Pool,1,2019-01-02 -Playing hard exploration games by watching YouTube,http://arxiv.org/abs/1805.11592v1,NIPS,2018,https://github.com/dnddnjs/learning-from-youtube,1,2018-10-14 -Highly-Economized Multi-View Binary Compression for Scalable Image Clustering,http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Zhang_Highly-Economized_Multi-View_Binary_ECCV_2018_paper.html,ECCV,2018,https://github.com/DarrenZhangZ/HSIC,1,2018-10-01 -Adversarial PoseNet: A Structure-Aware Convolutional Network for Human Pose Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Adversarial_PoseNet_A_ICCV_2017_paper.html,ICCV,2017,https://github.com/danache/Adversarial-PoseNet,1,2019-01-02 -Fast Zero-Shot Image Tagging,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Fast_Zero-Shot_Image_CVPR_2016_paper.html,CVPR,2016,https://github.com/csueb-research/fast-zero-shot-image-tagging,1,2019-01-02 -MEC: Memory-efficient Convolution for Deep Neural Network,http://proceedings.mlr.press/v70/cho17a.html,ICML,2017,https://github.com/CSshengxy/MEC,4,2019-01-02 -A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liang_A_Hybrid_l1-l0_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/csjunxu/L1L0_TM-CVPR2018,3,2019-01-02 -Multispectral Image Intrinsic Decomposition via Subspace Constraint,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Multispectral_Image_Intrinsic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cianhwang/MIID,2,2019-01-02 -Chi-square Generative Adversarial Network,http://proceedings.mlr.press/v80/tao18b.html,ICML,2018,https://github.com/chenyang-tao/chi2gan,2,2019-01-02 -Co-teaching: Robust Training Deep Neural Networks with Extremely Noisy Labels,,NIPS,2018,https://github.com/char256/co-teaching_bohan_et.al,1,2019-01-02 -Linearly constrained Gaussian processes,http://papers.nips.cc/paper/6721-linearly-constrained-gaussian-processes.pdf,NIPS,2017,https://github.com/carji475/linearly-constrained-gaussian-processes,1,2019-01-02 -A Joint Intrinsic-Extrinsic Prior Model for Retinex,http://openaccess.thecvf.com/content_iccv_2017/html/Cai_A_Joint_Intrinsic-Extrinsic_ICCV_2017_paper.html,ICCV,2017,https://github.com/caibolun/JieP,2,2019-01-02 -Learning unknown ODE models with Gaussian processes,http://proceedings.mlr.press/v80/heinonen18a.html,ICML,2018,https://github.com/cagatayyildiz/npode,1,2019-01-02 -The committee machine: Computational to statistical gaps in learning a two-layers neural network,,NIPS,2018,https://github.com/benjaminaubin/TheCommitteeMachine,1,2019-01-02 -The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities,http://papers.nips.cc/paper/7031-the-expxorcist-nonparametric-graphical-models-via-conditional-exponential-densities.pdf,NIPS,2017,https://github.com/arunsais/Expxorcist,1,2019-01-02 -Found Graph Data and Planted Vertex Covers,http://arxiv.org/abs/1805.01209v1,NIPS,2018,https://github.com/arbenson/FGDnPVC,1,2019-01-02 -Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization,http://proceedings.mlr.press/v80/filstroff18a.html,ICML,2018,https://github.com/alumbreras/MMLE-GaP,1,2019-01-02 -Robust Optimization for Deep Regression,http://openaccess.thecvf.com/content_iccv_2015/html/Belagiannis_Robust_Optimization_for_ICCV_2015_paper.html,ICCV,2015,https://github.com/AIHGF/matconvnet-deepReg,1,2019-01-02 -Unsupervised Hard Example Mining from Videos for Improved Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/SouYoung_Jin_Unsupervised_Hard-Negative_Mining_ECCV_2018_paper.html,ECCV,2018,https://github.com/adiprasad/unsup-hard-negative-mining-mscoco,1,2019-01-02 -3D Part-Based Sparse Tracker With Automatic Synchronization and Registration,http://openaccess.thecvf.com/content_cvpr_2016/html/Bibi_3D_Part-Based_Sparse_CVPR_2016_paper.html,CVPR,2016,https://github.com/adelbibi/3D-Part-Based-Sparse-Tracker-with-Automatic-Synchronization-and-Registration,1,2019-01-02 -Video Acceleration Magnification,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Video_Acceleration_Magnification_CVPR_2017_paper.html,CVPR,2017,https://github.com/acceleration-magnification/acceleration-magnification.github.io,1,2019-01-02 -Video Representation Learning Using Discriminative Pooling,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Video_Representation_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/3xWangDot/SVMP,2,2019-01-02 -Learning Discriminative Video Representations Using Adversarial Perturbations,http://openaccess.thecvf.com/content_ECCV_2018/html/Jue_Wang_Learning_Discriminative_Video_ECCV_2018_paper.html,ECCV,2018,https://github.com/3xWangDot/DSP,2,2019-01-02 -"Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning",http://openaccess.thecvf.com/content_cvpr_2018/papers/Ge_Multi-Evidence_Filtering_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ZYYSzj/Multi-Evidence-Filtering-and-Fusion-WSL,0,2019-01-02 -Stein Points,http://proceedings.mlr.press/v80/chen18f.html,ICML,2018,https://github.com/ZloyChert/Romash.ISO.SteinerPoints,0,2019-01-02 -Deep Defense: Training DNNs with Improved Adversarial Robustness,http://arxiv.org/abs/1803.00404v2,NIPS,2018,https://github.com/ZiangYan/deepdefense.pytorch,8,2019-01-02 -Supervision by Fusion: Towards Unsupervised Learning of Deep Salient Object Detector,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Supervision_by_Fusion_ICCV_2017_paper.html,ICCV,2017,https://github.com/zhangyuygss/caffe-modified,0,2019-01-02 -Active Learning with Logged Data,http://proceedings.mlr.press/v80/yan18a.html,ICML,2018,https://github.com/yyysbysb/al_log_icml18,0,2019-01-02 -Long-Term Recurrent Convolutional Networks for Visual Recognition and Description,http://openaccess.thecvf.com/content_cvpr_2015/html/Donahue_Long-Term_Recurrent_Convolutional_2015_CVPR_paper.html,CVPR,2015,https://github.com/yurisan/Long-term-Recurrent-Convolutional-Networks-for-Visual-Recognition-and-Description,0,2019-01-02 -The Weighted Kendall and High-order Kernels for Permutations,http://proceedings.mlr.press/v80/jiao18a.html,ICML,2018,https://github.com/YunlongJiao/weightedkendall,0,2019-01-02 -On Word Embedding Dimensionality,,NIPS,2018,https://github.com/yukubo/sample_word2vec_skipgram,0,2019-01-02 -DeepPINK: reproducible feature selection in deep neural networks,http://arxiv.org/abs/1809.01185v2,NIPS,2018,https://github.com/younglululu/DeepPINK,0,2019-01-02 -Ego-Surfing First-Person Videos,http://openaccess.thecvf.com/content_cvpr_2015/html/Yonetani_Ego-Surfing_First-Person_Videos_2015_CVPR_paper.html,CVPR,2015,https://github.com/yonetaniryo/corrsearch,0,2019-01-02 -Multiresolution Kernel Approximation for Gaussian Process Regression,http://papers.nips.cc/paper/6964-multiresolution-kernel-approximation-for-gaussian-process-regression.pdf,NIPS,2017,https://github.com/yiding2012/MKA,0,2019-01-02 -Accurate Inference for Adaptive Linear Models,http://proceedings.mlr.press/v80/deshpande18a.html,ICML,2018,https://github.com/yash-deshpande/decorrelating-linear-models,1,2019-01-02 -Modular Generative Adversarial Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Bo_Zhao_Modular_Generative_Adversarial_ECCV_2018_paper.html,ECCV,2018,https://github.com/xjdeng/EasyGAN,0,2019-01-02 -Weighted-Entropy-Based Quantization for Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Weighted-Entropy-Based_Quantization_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/xiaoweiChen/Weighted-Entropy-based-Quantization-for-Deep-Neural-Networks,0,2019-01-02 -End-To-End People Detection in Crowded Scenes,http://openaccess.thecvf.com/content_cvpr_2016/html/Stewart_End-To-End_People_Detection_CVPR_2016_paper.html,CVPR,2016,https://github.com/wuyx/End-to-end-people-detection-in-crowded-scenes,0,2019-01-02 -Towards End-To-End Text Spotting With Convolutional Recurrent Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Li_Towards_End-To-End_Text_ICCV_2017_paper.html,ICCV,2017,https://github.com/wuyenan/-Towards-End-to-end-Text-Spotting-with-Convolutional-Recurrent-Neural-Networks,0,2019-01-02 -A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations,http://proceedings.mlr.press/v80/nie18a.html,ICML,2018,https://github.com/weilinie/BackpropVis,1,2019-01-02 -What If We Do Not Have Multiple Videos of the Same Action? -- Video Action Localization Using Web Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Sultani_What_If_We_CVPR_2016_paper.html,CVPR,2016,https://github.com/WaqasSultani/ActionLocalization_CVPR16,0,2019-01-02 -"Cross-view Action Modeling, Learning and Recognition",http://openaccess.thecvf.com/content_cvpr_2014/html/Wang_Cross-view_Action_Modeling_2014_CVPR_paper.html,CVPR,2014,https://github.com/wangjiangb/crossviewActionRecognition,0,2019-01-02 -Deep Neural Networks with Box Convolutions,,NIPS,2018,https://github.com/vvoluom/Neural-Networks,0,2018-10-01 -ResNet with one-neuron hidden layers is a Universal Approximator,http://arxiv.org/abs/1806.10909v2,NIPS,2018,https://github.com/vinsis/points-in-2d,0,2019-01-02 -Guided Proofreading of Automatic Segmentations for Connectomics,http://openaccess.thecvf.com/content_cvpr_2018/papers/Haehn_Guided_Proofreading_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/VCG/guidedproofreading,0,2019-01-02 -Reducing Network Agnostophobia,,NIPS,2018,https://github.com/Vastlab/Reducing-Network-Agnostophobia,2,2019-01-02 -Gray-box Adversarial Training,http://openaccess.thecvf.com/content_ECCV_2018/html/Vivek_B_S_Gray_box_adversarial_ECCV_2018_paper.html,ECCV,2018,https://github.com/val-iisc/gat,0,2019-01-02 -What Value Do Explicit High Level Concepts Have in Vision to Language Problems?,http://openaccess.thecvf.com/content_cvpr_2016/html/Wu_What_Value_Do_CVPR_2016_paper.html,CVPR,2016,https://github.com/upccpu/-,0,2019-01-02 -Motion-Depth: RGB-D Depth Map Enhancement with Motion and Depth in Complement,http://openaccess.thecvf.com/content_cvpr_2014/html/Hui_Motion-Depth_RGB-D_Depth_2014_CVPR_paper.html,CVPR,2014,https://github.com/twhui/Motion-Depth,0,2019-01-02 -Efficient Point Process Inference for Large-Scale Object Detection,http://openaccess.thecvf.com/content_cvpr_2016/html/Pham_Efficient_Point_Process_CVPR_2016_paper.html,CVPR,2016,https://github.com/trungtpham/point_process_optimisation,0,2019-01-02 -"Real-World Repetition Estimation by Div, Grad and Curl",http://openaccess.thecvf.com/content_cvpr_2018/papers/Runia_Real-World_Repetition_Estimation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tomrunia/RepetitionEstimation,1,2019-01-02 -Efficient Intersection of Three Quadrics and Applications in Computer Vision,http://openaccess.thecvf.com/content_cvpr_2016/html/Kukelova_Efficient_Intersection_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/tolgabirdal/e3q3,0,2019-01-02 -Adaptive Neural Networks for Efficient Inference,http://proceedings.mlr.press/v70/bolukbasi17a.html,ICML,2017,https://github.com/tolga-b/ann,0,2019-01-02 -A Laplacian Framework for Option Discovery in Reinforcement Learning,http://proceedings.mlr.press/v70/machado17a.html,ICML,2017,https://github.com/timguoqk/option_discovery,0,2019-01-02 -SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate,http://proceedings.mlr.press/v80/ramdas18a.html,ICML,2018,https://github.com/tijana-zrnic/SAFFRONcode,0,2019-01-02 -Product Split Trees,http://openaccess.thecvf.com/content_cvpr_2017/html/Babenko_Product_Split_Trees_CVPR_2017_paper.html,CVPR,2017,https://github.com/theherobrinehunter/Mod,1,2019-01-02 -Emotion Recognition in Context,http://openaccess.thecvf.com/content_cvpr_2017/html/Kosti_Emotion_Recognition_in_CVPR_2017_paper.html,CVPR,2017,https://github.com/Thanuja2812/Deep-Neural-Network,0,2019-01-02 -Hybrid Camera Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Camposeco_Hybrid_Camera_Pose_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/TeaganLi/A-Hybrid-3DoF-Pose-Estimation-Method-based-on-Camera-and-Lidar-Data,0,2019-01-02 -Multi-View Subspace Clustering,http://openaccess.thecvf.com/content_iccv_2015/html/Gao_Multi-View_Subspace_Clustering_ICCV_2015_paper.html,ICCV,2015,https://github.com/TaoZhou19/Dual-Shared-Specific-Multi-view-Subspace-Clustering,0,2019-01-02 -Comparison-Based Random Forests,http://proceedings.mlr.press/v80/haghiri18a.html,ICML,2018,https://github.com/SylwiaOliwia2/Decision-tree-random-forest-xgboost-comparison,0,2019-01-02 -Guided Perturbations: Self-Corrective Behavior in Convolutional Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Sankaranarayanan_Guided_Perturbations_Self-Corrective_ICCV_2017_paper.html,ICCV,2017,https://github.com/swamiviv/guided_perturbations,1,2019-01-02 -Non-Blind Deblurring: Handling Kernel Uncertainty With CNNs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Vasu_Non-Blind_Deblurring_Handling_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/subeeshvasu/2018_subeesh_nbd_cvpr,0,2019-01-02 -Object-centered image stitching,http://openaccess.thecvf.com/content_ECCV_2018/html/Charles_Herrmann_Object-centered_image_stitching_ECCV_2018_paper.html,ECCV,2018,https://github.com/StewartNash/img_proc_7,0,2019-01-02 -Topological mixture estimation,http://proceedings.mlr.press/v80/huntsman18a.html,ICML,2018,https://github.com/SteveHuntsmanBAESystems/TopologicalMixtureEstimation,0,2019-01-02 -Non-metric Similarity Graphs for Maximum Inner Product Search,,NIPS,2018,https://github.com/stanis-morozov/ip-nsw,7,2019-01-02 -Gradient Boosted Decision Trees for High Dimensional Sparse Output,http://proceedings.mlr.press/v70/si17a.html,ICML,2017,https://github.com/springdaisy/GBDT,0,2019-01-02 -What Do Deep Networks Like to See?,http://openaccess.thecvf.com/content_cvpr_2018/papers/Palacio_What_Do_Deep_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/spalaciob/normnets,0,2019-01-02 -Analysis by Synthesis: 3D Object Recognition by Object Reconstruction,http://openaccess.thecvf.com/content_cvpr_2014/html/Hejrati_Analysis_by_Synthesis_2014_CVPR_paper.html,CVPR,2014,https://github.com/siqihao95/Musical-Analysis-by-Synthesis,0,2019-01-02 -Neural Network Encapsulation,http://openaccess.thecvf.com/content_ECCV_2018/html/Hongyang_Li_Neural_Network_Encapsulation_ECCV_2018_paper.html,ECCV,2018,https://github.com/sio2boss/k5-spec,0,2019-01-02 -From Source to Target and Back: Symmetric Bi-Directional Adaptive GAN,http://openaccess.thecvf.com/content_cvpr_2018/papers/Russo_From_Source_to_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shubhampachori12110095/GAN,0,2019-01-02 -Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation,,NIPS,2018,https://github.com/shivapratap/AlgorithmicAssurance_NIPS2018,0,2019-01-02 -Estimating Sparse Signals With Smooth Support via Convex Programming and Block Sparsity,http://openaccess.thecvf.com/content_cvpr_2016/html/Shah_Estimating_Sparse_Signals_CVPR_2016_paper.html,CVPR,2016,https://github.com/shahsohil/CoLaMP,0,2019-01-02 -Learning with Abandonment,http://proceedings.mlr.press/v80/schmit18a.html,ICML,2018,https://github.com/schmit/learning-abandonment,0,2019-01-02 -Infinite Feature Selection,http://openaccess.thecvf.com/content_iccv_2015/html/Roffo_Infinite_Feature_Selection_ICCV_2015_paper.html,ICCV,2015,https://github.com/Sadegh28/SINF,0,2019-01-02 -Gaussian Process Conditional Density Estimation,,NIPS,2018,https://github.com/richardbayes/bayes-treed-cde,0,2019-01-02 -Learning SMaLL Predictors,http://arxiv.org/abs/1803.02388v1,NIPS,2018,https://github.com/retropean/mspa-apps,0,2019-01-02 -Diversity-Enhanced Condensation Algorithm and Its Application for Robust and Accurate Endoscope Three-Dimensional Motion Tracking,http://openaccess.thecvf.com/content_cvpr_2014/html/Luo_Diversity-Enhanced_Condensation_Algorithm_2014_CVPR_paper.html,CVPR,2014,https://github.com/renzhe0009/Diversity-Enhanced-Condensation-Algorithm,0,2019-01-02 -Learning to Predict Saliency on Face Images,http://openaccess.thecvf.com/content_iccv_2015/html/Xu_Learning_to_Predict_ICCV_2015_paper.html,ICCV,2015,https://github.com/RenYun2016/Face,0,2019-01-02 -Clustering of Static-Adaptive Correspondences for Deformable Object Tracking,http://openaccess.thecvf.com/content_cvpr_2015/html/Nebehay_Clustering_of_Static-Adaptive_2015_CVPR_paper.html,CVPR,2015,https://github.com/rafaelvareto/CMT-Tracker,0,2019-01-02 -Streaming Principal Component Analysis in Noisy Setting,http://proceedings.mlr.press/v80/marinov18a.html,ICML,2018,https://github.com/r3831/NPCA,0,2019-01-02 -Local and Global Optimization Techniques in Graph-Based Clustering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ikami_Local_and_Global_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/qiao-/thesis_GPU_parallel_EuclideanMST_Multiple_2or3-opt_moves_for_graph_minimization-,0,2019-01-02 -Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees,http://proceedings.mlr.press/v80/taylor18a.html,ICML,2018,https://github.com/QCGroup/quad-lyap-first-order,0,2019-01-02 -Consistent Robust Regression,http://papers.nips.cc/paper/6806-consistent-robust-regression.pdf,NIPS,2017,https://github.com/purushottamkar/rreg,0,2019-01-02 -What Will Happen Next? Forecasting Player Moves in Sports Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Felsen_What_Will_Happen_ICCV_2017_paper.html,ICCV,2017,https://github.com/pulkitag/sports-forecasting,0,2019-01-02 -Nearly Optimal Robust Subspace Tracking,http://proceedings.mlr.press/v80/narayanamurthy18a.html,ICML,2018,https://github.com/praneethmurthy/NORST,0,2019-01-02 -Laplacian Coordinates for Seeded Image Segmentation,http://openaccess.thecvf.com/content_cvpr_2014/html/Casaca_Laplacian_Coordinates_for_2014_CVPR_paper.html,CVPR,2014,https://github.com/pianoza/seproject,0,2019-01-02 -Unsupervised Correlation Analysis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hoshen_Unsupervised_Correlation_Analysis_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/pgyrya/customer_segments,0,2019-01-02 -Learning Abstract Options,,NIPS,2018,https://github.com/petterasla/IECCS,0,2019-01-02 -Smooth Representation Clustering,http://openaccess.thecvf.com/content_cvpr_2014/html/Hu_Smooth_Representation_Clustering_2014_CVPR_paper.html,CVPR,2014,https://github.com/PennStateStatGen/WaveletBasedFunctionalCluster,0,2019-01-02 -Complexity-Adaptive Distance Metric for Object Proposals Generation,http://openaccess.thecvf.com/content_cvpr_2015/html/Xiao_Complexity-Adaptive_Distance_Metric_2015_CVPR_paper.html,CVPR,2015,https://github.com/peacefulxy/CADM,0,2019-01-02 -Policy Optimization as Wasserstein Gradient Flows,http://proceedings.mlr.press/v80/zhang18a.html,ICML,2018,https://github.com/paper-review/ICML2018,0,2019-01-02 -Structured Set Matching Networks for One-Shot Part Labeling,http://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_Structured_Set_Matching_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Oushesh/Structured-Set-Matching-Networks-for-One-Shot-Part-Labeling-readme,0,2019-01-02 -Efficient First-Order Algorithms for Adaptive Signal Denoising,http://proceedings.mlr.press/v80/ostrovskii18a.html,ICML,2018,https://github.com/ostrodmit/AlgoRec,0,2019-01-02 -Best of Both Worlds: Human-Machine Collaboration for Object Annotation,http://openaccess.thecvf.com/content_cvpr_2015/html/Russakovsky_Best_of_Both_2015_CVPR_paper.html,CVPR,2015,https://github.com/orussakovsky/best-of-both-worlds,0,2019-01-02 -Best Response Regression,http://papers.nips.cc/paper/6748-best-response-regression.pdf,NIPS,2017,https://github.com/omerbp/Best-Response-Regression,0,2019-01-02 -Truncating Wide Networks Using Binary Tree Architectures,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Truncating_Wide_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/nutszebra/wide_networks_using_binary_tree,0,2019-01-02 -Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification,http://openaccess.thecvf.com/content_iccv_2015/html/He_Delving_Deep_into_ICCV_2015_paper.html,ICCV,2015,https://github.com/nutszebra/prelu_net,2,2019-01-02 -Unified Embedding and Metric Learning for Zero-Exemplar Event Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Hussein_Unified_Embedding_and_CVPR_2017_paper.html,CVPR,2017,https://github.com/noureldien/unified_embedding,0,2019-01-02 -Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction,,NIPS,2018,https://github.com/nips2018axiomatic/Mapping-Images-to-Scene-Graphs-master,2,2019-01-02 -Unsupervised Learning of Depth and Ego-Motion From Monocular Video Using 3D Geometric Constraints,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mahjourian_Unsupervised_Learning_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Nick36/unsupervised-learning-depth-ego-motion,0,2019-01-02 -Unsupervised Learning of Depth and Ego-Motion From Video,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Unsupervised_Learning_of_CVPR_2017_paper.html,CVPR,2017,https://github.com/Nick36/unsupervised-learning-depth-ego-motion,0,2019-01-02 -Dynamic Time-Of-Flight,http://openaccess.thecvf.com/content_cvpr_2017/html/Schober_Dynamic_Time-Of-Flight_CVPR_2017_paper.html,CVPR,2017,https://github.com/neiljones12/Whackathon2016,0,2019-01-02 -Predict and Constrain: Modeling Cardinality in Deep Structured Prediction,http://proceedings.mlr.press/v80/brukhim18a.html,ICML,2018,https://github.com/Natalybr/predict_and_constrain,1,2019-01-02 -Propagated Image Filtering,http://openaccess.thecvf.com/content_cvpr_2015/html/Chang_Propagated_Image_Filtering_2015_CVPR_paper.html,CVPR,2015,https://github.com/NASA-Planetary-Science/SALTAD,0,2019-01-02 -Processing of missing data by neural networks,http://arxiv.org/abs/1805.07405v2,NIPS,2018,https://github.com/mzkhan2000/TypeNeuralModel,0,2019-01-02 -Comparator Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Weidi_Xie_Comparator_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/Morwenn/comparator-networks,0,2019-01-02 -Linear Ranking Analysis,http://openaccess.thecvf.com/content_cvpr_2014/html/Deng_Linear_Ranking_Analysis_2014_CVPR_paper.html,CVPR,2014,https://github.com/MickyDowns/mine_ncaa_rankings,0,2019-01-02 -Relationship Proposal Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Relationship_Proposal_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/mdxedia/Awsome-Cash,1,2019-01-02 -Semi-supervised Spectral Clustering for Image Set Classification,http://openaccess.thecvf.com/content_cvpr_2014/html/Mahmood_Semi-supervised_Spectral_Clustering_2014_CVPR_paper.html,CVPR,2014,https://github.com/Masoud-Fatemi/Pattern-Recognition,0,2019-01-02 -A Generative Model of People in Clothing,http://openaccess.thecvf.com/content_iccv_2017/html/Lassner_A_Generative_Model_ICCV_2017_paper.html,ICCV,2017,https://github.com/Masaokb/ClothesNet_PyTorch,0,2019-01-02 -SWIFT: Sparse Withdrawal of Inliers in a First Trial,http://openaccess.thecvf.com/content_cvpr_2015/html/Jaberi_SWIFT_Sparse_Withdrawal_2015_CVPR_paper.html,CVPR,2015,https://github.com/mary-jab/SWIFT,0,2019-01-02 -Adaptive Clustering through Semidefinite Programming,http://papers.nips.cc/paper/6776-adaptive-clustering-through-semidefinite-programming.pdf,NIPS,2017,https://github.com/martinroyer/pecok,0,2019-01-02 -Scalable Bayesian Rule Lists,http://proceedings.mlr.press/v70/yang17h.html,ICML,2017,https://github.com/margoseltzer/homebrew-sbrlmod,0,2019-01-02 -Efficient Multiple Instance Metric Learning Using Weakly Supervised Data,http://openaccess.thecvf.com/content_cvpr_2017/html/Law_Efficient_Multiple_Instance_CVPR_2017_paper.html,CVPR,2017,https://github.com/MarcTLaw/MIMLCA,0,2019-01-02 -Variational Bayesian Multiple Instance Learning With Gaussian Processes,http://openaccess.thecvf.com/content_cvpr_2017/html/Haussmann_Variational_Bayesian_Multiple_CVPR_2017_paper.html,CVPR,2017,https://github.com/manuelhaussmann/vgpmil,0,2019-01-02 -Learning Deep Representation for Imbalanced Classification,http://openaccess.thecvf.com/content_cvpr_2016/html/Huang_Learning_Deep_Representation_CVPR_2016_paper.html,CVPR,2016,https://github.com/Makundi/Machine-Learning-IPT-ParrotAI,1,2019-01-02 -Distributed Clustering via LSH Based Data Partitioning,http://proceedings.mlr.press/v80/bhaskara18a.html,ICML,2018,https://github.com/maheshakya/DistClust_via_LSH_L2,0,2019-01-02 -Delayed Impact of Fair Machine Learning,http://proceedings.mlr.press/v80/liu18c.html,ICML,2018,https://github.com/lydiatliu/delayedimpact,2,2019-01-02 -A High-Quality Denoising Dataset for Smartphone Cameras,http://openaccess.thecvf.com/content_cvpr_2018/papers/Abdelhamed_A_High-Quality_Denoising_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/luhannan/mean-fusion-to-denoise-image,0,2019-01-02 -Structured Regression Gradient Boosting,http://openaccess.thecvf.com/content_cvpr_2016/html/Diego_Structured_Regression_Gradient_CVPR_2016_paper.html,CVPR,2016,https://github.com/LJohanna/Project_Python_SpeedDatingData,0,2019-01-02 -Data-Efficient Hierarchical Reinforcement Learning,,NIPS,2018,https://github.com/lizhuoru/aaai17,0,2019-01-02 -Open Category Detection with PAC Guarantees,http://proceedings.mlr.press/v80/liu18e.html,ICML,2018,https://github.com/liusi2019/ocd,1,2019-01-02 -Using Spatial Order to Boost the Elimination of Incorrect Feature Matches,http://openaccess.thecvf.com/content_cvpr_2016/html/Talker_Using_Spatial_Order_CVPR_2016_paper.html,CVPR,2016,https://github.com/liortalker/SpatialOrder,3,2019-01-02 -Efficient Sliding Window Computation for NN-Based Template Matching,http://openaccess.thecvf.com/content_ECCV_2018/html/Lior_Talker_Efficient_Sliding_Window_ECCV_2018_paper.html,ECCV,2018,https://github.com/liortalker/DIWU,2,2019-01-02 -"A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening",http://papers.nips.cc/paper/7264-a-sharp-error-analysis-for-the-fused-lasso-with-application-to-approximate-changepoint-screening.pdf,NIPS,2017,https://github.com/linnylin92/fused_lasso,0,2019-01-02 -Deep Learning Strong Parts for Pedestrian Detection,http://openaccess.thecvf.com/content_iccv_2015/html/Tian_Deep_Learning_Strong_ICCV_2015_paper.html,ICCV,2015,https://github.com/lijinxi1314/Deep_learning_strong_parts,0,2019-01-02 -Boosted Sparse and Low-Rank Tensor Regression,,NIPS,2018,https://github.com/LifangHe/SURF,1,2019-01-02 -Dual Supervised Learning,http://proceedings.mlr.press/v70/xia17a.html,ICML,2017,https://github.com/LifangHe/SDM14_DuSK,0,2019-01-02 -Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior,,NIPS,2018,https://github.com/Learning-and-Intelligent-Systems/meta-bo,0,2019-01-02 -Understanding Classifier Errors by Examining Influential Neighbors,http://openaccess.thecvf.com/content_cvpr_2015/html/Kabra_Understanding_Classifier_Errors_2015_CVPR_paper.html,CVPR,2015,https://github.com/kristinbranson/InfluentialNeighbors,0,2019-01-02 -Co-Occurrence Filter,http://openaccess.thecvf.com/content_cvpr_2017/html/Jevnisek_Co-Occurrence_Filter_CVPR_2017_paper.html,CVPR,2017,https://github.com/kobybibas/CoOccurrenceFilter,0,2019-01-02 -Learning to Assign Orientations to Feature Points,http://openaccess.thecvf.com/content_cvpr_2016/html/Yi_Learning_to_Assign_CVPR_2016_paper.html,CVPR,2016,https://github.com/kmyid/benchmark-orientation,0,2019-01-02 -Multi-Instance Object Segmentation With Occlusion Handling,http://openaccess.thecvf.com/content_cvpr_2015/html/Chen_Multi-Instance_Object_Segmentation_2015_CVPR_paper.html,CVPR,2015,https://github.com/kasertim/ObjectSegmentationOcclusionHandling,0,2019-01-02 -Leveraging Motion Priors in Videos for Improving Human Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Yu-Ting_Chen_Leveraging_Motion_Priors_ECCV_2018_paper.html,ECCV,2018,https://github.com/Jwy-Leo/Leveraging-Motion-Priors-in-Videos-for-Improving-Human-Segmentation,0,2019-01-02 -What Is Around the Camera?,http://openaccess.thecvf.com/content_iccv_2017/html/Georgoulis_What_Is_Around_ICCV_2017_paper.html,ICCV,2017,https://github.com/julianchow/LocationTesting,0,2019-01-02 -Local Convergence Properties of SAGA/Prox-SVRG and Acceleration,http://proceedings.mlr.press/v80/poon18a.html,ICML,2018,https://github.com/jliang993/Local-VRSGD,0,2019-01-02 -Generation and Comprehension of Unambiguous Object Descriptions,http://openaccess.thecvf.com/content_cvpr_2016/html/Mao_Generation_and_Comprehension_CVPR_2016_paper.html,CVPR,2016,https://github.com/jeetp465/Unambiguous-Object-Description,0,2019-01-02 -Large-Scale Stochastic Sampling from the Probability Simplex,http://arxiv.org/abs/1806.07137v1,NIPS,2018,https://github.com/jbaker92/SCIR,1,2019-01-02 -On the Solvability of Viewing Graphs,http://openaccess.thecvf.com/content_ECCV_2018/html/Matthew_Trager_On_the_Solvability_ECCV_2018_paper.html,ECCV,2018,https://github.com/ismummy/Train-Tracker,0,2019-01-02 -Learning Region Features for Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Jiayuan_Gu_Learning_Region_Features_ECCV_2018_paper.html,ECCV,2018,https://github.com/ironmanmark23/opencv_project1,0,2019-01-02 -RGB-Infrared Cross-Modality Person Re-Identification,http://openaccess.thecvf.com/content_iccv_2017/html/Wu_RGB-Infrared_Cross-Modality_Person_ICCV_2017_paper.html,ICCV,2017,https://github.com/InnovArul/rgb_IR_personreid,2,2019-01-02 -Composable Planning with Attributes,http://proceedings.mlr.press/v80/zhang18k.html,ICML,2018,https://github.com/infocampuspvtin/-Web-Designing-training-bangalore,0,2019-01-02 -Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning,http://arxiv.org/abs/1807.03146v1,NIPS,2018,https://github.com/ihankyang/keypoint-network,0,2019-01-02 -Single Image 3D Without a Single 3D Image,http://openaccess.thecvf.com/content_iccv_2015/html/Fouhey_Single_Image_3D_ICCV_2015_paper.html,ICCV,2015,https://github.com/ihankyang/keypoint-network,0,2019-01-02 -Neural Voice Cloning with a Few Samples,http://arxiv.org/abs/1802.06006v2,NIPS,2018,https://github.com/IEEE-NITK/Neural-Voice-Cloning,0,2019-01-02 -ATOMO: Communication-efficient Learning via Atomic Sparsification,http://arxiv.org/abs/1806.04090v2,NIPS,2018,https://github.com/hwang595/ATOMO,1,2019-01-02 -Designing Illuminant Spectral Power Distributions for Surface Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Blasinski_Designing_Illuminant_Spectral_CVPR_2017_paper.html,CVPR,2017,https://github.com/hblasins/optIll,0,2019-01-02 -Enhancing the Spatial Resolution of Stereo Images Using a Parallax Prior,http://openaccess.thecvf.com/content_cvpr_2018/papers/Jeon_Enhancing_the_Spatial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hassanisaadi/stereoSR_tf,0,2019-01-02 -Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization,http://proceedings.mlr.press/v80/wu18g.html,ICML,2018,https://github.com/hang-wu/VRCRM,0,2019-01-02 -Learning to Estimate 3D Hand Pose From Single RGB Images,http://openaccess.thecvf.com/content_iccv_2017/html/Zimmermann_Learning_to_Estimate_ICCV_2017_paper.html,ICCV,2017,https://github.com/hamaskhan/Hand3dRHD,0,2019-01-02 -CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images,http://openaccess.thecvf.com/content_ECCV_2018/html/Sheng_Guo_CurriculumNet_Learning_from_ECCV_2018_paper.html,ECCV,2018,https://github.com/guoshengcv/CurriculumNet,2,2019-01-02 -A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency,http://proceedings.mlr.press/v70/appel17a.html,ICML,2017,https://github.com/GuillaumeCollin/A-Simple-Multi-Class-Boosting-Framework-with-Theoretical-Guarantees-and-Empirical-Proficiency,0,2019-01-02 -Algebraic Variety Models for High-Rank Matrix Completion,http://proceedings.mlr.press/v70/ongie17a.html,ICML,2017,https://github.com/gregongie/vmc,0,2019-01-02 -Dynamic Few-Shot Visual Learning Without Forgetting,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gidaris_Dynamic_Few-Shot_Visual_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/greentfrapp/few-shot-without-forgetting-tensorflow,1,2019-01-02 -Supervised Local Modeling for Interpretability,http://arxiv.org/abs/1807.02910v1,NIPS,2018,https://github.com/GDPlumb/SLIM,0,2019-01-02 -Multimodal Visual Concept Learning With Weakly Supervised Techniques,http://openaccess.thecvf.com/content_cvpr_2018/papers/Bouritsas_Multimodal_Visual_Concept_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/gbouritsas/cvpr18_multimodal_weakly_supervised_learning,0,2019-01-02 -Bayesian Adversarial Learning,,NIPS,2018,https://github.com/GaganNarula/BirdsongGAN_sequencelearning,0,2019-01-02 -Structured Indoor Modeling,http://openaccess.thecvf.com/content_iccv_2015/html/Ikehata_Structured_Indoor_Modeling_ICCV_2015_paper.html,ICCV,2015,https://github.com/furukawa00000/2015_structured_indoor_modeling,0,2019-01-02 -Actions and Attributes From Wholes and Parts,http://openaccess.thecvf.com/content_iccv_2015/html/Gkioxari_Actions_and_Attributes_ICCV_2015_paper.html,ICCV,2015,https://github.com/frankmalcolmkembery/GNU-GENERAL-PUBLIC-LICENSE-Version-3-29-June-2007-Copy,0,2019-01-02 -Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes,http://openaccess.thecvf.com/content_ECCV_2018/html/Fangneng_Zhan_Verisimilar_Image_Synthesis_ECCV_2018_paper.html,ECCV,2018,https://github.com/fnzhan/Verisimilar-Image-Synthesis-for-Accurate-Detection-and-Recognition-of-Texts-in-Scenes,24,2019-01-02 -Human Pose Estimation in Videos,http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Human_Pose_Estimation_ICCV_2015_paper.html,ICCV,2015,https://github.com/FJR-Nancy/TS-LSTM,0,2019-01-02 -Maximum Persistency via Iterative Relaxed Inference With Graphical Models,http://openaccess.thecvf.com/content_cvpr_2015/html/Shekhovtsov_Maximum_Persistency_via_2015_CVPR_paper.html,CVPR,2015,https://github.com/fgrsnau/part_opt,0,2019-01-02 -Density Adaptive Point Set Registration,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lawin_Density_Adaptive_Point_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/felja633/DARE,9,2019-01-02 -Scale-Aware Face Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Hao_Scale-Aware_Face_Detection_CVPR_2017_paper.html,CVPR,2017,https://github.com/eugenelet/Scale-Aware-Face-Detection,0,2019-01-02 -Hamiltonian Variational Auto-Encoder,,NIPS,2018,https://github.com/ericZYZ/HVI-RMHVI-for-VAE,0,2019-01-02 -Adaptive Sampling Probabilities for Non-Smooth Optimization,http://proceedings.mlr.press/v70/namkoong17a.html,ICML,2017,https://github.com/duchi-lab/adaptive-sampling-descent,2,2019-01-02 -Extending Layered Models to 3D Motion,http://openaccess.thecvf.com/content_ECCV_2018/html/Dong_Lao_Extending_Layered_Models_ECCV_2018_paper.html,ECCV,2018,https://github.com/donglao/layers3Dmotion,0,2019-01-02 -Forest-type Regression with General Losses and Robust Forest,http://proceedings.mlr.press/v70/li17e.html,ICML,2017,https://github.com/dma092/Forest-type-Regression-with-General-Losses-and-Robust-Forest-an-implementation,0,2019-01-02 -Beyond the Pixel-Wise Loss for Topology-Aware Delineation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mosinska_Beyond_the_Pixel-Wise_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/dingmyu/Pytorch-Topology-Aware-Delineation,0,2019-01-02 -The Stitched Puppet: A Graphical Model of 3D Human Shape and Pose,http://openaccess.thecvf.com/content_cvpr_2015/html/Zuffi_The_Stitched_Puppet_2015_CVPR_paper.html,CVPR,2015,https://github.com/despicableMinions/stitched-puppet,0,2019-01-02 -"Cut, Glue & Cut: A Fast, Approximate Solver for Multicut Partitioning",http://openaccess.thecvf.com/content_cvpr_2014/html/Beier_Cut_Glue__2014_CVPR_paper.html,CVPR,2014,https://github.com/danoan/GCCS,0,2019-01-02 -Effective Face Frontalization in Unconstrained Images,http://openaccess.thecvf.com/content_cvpr_2015/html/Hassner_Effective_Face_Frontalization_2015_CVPR_paper.html,CVPR,2015,https://github.com/daemonlair/face-frontalization,0,2019-01-02 -Light Field Intrinsics With a Deep Encoder-Decoder Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Alperovich_Light_Field_Intrinsics_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cvia-kn/lf_autoencoder_cvpr2018_code,0,2019-01-02 -Reconfiguring the Imaging Pipeline for Computer Vision,http://openaccess.thecvf.com/content_iccv_2017/html/Buckler_Reconfiguring_the_Imaging_ICCV_2017_paper.html,ICCV,2017,https://github.com/cucapra/vision-plots,0,2019-01-02 -A Holistic Approach to Cross-Channel Image Noise Modeling and Its Application to Image Denoising,http://openaccess.thecvf.com/content_cvpr_2016/html/Nam_A_Holistic_Approach_CVPR_2016_paper.html,CVPR,2016,https://github.com/csjunxu/ccnoise_code_CVPR2016,0,2019-01-02 -A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models,http://proceedings.mlr.press/v80/wang18f.html,ICML,2018,https://github.com/cran/jeek,0,2019-01-02 -Latent Feature Lasso,http://proceedings.mlr.press/v70/yen17a.html,ICML,2017,https://github.com/cran/FLLat,0,2019-01-02 -Bayesian Nonparametric Spectral Estimation,,NIPS,2018,https://github.com/cran/bsplinePsd,0,2019-01-02 -A Linear Generalized Camera Calibration From Three Intersecting Reference Planes,http://openaccess.thecvf.com/content_iccv_2015/html/Nishimura_A_Linear_Generalized_ICCV_2015_paper.html,ICCV,2015,https://github.com/computer-vision/iccv2015,0,2019-01-02 -A Linear Extrinsic Calibration of Kaleidoscopic Imaging System From Single 3D Point,http://openaccess.thecvf.com/content_cvpr_2017/html/Takahashi_A_Linear_Extrinsic_CVPR_2017_paper.html,CVPR,2017,https://github.com/computer-vision/cvpr2017,0,2019-01-02 -ML-MG: Multi-Label Learning With Missing Labels Using a Mixed Graph,http://openaccess.thecvf.com/content_iccv_2015/html/Wu_ML-MG_Multi-Label_Learning_ICCV_2015_paper.html,ICCV,2015,https://github.com/CoderZWei/Multi-label,0,2019-01-02 -Extreme Learning to Rank via Low Rank Assumption,http://proceedings.mlr.press/v80/cheng18a.html,ICML,2018,https://github.com/cmhcbb/Extreme-learning-to-rank-via-low-rank-assumption,0,2019-01-02 -Hierarchical Recurrent Neural Network for Skeleton Based Action Recognition,http://openaccess.thecvf.com/content_cvpr_2015/html/Du_Hierarchical_Recurrent_Neural_2015_CVPR_paper.html,CVPR,2015,https://github.com/chrisjkim/hierarchical-recurrent-neural-network-for-skeleton-based-action-recognition,0,2019-01-02 -A Stable Multi-Scale Kernel for Topological Machine Learning,http://openaccess.thecvf.com/content_cvpr_2015/html/Reininghaus_A_Stable_Multi-Scale_2015_CVPR_paper.html,CVPR,2015,https://github.com/chocojoX/Kernel_for_TDAML,0,2019-01-02 -Fine-Grained Recognition Without Part Annotations,http://openaccess.thecvf.com/content_cvpr_2015/html/Krause_Fine-Grained_Recognition_Without_2015_CVPR_paper.html,CVPR,2015,https://github.com/chenlongcv/OVSNet,0,2019-01-02 -What are You Talking About? Text-to-Image Coreference,http://openaccess.thecvf.com/content_cvpr_2014/html/Kong_What_are_You_2014_CVPR_paper.html,CVPR,2014,https://github.com/chagge/sentences3D,0,2019-01-02 -Cross-View Image Matching for Geo-Localization in Urban Environments,http://openaccess.thecvf.com/content_cvpr_2017/html/Tian_Cross-View_Image_Matching_CVPR_2017_paper.html,CVPR,2017,https://github.com/cc1164/Cross-View-Image-Matching-for-Geo-localization-in-Urban-Environments,0,2019-01-02 -Deep Shape Matching,http://openaccess.thecvf.com/content_ECCV_2018/html/Filip_Radenovic_Deep_Shape_Matching_ECCV_2018_paper.html,ECCV,2018,https://github.com/CaramelYo/shape_matching_with_deep_learning,0,2019-01-02 -Seeing the Arrow of Time,http://openaccess.thecvf.com/content_cvpr_2014/html/Pickup_Seeing_the_Arrow_2014_CVPR_paper.html,CVPR,2014,https://github.com/BoeingX/seeing-the-arrow-of-time,0,2019-01-02 -Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification,http://papers.nips.cc/paper/7004-aggressive-sampling-for-multi-class-to-binary-reduction-with-applications-to-text-classification.pdf,NIPS,2017,https://github.com/bikash617/Aggressive-Sampling-for-Multi-class-to-BinaryReduction,0,2019-01-02 -An Analysis of Visual Question Answering Algorithms,http://openaccess.thecvf.com/content_iccv_2017/html/Kafle_An_Analysis_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/bigman911/Project,0,2019-01-02 -A Boo(n) for Evaluating Architecture Performance,http://proceedings.mlr.press/v80/bajgar18a.html,ICML,2018,https://github.com/bajgar/Boon,0,2019-01-02 -Deep Reinforcement Learning-Based Image Captioning With Embedding Reward,http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_Deep_Reinforcement_Learning-Based_CVPR_2017_paper.html,CVPR,2017,https://github.com/B3-348/DRL-based-Image-Captioning-with-Embedding-Reward,0,2019-01-02 -Interval Tracker: Tracking by Interval Analysis,http://openaccess.thecvf.com/content_cvpr_2014/html/Kwon_Interval_Tracker_Tracking_2014_CVPR_paper.html,CVPR,2014,https://github.com/atanu1982/Major-HIPAA-Survival-Guide,0,2019-01-02 -Webly Supervised Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Jin_Webly_Supervised_Semantic_CVPR_2017_paper.html,CVPR,2017,https://github.com/ascust/WSS,0,2019-01-02 -Image to Image Translation for Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Murez_Image_to_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/artix41/ai-week-talk,0,2019-01-02 -Using Object Information for Spotting Text,http://openaccess.thecvf.com/content_ECCV_2018/html/Shitala_Prasad_Using_Object_Information_ECCV_2018_paper.html,ECCV,2018,https://github.com/arjun1237/Inheritance---Java,0,2019-01-02 -A Universal Analysis of Large-Scale Regularized Least Squares Solutions,http://papers.nips.cc/paper/6930-a-universal-analysis-of-large-scale-regularized-least-squares-solutions.pdf,NIPS,2017,https://github.com/apanahi/NIPS_Paper_1937,0,2019-01-02 -Fast Light Field Reconstruction With Deep Coarse-To-Fine Modeling of Spatial-Angular Clues,http://openaccess.thecvf.com/content_ECCV_2018/html/Henry_W._F._Yeung_Fast_Light_Field_ECCV_2018_paper.html,ECCV,2018,https://github.com/angularsr/LightFieldAngularSR,2,2019-01-02 -A Dataset for Movie Description,http://openaccess.thecvf.com/content_cvpr_2015/html/Rohrbach_A_Dataset_for_2015_CVPR_paper.html,CVPR,2015,https://github.com/aminanima/MovieProject,0,2019-01-02 -Feature Generating Networks for Zero-Shot Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xian_Feature_Generating_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/akku1506/Feature-Generating-Networks-for-ZSL,3,2019-01-02 -AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning,http://proceedings.mlr.press/v80/alaa18b.html,ICML,2018,https://github.com/ahmedmalaa/AutoPrognosis,0,2019-01-02 -Accelerated Spectral Ranking,http://proceedings.mlr.press/v80/agarwal18b.html,ICML,2018,https://github.com/agarpit/asr,0,2019-01-02 -Active Learning for Top-$K$ Rank Aggregation from Noisy Comparisons,http://proceedings.mlr.press/v70/mohajer17a.html,ICML,2017,https://github.com/a-elmahdy/Active-Learning-from-Noisy-Comparisons,0,2019-01-02 -CryptoKnight: Generating and Modelling Compiled Cryptographic Primitives,https://www.mdpi.com/2078-2489/9/9/231,NAN,2018,https://github.com/AbertayMachineLearningGroup/CryptoKnight,13,2019-01-02 -"Detection, localisation and tracking of pallets using machine learning techniques and 2D range data",https://arxiv.org/abs/1803.11254,NCAA,2018,https://github.com/EmaroLab/PDT,5,2019-01-02 +Bridging the Gap Between Value and Policy Based Reinforcement Learning,http://papers.nips.cc/paper/6870-bridging-the-gap-between-value-and-policy-based-reinforcement-learning.pdf,NIPS,2017,https://github.com/tensorflow/models,46593,1/2/2019 +"REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models",http://papers.nips.cc/paper/6856-rebar-low-variance-unbiased-gradient-estimates-for-discrete-latent-variable-models.pdf,NIPS,2017,https://github.com/tensorflow/models,46593,1/2/2019 +Focal Loss for Dense Object Detection,http://openaccess.thecvf.com/content_iccv_2017/html/Lin_Focal_Loss_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/facebookresearch/Detectron,18356,1/2/2019 +Faster R-CNN: Towards Real-Time Object Detectionwith Region Proposal Networks,https://papers.nips.cc/paper/5638-faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks.pdf,NIPS,2015,https://github.com/facebookresearch/Detectron,18356,1/2/2019 +R-FCN: Object Detection via Region-based Fully Convolutional Networks,https://papers.nips.cc/paper/6465-r-fcn-object-detection-via-region-based-fully-convolutional-networks.pdf,NIPS,2016,https://github.com/facebookresearch/Detectron,18356,1/2/2019 +Fast R-CNN,http://openaccess.thecvf.com/content_iccv_2015/html/Girshick_Fast_R-CNN_ICCV_2015_paper.html,ICCV,2015,https://github.com/facebookresearch/Detectron,18356,1/2/2019 +Image Style Transfer Using Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Gatys_Image_Style_Transfer_CVPR_2016_paper.html,CVPR,2016,https://github.com/jcjohnson/neural-style,16435,1/2/2019 +Deep Photo Style Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Luan_Deep_Photo_Style_CVPR_2017_paper.html,CVPR,2017,https://github.com/luanfujun/deep-photo-styletransfer,8655,1/2/2019 +Mask R-CNN,http://openaccess.thecvf.com/content_iccv_2017/html/He_Mask_R-CNN_ICCV_2017_paper.html,ICCV,2017,https://github.com/matterport/Mask_RCNN,9493,1/2/2019 +LightGBM: A Highly Efficient Gradient Boosting Decision Tree,http://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf,NIPS,2017,https://github.com/Microsoft/LightGBM,7536,1/2/2019 +Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation,http://papers.nips.cc/paper/7112-scalable-trust-region-method-for-deep-reinforcement-learning-using-kronecker-factored-approximation.pdf,NIPS,2017,https://github.com/openai/baselines,6449,1/2/2019 +Attention is All you Need,http://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf,NIPS,2017,https://github.com/tensorflow/tensor2tensor,6288,1/2/2019 +Video-to-Video Synthesis,https://arxiv.org/abs/1808.06601,NIPS,2018,https://github.com/NVIDIA/vid2vid,5578,1/2/2019 +Deep Residual Learning for Image Recognition,http://openaccess.thecvf.com/content_cvpr_2016/html/He_Deep_Residual_Learning_CVPR_2016_paper.html,CVPR,2016,https://github.com/KaimingHe/deep-residual-networks,4468,1/2/2019 +Deep Image Prior,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ulyanov_Deep_Image_Prior_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/DmitryUlyanov/deep-image-prior,3736,1/2/2019 +Large Pose 3D Face Reconstruction From a Single Image via Direct Volumetric CNN Regression,http://openaccess.thecvf.com/content_iccv_2017/html/Jackson_Large_Pose_3D_ICCV_2017_paper.html,ICCV,2017,https://github.com/AaronJackson/vrn,3354,1/2/2019 +StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_StarGAN_Unified_Generative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yunjey/StarGAN,3405,1/2/2019 +Convolutional Pose Machines,http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Convolutional_Pose_Machines_CVPR_2016_paper.html,CVPR,2016,https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation,3260,1/2/2019 +Densely Connected Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Densely_Connected_Convolutional_CVPR_2017_paper.html,CVPR,2017,https://github.com/liuzhuang13/DenseNet,3130,1/2/2019 +A Unified Approach to Interpreting Model Predictions,http://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions.pdf,NIPS,2017,https://github.com/slundberg/shap,3122,1/2/2019 +Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network,http://openaccess.thecvf.com/content_ECCV_2018/html/Yao_Feng_Joint_3D_Face_ECCV_2018_paper.html,ECCV,2018,https://github.com/YadiraF/PRNet,2434,1/2/2019 +Learning to See in the Dark,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Learning_to_See_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cchen156/Learning-to-See-in-the-Dark,2326,1/2/2019 +Glow: Generative Flow with Invertible 1x1 Convolutions,http://arxiv.org/abs/1807.03039v2,NIPS,2018,https://github.com/openai/glow,2088,1/2/2019 +Deformable Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Deformable_Convolutional_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/msracver/Deformable-ConvNets,2165,1/2/2019 +"ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games",http://papers.nips.cc/paper/6859-elf-an-extensive-lightweight-and-flexible-research-platform-for-real-time-strategy-games.pdf,NIPS,2017,https://github.com/facebookresearch/ELF,1823,1/2/2019 +Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2014/html/Girshick_Rich_Feature_Hierarchies_2014_CVPR_paper.html,CVPR,2014,https://github.com/rbgirshick/rcnn,1681,1/2/2019 +Fully Convolutional Instance-Aware Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Fully_Convolutional_Instance-Aware_CVPR_2017_paper.html,CVPR,2017,https://github.com/msracver/FCIS,1395,1/2/2019 +PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Qi_PointNet_Deep_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/charlesq34/pointnet,1523,1/2/2019 +Improved Training of Wasserstein GANs,http://papers.nips.cc/paper/7159-improved-training-of-wasserstein-gans.pdf,NIPS,2017,https://github.com/igul222/improved_wgan_training,1405,1/2/2019 +Aggregated Residual Transformations for Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Xie_Aggregated_Residual_Transformations_CVPR_2017_paper.html,CVPR,2017,https://github.com/facebookresearch/ResNeXt,1361,1/2/2019 +Squeeze-and-Excitation Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hujie-frank/SENet,1477,1/2/2019 +Efficient Neural Architecture Search via Parameters Sharing,http://proceedings.mlr.press/v80/pham18a.html,ICML,2018,https://github.com/carpedm20/ENAS-pytorch,1382,1/2/2019 +Multimodal Unsupervised Image-to-image Translation,http://openaccess.thecvf.com/content_ECCV_2018/html/Xun_Huang_Multimodal_Unsupervised_Image-to-image_ECCV_2018_paper.html,ECCV,2018,https://github.com/NVlabs/MUNIT,1296,1/2/2019 +Conditional Random Fields as Recurrent Neural Networks,http://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Conditional_Random_Fields_ICCV_2015_paper.html,ICCV,2015,https://github.com/torrvision/crfasrnn,1189,1/2/2019 +Photographic Image Synthesis With Cascaded Refinement Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Photographic_Image_Synthesis_ICCV_2017_paper.html,ICCV,2017,https://github.com/CQFIO/PhotographicImageSynthesis,1142,1/2/2019 +Unsupervised Image-to-Image Translation Networks,http://papers.nips.cc/paper/6672-unsupervised-image-to-image-translation-networks.pdf,NIPS,2017,https://github.com/mingyuliutw/unit,1205,1/2/2019 +Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Ledig_Photo-Realistic_Single_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/tensorlayer/srgan,1301,1/2/2019 +High-Resolution Image Inpainting Using Multi-Scale Neural Patch Synthesis,http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_High-Resolution_Image_Inpainting_CVPR_2017_paper.html,CVPR,2017,https://github.com/leehomyc/Faster-High-Res-Neural-Inpainting,1072,1/2/2019 +SphereFace: Deep Hypersphere Embedding for Face Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_SphereFace_Deep_Hypersphere_CVPR_2017_paper.html,CVPR,2017,https://github.com/wy1iu/sphereface,1048,1/2/2019 +Bayesian GAN,http://papers.nips.cc/paper/6953-bayesian-gan.pdf,NIPS,2017,https://github.com/andrewgordonwilson/bayesgan,942,1/2/2019 +Deep Feature Flow for Video Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Deep_Feature_Flow_CVPR_2017_paper.html,CVPR,2017,https://github.com/msracver/Deep-Feature-Flow,966,1/2/2019 +Pyramid Scene Parsing Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhao_Pyramid_Scene_Parsing_CVPR_2017_paper.html,CVPR,2017,https://github.com/hszhao/PSPNet,934,1/2/2019 +Non-Local Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Non-Local_Neural_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/facebookresearch/video-nonlocal-net,992,1/2/2019 +Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes,http://papers.nips.cc/paper/7098-efficient-modeling-of-latent-information-in-supervised-learning-using-gaussian-processes.pdf,NIPS,2017,https://github.com/SheffieldML/GPy,906,1/2/2019 +Fully Convolutional Networks for Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2015/html/Long_Fully_Convolutional_Networks_2015_CVPR_paper.html,CVPR,2015,https://github.com/shekkizh/FCN.tensorflow,911,1/2/2019 +Finding Tiny Faces,http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Finding_Tiny_Faces_CVPR_2017_paper.html,CVPR,2017,https://github.com/peiyunh/tiny,856,1/2/2019 +Image Generation From Scene Graphs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Johnson_Image_Generation_From_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/google/sg2im,851,1/2/2019 +Learning to Discover Cross-Domain Relations with Generative Adversarial Networks,http://proceedings.mlr.press/v70/kim17a.html,ICML,2017,https://github.com/carpedm20/DiscoGAN-pytorch,784,1/2/2019 +"YOLO9000: Better, Faster, Stronger",http://openaccess.thecvf.com/content_cvpr_2017/html/Redmon_YOLO9000_Better_Faster_CVPR_2017_paper.html,CVPR,2017,https://github.com/philipperemy/yolo-9000,773,1/2/2019 +Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis,http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Combining_Markov_Random_CVPR_2016_paper.html,CVPR,2016,https://github.com/chuanli11/CNNMRF,731,1/2/2019 +Toward Multimodal Image-to-Image Translation,http://papers.nips.cc/paper/6650-toward-multimodal-image-to-image-translation.pdf,NIPS,2017,https://github.com/junyanz/BiCycleGAN,794,1/2/2019 +Synthetic Data for Text Localisation in Natural Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Gupta_Synthetic_Data_for_CVPR_2016_paper.html,CVPR,2016,https://github.com/ankush-me/SynthText,787,1/2/2019 +Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hara_Can_Spatiotemporal_3D_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kenshohara/3D-ResNets-PyTorch,924,1/2/2019 +Single-Shot Refinement Neural Network for Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Single-Shot_Refinement_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sfzhang15/RefineDet,875,1/2/2019 +FlowNet 2.0: Evolution of Optical Flow Estimation With Deep Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Ilg_FlowNet_2.0_Evolution_CVPR_2017_paper.html,CVPR,2017,https://github.com/lmb-freiburg/flownet2,720,1/2/2019 +PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space,http://papers.nips.cc/paper/7095-pointnet-deep-hierarchical-feature-learning-on-point-sets-in-a-metric-space.pdf,NIPS,2017,https://github.com/charlesq34/pointnet2,772,1/2/2019 +Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks,http://proceedings.mlr.press/v70/finn17a.html,ICML,2017,https://github.com/cbfinn/maml,729,1/2/2019 +GANimation: Anatomically-aware Facial Animation from a Single Image,http://openaccess.thecvf.com/content_ECCV_2018/html/Albert_Pumarola_Anatomically_Coherent_Facial_ECCV_2018_paper.html,ECCV,2018,https://github.com/albertpumarola/GANimation,772,1/2/2019 +Inferring and Executing Programs for Visual Reasoning,http://openaccess.thecvf.com/content_iccv_2017/html/Johnson_Inferring_and_Executing_ICCV_2017_paper.html,ICCV,2017,https://github.com/facebookresearch/clevr-iep,636,1/2/2019 +Channel Pruning for Accelerating Very Deep Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/He_Channel_Pruning_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/yihui-he/channel-pruning,649,1/2/2019 +Dilated Residual Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Yu_Dilated_Residual_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/fyu/drn,640,1/2/2019 +Accelerating Eulerian Fluid Simulation With Convolutional Networks,http://proceedings.mlr.press/v70/tompson17a.html,ICML,2017,https://github.com/google/FluidNet,570,1/2/2019 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Deep Generative Models,http://papers.nips.cc/paper/7174-learning-disentangled-representations-with-semi-supervised-deep-generative-models.pdf,NIPS,2017,https://github.com/probtorch/probtorch,556,1/2/2019 +PointCNN,http://arxiv.org/abs/1801.07791v3,NIPS,2018,https://github.com/yangyanli/PointCNN,607,1/2/2019 +"How Far Are We From Solving the 2D & 3D Face Alignment Problem? (And a Dataset of 230,000 3D Facial Landmarks)",http://openaccess.thecvf.com/content_iccv_2017/html/Bulat_How_Far_Are_ICCV_2017_paper.html,ICCV,2017,https://github.com/1adrianb/2D-and-3D-face-alignment,526,1/2/2019 +Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples,http://proceedings.mlr.press/v80/athalye18a.html,ICML,2018,https://github.com/anishathalye/obfuscated-gradients,535,1/2/2019 +Simple Baselines for Human Pose Estimation and Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Bin_Xiao_Simple_Baselines_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/Microsoft/human-pose-estimation.pytorch,752,1/2/2019 +Regressing Robust and Discriminative 3D Morphable Models With a Very Deep Neural Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Tran_Regressing_Robust_and_CVPR_2017_paper.html,CVPR,2017,https://github.com/anhttran/3dmm_cnn,537,1/2/2019 +Learning From Simulated and Unsupervised Images Through Adversarial Training,http://openaccess.thecvf.com/content_cvpr_2017/html/Shrivastava_Learning_From_Simulated_CVPR_2017_paper.html,CVPR,2017,https://github.com/carpedm20/simulated-unsupervised-tensorflow,492,1/2/2019 +Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space,http://openaccess.thecvf.com/content_cvpr_2017/html/Nguyen_Plug__Play_CVPR_2017_paper.html,CVPR,2017,https://github.com/Evolving-AI-Lab/ppgn,487,1/2/2019 +Taskonomy: Disentangling Task Transfer Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zamir_Taskonomy_Disentangling_Task_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/StanfordVL/taskonomy,502,1/2/2019 +Which Training Methods for GANs do actually Converge?,http://proceedings.mlr.press/v80/mescheder18a.html,ICML,2018,https://github.com/LMescheder/GAN_stability,520,1/2/2019 +Cascaded Pyramid Network for Multi-Person Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Cascaded_Pyramid_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chenyilun95/tf-cpn,497,1/2/2019 +Pelee: A Real-Time Object Detection System on Mobile Devices,https://arxiv.org/pdf/1804.06882.pdf,NIPS,2018,https://github.com/Robert-JunWang/Pelee,548,1/2/2019 +Generative Image Inpainting With Contextual Attention,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Generative_Image_Inpainting_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JiahuiYu/generative_inpainting,609,1/2/2019 +Neural 3D Mesh Renderer,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kato_Neural_3D_Mesh_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hiroharu-kato/neural_renderer,489,1/2/2019 +SSH: Single Stage Headless Face Detector,http://openaccess.thecvf.com/content_iccv_2017/html/Najibi_SSH_Single_Stage_ICCV_2017_paper.html,ICCV,2017,https://github.com/mahyarnajibi/SSH,515,1/2/2019 +"GMS: Grid-based Motion Statistics for 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Convolution,http://openaccess.thecvf.com/content_cvpr_2017/html/Niklaus_Video_Frame_Interpolation_CVPR_2017_paper.html,CVPR,2017,https://github.com/sniklaus/pytorch-sepconv,482,1/2/2019 +Video Frame Interpolation via Adaptive Separable Convolution,http://openaccess.thecvf.com/content_iccv_2017/html/Niklaus_Video_Frame_Interpolation_ICCV_2017_paper.html,ICCV,2017,https://github.com/sniklaus/pytorch-sepconv,482,1/2/2019 +Look at Boundary: A Boundary-Aware Face Alignment Algorithm,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Look_at_Boundary_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wywu/LAB,575,1/2/2019 +Joint Detection and Identification Feature Learning for Person Search,http://openaccess.thecvf.com/content_cvpr_2017/html/Xiao_Joint_Detection_and_CVPR_2017_paper.html,CVPR,2017,https://github.com/ShuangLI59/person_search,459,1/2/2019 +Zero-Shot Recognition via Semantic Embeddings and Knowledge Graphs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Zero-Shot_Recognition_via_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JudyYe/zero-shot-gcn,489,1/2/2019 +Locally Optimized Product Quantization for Approximate Nearest Neighbor Search,http://openaccess.thecvf.com/content_cvpr_2014/html/Kalantidis_Locally_Optimized_Product_2014_CVPR_paper.html,CVPR,2014,https://github.com/yahoo/lopq,437,1/2/2019 +Flow-Guided Feature Aggregation for Video Object Detection,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Flow-Guided_Feature_Aggregation_ICCV_2017_paper.html,ICCV,2017,https://github.com/msracver/Flow-Guided-Feature-Aggregation,436,1/2/2019 +In-Place Activated BatchNorm for Memory-Optimized Training of DNNs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Bulo_In-Place_Activated_BatchNorm_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mapillary/inplace_abn,485,1/2/2019 +End-to-End Recovery of Human Shape and Pose,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kanazawa_End-to-End_Recovery_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/akanazawa/hmr,502,1/2/2019 +Recurrent Highway Networks,http://proceedings.mlr.press/v70/zilly17a.html,ICML,2017,https://github.com/julian121266/RecurrentHighwayNetworks,397,1/2/2019 +ICNet for Real-Time Semantic Segmentation on High-Resolution Images,http://openaccess.thecvf.com/content_ECCV_2018/html/Hengshuang_Zhao_ICNet_for_Real-Time_ECCV_2018_paper.html,ECCV,2018,https://github.com/hszhao/ICNet,415,1/2/2019 +Deep Image Matting,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Deep_Image_Matting_CVPR_2017_paper.html,CVPR,2017,https://github.com/Joker316701882/Deep-Image-Matting,434,1/2/2019 +The Unreasonable Effectiveness of Deep Features as a Perceptual Metric,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_The_Unreasonable_Effectiveness_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/richzhang/PerceptualSimilarity,447,1/2/2019 +Detect to Track and Track to Detect,http://openaccess.thecvf.com/content_iccv_2017/html/Feichtenhofer_Detect_to_Track_ICCV_2017_paper.html,ICCV,2017,https://github.com/feichtenhofer/Detect-Track,387,1/2/2019 +Distractor-aware Siamese Networks for Visual Object Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Zhu_Distractor-aware_Siamese_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/foolwood/DaSiamRPN,545,1/2/2019 +Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results,http://papers.nips.cc/paper/6719-mean-teachers-are-better-role-models-weight-averaged-consistency-targets-improve-semi-supervised-deep-learning-results.pdf,NIPS,2017,https://github.com/CuriousAI/mean-teacher/,347,9/16/2018 +Frustum PointNets for 3D Object Detection From RGB-D Data,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Frustum_PointNets_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/charlesq34/frustum-pointnets,434,1/2/2019 +Efficient Interactive Annotation of Segmentation Datasets With Polygon-RNN++,http://openaccess.thecvf.com/content_cvpr_2018/papers/Acuna_Efficient_Interactive_Annotation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/fidler-lab/polyrnn-pp-pytorch,397,1/2/2019 +Annotating Object Instances With a Polygon-RNN,http://openaccess.thecvf.com/content_cvpr_2017/html/Castrejon_Annotating_Object_Instances_CVPR_2017_paper.html,CVPR,2017,https://github.com/fidler-lab/polyrnn-pp-pytorch,397,1/2/2019 +RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_RefineNet_Multi-Path_Refinement_CVPR_2017_paper.html,CVPR,2017,https://github.com/guosheng/refinenet,379,1/2/2019 +Learning Multi-Domain Convolutional Neural Networks for Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2016/html/Nam_Learning_Multi-Domain_Convolutional_CVPR_2016_paper.html,CVPR,2016,https://github.com/HyeonseobNam/MDNet,350,1/2/2019 +Gibson Env: Real-World Perception for Embodied Agents,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xia_Gibson_Env_Real-World_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/StanfordVL/GibsonEnv,385,1/2/2019 +Deep Lattice Networks and Partial Monotonic Functions,http://papers.nips.cc/paper/6891-deep-lattice-networks-and-partial-monotonic-functions.pdf,NIPS,2017,https://github.com/tensorflow/lattice,349,1/2/2019 +RON: Reverse Connection With Objectness Prior Networks for Object Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Kong_RON_Reverse_Connection_CVPR_2017_paper.html,CVPR,2017,https://github.com/taokong/RON,345,1/2/2019 +Detecting Oriented Text in Natural Images by Linking Segments,http://openaccess.thecvf.com/content_cvpr_2017/html/Shi_Detecting_Oriented_Text_CVPR_2017_paper.html,CVPR,2017,https://github.com/dengdan/seglink,364,1/2/2019 +Universal Style Transfer via Feature Transforms,http://papers.nips.cc/paper/6642-universal-style-transfer-via-feature-transforms.pdf,NIPS,2017,https://github.com/Yijunmaverick/UniversalStyleTransfer,344,1/2/2019 +Learning Deep Features for Discriminative Localization,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhou_Learning_Deep_Features_CVPR_2016_paper.html,CVPR,2016,https://github.com/jazzsaxmafia/Weakly_detector,323,1/2/2019 +Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mascharka_Transparency_by_Design_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/davidmascharka/tbd-nets,317,1/2/2019 +Soccer on Your 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Pose",http://openaccess.thecvf.com/content_cvpr_2018/papers/Yin_GeoNet_Unsupervised_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yzcjtr/GeoNet,359,1/2/2019 +GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_GeoNet_Geometric_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yzcjtr/GeoNet,359,1/2/2019 +One-Shot Video Object Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Caelles_One-Shot_Video_Object_CVPR_2017_paper.html,CVPR,2017,https://github.com/scaelles/OSVOS-TensorFlow,316,1/2/2019 +Neural Baby Talk,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lu_Neural_Baby_Talk_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiasenlu/NeuralBabyTalk,332,1/2/2019 +Learning Deconvolution Network for Semantic Segmentation,http://openaccess.thecvf.com/content_iccv_2015/html/Noh_Learning_Deconvolution_Network_ICCV_2015_paper.html,ICCV,2015,https://github.com/HyeonwooNoh/DeconvNet,296,1/2/2019 +Efficient softmax approximation for GPUs,http://proceedings.mlr.press/v70/grave17a.html,ICML,2017,https://github.com/facebookresearch/adaptive-softmax,304,1/2/2019 +Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution,http://openaccess.thecvf.com/content_cvpr_2017/html/Lai_Deep_Laplacian_Pyramid_CVPR_2017_paper.html,CVPR,2017,https://github.com/phoenix104104/LapSRN,301,1/2/2019 +Learning to Track: Online Multi-Object Tracking by Decision Making,http://openaccess.thecvf.com/content_iccv_2015/html/Xiang_Learning_to_Track_ICCV_2015_paper.html,ICCV,2015,https://github.com/yuxng/MDP_Tracking,308,1/2/2019 +Learning to Compare Image Patches via Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2015/html/Zagoruyko_Learning_to_Compare_2015_CVPR_paper.html,CVPR,2015,https://github.com/szagoruyko/cvpr15deepcompare,300,1/2/2019 +Acquisition of Localization Confidence for Accurate Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Borui_Jiang_Acquisition_of_Localization_ECCV_2018_paper.html,ECCV,2018,https://github.com/vacancy/PreciseRoIPooling,384,1/2/2019 +"PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume",http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_PWC-Net_CNNs_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/NVlabs/PWC-Net,398,1/2/2019 +Pixel Recursive Super Resolution,http://openaccess.thecvf.com/content_iccv_2017/html/Dahl_Pixel_Recursive_Super_ICCV_2017_paper.html,ICCV,2017,https://github.com/nilboy/pixel-recursive-super-resolution,301,1/2/2019 +The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Berman_The_LovaSz-Softmax_Loss_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/bermanmaxim/LovaszSoftmax,416,1/2/2019 +Residual Attention Network for Image Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Residual_Attention_Network_CVPR_2017_paper.html,CVPR,2017,https://github.com/fwang91/residual-attention-network,329,1/2/2019 +OctNet: Learning Deep 3D Representations at High Resolutions,http://openaccess.thecvf.com/content_cvpr_2017/html/Riegler_OctNet_Learning_Deep_CVPR_2017_paper.html,CVPR,2017,https://github.com/griegler/octnet,302,1/2/2019 +Dilated Recurrent Neural Networks,http://papers.nips.cc/paper/6613-dilated-recurrent-neural-networks.pdf,NIPS,2017,https://github.com/code-terminator/DilatedRNN,285,1/2/2019 +Fast End-to-End Trainable Guided 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Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Kim_Accurate_Image_Super-Resolution_CVPR_2016_paper.html,CVPR,2016,https://github.com/Jongchan/tensorflow-vdsr,182,1/2/2019 +Multi-View 3D Object Detection Network for Autonomous Driving,http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_Multi-View_3D_Object_CVPR_2017_paper.html,CVPR,2017,https://github.com/bostondiditeam/MV3D,199,1/2/2019 +Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment With Limited Resources,http://openaccess.thecvf.com/content_iccv_2017/html/Bulat_Binarized_Convolutional_Landmark_ICCV_2017_paper.html,ICCV,2017,https://github.com/1adrianb/binary-human-pose-estimation,175,1/2/2019 +Learning Efficient Convolutional Networks Through Network Slimming,http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Learning_Efficient_Convolutional_ICCV_2017_paper.html,ICCV,2017,https://github.com/liuzhuang13/slimming,186,1/2/2019 +Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis,http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Beyond_Face_Rotation_ICCV_2017_paper.html,ICCV,2017,https://github.com/HRLTY/TP-GAN,202,1/2/2019 +GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium,http://papers.nips.cc/paper/7240-gans-trained-by-a-two-time-scale-update-rule-converge-to-a-local-nash-equilibrium.pdf,NIPS,2017,https://github.com/bioinf-jku/TTUR,229,1/2/2019 +Render for CNN: Viewpoint Estimation in Images Using CNNs Trained With Rendered 3D Model Views,http://openaccess.thecvf.com/content_iccv_2015/html/Su_Render_for_CNN_ICCV_2015_paper.html,ICCV,2015,https://github.com/ShapeNet/RenderForCNN,176,1/2/2019 +Realtime Edge-Based Visual Odometry for a Monocular Camera,http://openaccess.thecvf.com/content_iccv_2015/html/Tarrio_Realtime_Edge-Based_Visual_ICCV_2015_paper.html,ICCV,2015,https://github.com/JuanTarrio/rebvo,175,1/2/2019 +Fast Image Processing With Fully-Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Fast_Image_Processing_ICCV_2017_paper.html,ICCV,2017,https://github.com/CQFIO/FastImageProcessing,180,1/2/2019 +Temporal Action Localization in Untrimmed Videos via Multi-Stage CNNs,http://openaccess.thecvf.com/content_cvpr_2016/html/Shou_Temporal_Action_Localization_CVPR_2016_paper.html,CVPR,2016,https://github.com/zhengshou/scnn,167,1/2/2019 +Scene Graph Generation by Iterative Message Passing,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Scene_Graph_Generation_CVPR_2017_paper.html,CVPR,2017,https://github.com/danfeiX/scene-graph-TF-release,182,1/2/2019 +Attentive Generative Adversarial Network for Raindrop Removal From a Single Image,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qian_Attentive_Generative_Adversarial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rui1996/DeRaindrop,186,1/2/2019 +Single View Stereo 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Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gupta_Social_GAN_Socially_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/agrimgupta92/sgan,178,1/2/2019 +LocNet: Improving Localization Accuracy for Object Detection,http://openaccess.thecvf.com/content_cvpr_2016/html/Gidaris_LocNet_Improving_Localization_CVPR_2016_paper.html,CVPR,2016,https://github.com/gidariss/LocNet,155,1/2/2019 +ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_ST-GAN_Spatial_Transformer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chenhsuanlin/spatial-transformer-GAN,179,1/2/2019 +Image Super-Resolution via Deep Recursive Residual Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Tai_Image_Super-Resolution_via_CVPR_2017_paper.html,CVPR,2017,https://github.com/tyshiwo/DRRN_CVPR17,163,1/2/2019 +Input Convex Neural Networks,http://proceedings.mlr.press/v70/amos17b.html,ICML,2017,https://github.com/locuslab/icnn,159,1/2/2019 +Understanding Deep Image Representations by Inverting Them,http://openaccess.thecvf.com/content_cvpr_2015/html/Mahendran_Understanding_Deep_Image_2015_CVPR_paper.html,CVPR,2015,https://github.com/aravindhm/deep-goggle,154,1/2/2019 +Evolved Policy Gradients,http://arxiv.org/abs/1802.04821v2,NIPS,2018,https://github.com/openai/EPG,160,1/2/2019 +Oriented Response Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Oriented_Response_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/ZhouYanzhao/ORN,157,1/2/2019 +Large-Scale Point Cloud Semantic Segmentation With Superpoint Graphs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Landrieu_Large-Scale_Point_Cloud_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/loicland/superpoint_graph,197,1/2/2019 +Optimizing Video Object Detection via a Scale-Time Lattice,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Optimizing_Video_Object_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hellock/scale-time-lattice,168,1/2/2019 +Learning Multiple Tasks with Multilinear Relationship Networks,http://papers.nips.cc/paper/6757-learning-multiple-tasks-with-multilinear-relationship-networks.pdf,NIPS,2017,https://github.com/thuml/Xlearn,178,1/2/2019 +Face Alignment at 3000 FPS via Regressing Local Binary Features,http://openaccess.thecvf.com/content_cvpr_2014/html/Ren_Face_Alignment_at_2014_CVPR_paper.html,CVPR,2014,https://github.com/luoyetx/face-alignment-at-3000fps,164,1/2/2019 +Learning Cross-Modal Embeddings for Cooking Recipes and Food Images,http://openaccess.thecvf.com/content_cvpr_2017/html/Salvador_Learning_Cross-Modal_Embeddings_CVPR_2017_paper.html,CVPR,2017,https://github.com/torralba-lab/im2recipe,160,1/2/2019 +Learning Category-Specific Mesh Reconstruction from Image Collections,http://openaccess.thecvf.com/content_ECCV_2018/html/Angjoo_Kanazawa_Learning_Category-Specific_Mesh_ECCV_2018_paper.html,ECCV,2018,https://github.com/akanazawa/cmr,176,1/2/2019 +Group Normalization,http://openaccess.thecvf.com/content_ECCV_2018/html/Yuxin_Wu_Group_Normalization_ECCV_2018_paper.html,ECCV,2018,https://github.com/shaohua0116/Group-Normalization-Tensorflow,175,1/2/2019 +On Human Motion Prediction Using Recurrent Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Martinez_On_Human_Motion_CVPR_2017_paper.html,CVPR,2017,https://github.com/una-dinosauria/human-motion-prediction,167,1/2/2019 +Language Modeling with Recurrent Highway Hypernetworks,http://papers.nips.cc/paper/6919-language-modeling-with-recurrent-highway-hypernetworks.pdf,NIPS,2017,https://github.com/jsuarez5341/Recurrent-Highway-Hypernetworks-NIPS,141,1/2/2019 +Context-Aware CNNs for Person Head 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Prediction,http://openaccess.thecvf.com/content_cvpr_2016/html/Pan_Shallow_and_Deep_CVPR_2016_paper.html,CVPR,2016,https://github.com/imatge-upc/saliency-2016-cvpr,153,1/2/2019 +ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_ShuffleNet_An_Extremely_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/camel007/Caffe-ShuffleNet,152,1/2/2019 +Axiomatic Attribution for Deep Networks,http://proceedings.mlr.press/v70/sundararajan17a.html,ICML,2017,https://github.com/hiranumn/IntegratedGradients,146,1/2/2019 +Compact Bilinear Pooling,http://openaccess.thecvf.com/content_cvpr_2016/html/Gao_Compact_Bilinear_Pooling_CVPR_2016_paper.html,CVPR,2016,https://github.com/gy20073/compact_bilinear_pooling,148,1/2/2019 +Simple Does It: Weakly Supervised Instance and Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Khoreva_Simple_Does_It_CVPR_2017_paper.html,CVPR,2017,https://github.com/philferriere/tfwss,159,1/2/2019 +Low-Shot Visual Recognition by Shrinking and Hallucinating Features,http://openaccess.thecvf.com/content_iccv_2017/html/Hariharan_Low-Shot_Visual_Recognition_ICCV_2017_paper.html,ICCV,2017,https://github.com/facebookresearch/low-shot-shrink-hallucinate,158,1/2/2019 +BSN: Boundary Sensitive Network for Temporal Action Proposal Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Tianwei_Lin_BSN_Boundary_Sensitive_ECCV_2018_paper.html,ECCV,2018,https://github.com/wzmsltw/BSN-boundary-sensitive-network,175,1/2/2019 +Deep Feature Interpolation for Image Content Changes,http://openaccess.thecvf.com/content_cvpr_2017/html/Upchurch_Deep_Feature_Interpolation_CVPR_2017_paper.html,CVPR,2017,https://github.com/paulu/deepfeatinterp,170,1/2/2019 +Deep Clustering for Unsupervised Learning of Visual Features,http://openaccess.thecvf.com/content_ECCV_2018/html/Mathilde_Caron_Deep_Clustering_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/facebookresearch/deepcluster,302,1/2/2019 +Learning a Single Convolutional Super-Resolution Network for Multiple Degradations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Learning_a_Single_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cszn/SRMD,169,1/2/2019 +Facelet-Bank for Fast Portrait Manipulation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Facelet-Bank_for_Fast_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yingcong/Facelet_Bank,150,1/2/2019 +Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning,http://papers.nips.cc/paper/6974-interpolated-policy-gradient-merging-on-policy-and-off-policy-gradient-estimation-for-deep-reinforcement-learning.pdf,NIPS,2017,https://github.com/shaneshixiang/rllabplusplus,138,1/2/2019 +Learning Compact Binary Descriptors With Unsupervised Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Lin_Learning_Compact_Binary_CVPR_2016_paper.html,CVPR,2016,https://github.com/kevinlin311tw/cvpr16-deepbit,144,1/2/2019 +Image Super-Resolution Using Very Deep Residual Channel Attention Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Yulun_Zhang_Image_Super-Resolution_Using_ECCV_2018_paper.html,ECCV,2018,https://github.com/yulunzhang/RCAN,234,1/2/2019 +ECO: Efficient Convolutional Network for Online Video Understanding,http://openaccess.thecvf.com/content_ECCV_2018/html/Mohammadreza_Zolfaghari_ECO_Efficient_Convolutional_ECCV_2018_paper.html,ECCV,2018,https://github.com/mzolfaghari/ECO-efficient-video-understanding,180,1/2/2019 +PlaneNet: Piece-Wise Planar Reconstruction From a Single RGB Image,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_PlaneNet_Piece-Wise_Planar_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/art-programmer/PlaneNet,164,1/2/2019 +Self-Imitation Learning,http://proceedings.mlr.press/v80/oh18b.html,ICML,2018,https://github.com/junhyukoh/self-imitation-learning,145,1/2/2019 +Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks,http://proceedings.mlr.press/v70/mescheder17a.html,ICML,2017,https://github.com/LMescheder/AdversarialVariationalBayes,147,1/2/2019 +Residual Dense Network for Image Super-Resolution,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Residual_Dense_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yulunzhang/RDN,163,1/2/2019 +Attend to You: Personalized Image Captioning With Context Sequence Memory Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Attend_to_You_CVPR_2017_paper.html,CVPR,2017,https://github.com/cesc-park/attend2u,143,1/2/2019 +Face Alignment by Coarse-to-Fine Shape Searching,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html,CVPR,2015,https://github.com/zhusz/CVPR15-CFSS,140,1/2/2019 +Triple Generative Adversarial Nets,http://papers.nips.cc/paper/6997-triple-generative-adversarial-nets.pdf,NIPS,2017,https://github.com/zhenxuan00/triple-gan,138,1/2/2019 +Embodied Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Das_Embodied_Question_Answering_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/facebookresearch/EmbodiedQA,162,1/2/2019 +Conditional Similarity Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Veit_Conditional_Similarity_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/andreasveit/conditional-similarity-networks,142,1/2/2019 +Two-Stream Convolutional Networks for Dynamic Texture Synthesis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tesfaldet_Two-Stream_Convolutional_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ryersonvisionlab/two-stream-dyntex-synth,141,1/2/2019 +Unsupervised Cross-Dataset Person Re-Identification by Transfer Learning of Spatial-Temporal Patterns,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lv_Unsupervised_Cross-Dataset_Person_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ahangchen/TFusion,166,1/2/2019 +Attentive Recurrent Comparators,http://proceedings.mlr.press/v70/shyam17a.html,ICML,2017,https://github.com/sanyam5/arc-pytorch,136,1/2/2019 +One-Sided Unsupervised Domain Mapping,http://papers.nips.cc/paper/6677-one-sided-unsupervised-domain-mapping.pdf,NIPS,2017,https://github.com/sagiebenaim/DistanceGAN,137,1/2/2019 +Densely Connected Pyramid Dehazing Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Densely_Connected_Pyramid_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hezhangsprinter/DCPDN,155,1/2/2019 +Detecting Visual Relationships With Deep Relational Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Dai_Detecting_Visual_Relationships_CVPR_2017_paper.html,CVPR,2017,https://github.com/doubledaibo/drnet_cvpr2017,137,1/2/2019 +Rethinking the Inception Architecture for Computer Vision,http://openaccess.thecvf.com/content_cvpr_2016/html/Szegedy_Rethinking_the_Inception_CVPR_2016_paper.html,CVPR,2016,https://github.com/Moodstocks/inception-v3.torch,130,1/2/2019 +Show and Tell: A Neural Image Caption Generator,http://openaccess.thecvf.com/content_cvpr_2015/html/Vinyals_Show_and_Tell_2015_CVPR_paper.html,CVPR,2015,https://github.com/KranthiGV/Pretrained-Show-and-Tell-model,141,1/2/2019 +Camera Style Adaptation for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhong_Camera_Style_Adaptation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhunzhong07/CamStyle,159,1/2/2019 +Neural Motifs: Scene Graph Parsing With Global Context,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zellers_Neural_Motifs_Scene_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rowanz/neural-motifs,171,1/2/2019 +Gradient Episodic Memory for Continual Learning,http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf,NIPS,2017,https://github.com/facebookresearch/GradientEpisodicMemory,146,1/2/2019 +CREST: Convolutional Residual Learning for Visual Tracking,http://openaccess.thecvf.com/content_iccv_2017/html/Song_CREST_Convolutional_Residual_ICCV_2017_paper.html,ICCV,2017,https://github.com/ybsong00/CREST-Release,126,1/2/2019 +Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer,http://openaccess.thecvf.com/content_cvpr_2018/papers/Fang_Weakly_and_Semi_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MVIG-SJTU/WSHP,159,1/2/2019 +Controlling Perceptual Factors in Neural Style Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Gatys_Controlling_Perceptual_Factors_CVPR_2017_paper.html,CVPR,2017,https://github.com/leongatys/NeuralImageSynthesis,130,1/2/2019 +LSTM Pose Machines,http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_LSTM_Pose_Machines_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lawy623/LSTM_Pose_Machines,141,1/2/2019 +Relational recurrent neural networks,https://arxiv.org/abs/1806.01822,NIPS,2018,https://github.com/L0SG/relational-rnn-pytorch,157,1/2/2019 +Multi-Context Attention for Human Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Chu_Multi-Context_Attention_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/bearpaw/pose-attention,131,1/2/2019 +SO-Net: Self-Organizing Network for Point Cloud Analysis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_SO-Net_Self-Organizing_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lijx10/SO-Net,152,1/2/2019 +SegFlow: Joint Learning for Video Object Segmentation and Optical Flow,http://openaccess.thecvf.com/content_iccv_2017/html/Cheng_SegFlow_Joint_Learning_ICCV_2017_paper.html,ICCV,2017,https://github.com/JingchunCheng/SegFlow,127,1/2/2019 +Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach,http://openaccess.thecvf.com/content_iccv_2017/html/Zhou_Towards_3D_Human_ICCV_2017_paper.html,ICCV,2017,https://github.com/xingyizhou/pose-hg-3d,136,1/2/2019 +Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Deng_Image-Image_Domain_Adaptation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Simon4Yan/Learning-via-Translation,137,1/2/2019 +An Improved Deep Learning Architecture for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2015/html/Ahmed_An_Improved_Deep_2015_CVPR_paper.html,CVPR,2015,https://github.com/Ning-Ding/Implementation-CVPR2015-CNN-for-ReID,127,1/2/2019 +Context Embedding Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kim_Context_Embedding_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/thunlp/CANE,131,1/2/2019 +Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model,http://papers.nips.cc/paper/7145-deep-learning-for-precipitation-nowcasting-a-benchmark-and-a-new-model.pdf,NIPS,2017,https://github.com/sxjscience/HKO-7,134,1/2/2019 +Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Song_Deep_Sliding_Shapes_CVPR_2016_paper.html,CVPR,2016,https://github.com/shurans/DeepSlidingShape,126,1/2/2019 +DSAC - Differentiable RANSAC for Camera Localization,http://openaccess.thecvf.com/content_cvpr_2017/html/Brachmann_DSAC_-_Differentiable_CVPR_2017_paper.html,CVPR,2017,https://github.com/cvlab-dresden/DSAC,144,1/2/2019 +Learning a Multi-View Stereo Machine,http://papers.nips.cc/paper/6640-learning-a-multi-view-stereo-machine.pdf,NIPS,2017,https://github.com/akar43/lsm,135,1/2/2019 +Segmentation-Aware Convolutional Networks Using Local Attention Masks,http://openaccess.thecvf.com/content_iccv_2017/html/Harley_Segmentation-Aware_Convolutional_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/aharley/segaware,126,1/2/2019 +Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Inoue_Cross-Domain_Weakly-Supervised_Object_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/naoto0804/cross-domain-detection,143,1/2/2019 +Bayesian Compression for Deep Learning,http://papers.nips.cc/paper/6921-bayesian-compression-for-deep-learning.pdf,NIPS,2017,https://github.com/KarenUllrich/Tutorial_BayesianCompressionForDL,130,1/2/2019 +Fast and Accurate Online Video Object Segmentation via Tracking Parts,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cheng_Fast_and_Accurate_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/JingchunCheng/FAVOS,129,1/2/2019 +Learning to Compare: Relation Network for Few-Shot Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sung_Learning_to_Compare_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lzrobots/LearningToCompare_ZSL,135,1/2/2019 +Dynamic Image Networks for Action Recognition,http://openaccess.thecvf.com/content_cvpr_2016/html/Bilen_Dynamic_Image_Networks_CVPR_2016_paper.html,CVPR,2016,https://github.com/hbilen/dynamic-image-nets,133,1/2/2019 +Context Encoders: Feature Learning by Inpainting,http://openaccess.thecvf.com/content_cvpr_2016/html/Pathak_Context_Encoders_Feature_CVPR_2016_paper.html,CVPR,2016,https://github.com/jazzsaxmafia/Inpainting,124,1/2/2019 +Weakly Supervised Instance Segmentation Using Class Peak Response,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Weakly_Supervised_Instance_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ZhouYanzhao/PRM,166,1/2/2019 +MVSNet: Depth Inference for Unstructured Multi-view Stereo,http://openaccess.thecvf.com/content_ECCV_2018/html/Yao_Yao_MVSNet_Depth_Inference_ECCV_2018_paper.html,ECCV,2018,https://github.com/YoYo000/MVSNet,174,1/2/2019 +Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining,http://openaccess.thecvf.com/content_ECCV_2018/html/Xia_Li_Recurrent_Squeeze-and-Excitation_Context_ECCV_2018_paper.html,ECCV,2018,https://github.com/XiaLiPKU/RESCAN,142,1/2/2019 +L4: Practical loss-based stepsize adaptation for deep learning,http://arxiv.org/abs/1802.05074v4,NIPS,2018,https://github.com/martius-lab/l4-optimizer,123,1/2/2019 +Value Prediction Network,http://papers.nips.cc/paper/7192-value-prediction-network.pdf,NIPS,2017,https://github.com/junhyukoh/value-prediction-network,119,1/2/2019 +Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Structure_Inference_Net_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/choasup/SIN,140,1/2/2019 +Hierarchical Attentive Recurrent Tracking,http://papers.nips.cc/paper/6898-hierarchical-attentive-recurrent-tracking.pdf,NIPS,2017,https://github.com/akosiorek/hart,121,1/2/2019 +A Closer Look at Spatiotemporal Convolutions for Action Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tran_A_Closer_Look_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/irhumshafkat/R2Plus1D-PyTorch,143,1/2/2019 +Discriminative Correlation Filter With Channel and 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Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Laptev_TI-Pooling_Transformation-Invariant_Pooling_CVPR_2016_paper.html,CVPR,2016,https://github.com/dlaptev/TI-pooling,109,1/2/2019 +Bayesian Optimization with Gradients,http://papers.nips.cc/paper/7111-bayesian-optimization-with-gradients.pdf,NIPS,2017,https://github.com/wujian16/Cornell-MOE,117,1/2/2019 +MemNet: A Persistent Memory Network for Image Restoration,http://openaccess.thecvf.com/content_iccv_2017/html/Tai_MemNet_A_Persistent_ICCV_2017_paper.html,ICCV,2017,https://github.com/tyshiwo/MemNet,119,1/2/2019 +Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Split-Brain_Autoencoders_Unsupervised_CVPR_2017_paper.html,CVPR,2017,https://github.com/richzhang/splitbrainauto,110,1/2/2019 +Long-term Tracking in the Wild: a Benchmark,http://openaccess.thecvf.com/content_ECCV_2018/html/Efstratios_Gavves_Long-term_Tracking_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/oxuva/long-term-tracking-benchmark,116,1/2/2019 +Detail-Revealing Deep Video Super-Resolution,http://openaccess.thecvf.com/content_iccv_2017/html/Tao_Detail-Revealing_Deep_Video_ICCV_2017_paper.html,ICCV,2017,https://github.com/jiangsutx/SPMC_VideoSR,126,1/2/2019 +Realistic Evaluation of Deep Semi-Supervised Learning Algorithms,http://arxiv.org/abs/1804.09170v2,NIPS,2018,https://github.com/brain-research/realistic-ssl-evaluation,175,1/2/2019 +FaceNet: A Unified Embedding for Face Recognition and Clustering,http://openaccess.thecvf.com/content_cvpr_2015/html/Schroff_FaceNet_A_Unified_2015_CVPR_paper.html,CVPR,2015,https://github.com/liorshk/facenet_pytorch,124,1/2/2019 +Compressed Sensing using Generative Models,http://proceedings.mlr.press/v70/bora17a.html,ICML,2017,https://github.com/AshishBora/csgm,116,1/2/2019 +Unrestricted Facial 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Transform,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Recovering_Realistic_Texture_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xinntao/CVPR18-SFTGAN,139,1/2/2019 +Switching Convolutional Neural Network for Crowd Counting,http://openaccess.thecvf.com/content_cvpr_2017/html/Sam_Switching_Convolutional_Neural_CVPR_2017_paper.html,CVPR,2017,https://github.com/val-iisc/crowd-counting-scnn,116,1/2/2019 +3D-CODED: 3D Correspondences by Deep Deformation,http://openaccess.thecvf.com/content_ECCV_2018/html/Thibault_Groueix_Shape_correspondences_from_ECCV_2018_paper.html,ECCV,2018,https://github.com/ThibaultGROUEIX/3D-CODED,125,1/2/2019 +FeUdal Networks for Hierarchical Reinforcement Learning,http://proceedings.mlr.press/v70/vezhnevets17a.html,ICML,2017,https://github.com/dmakian/feudal_networks,107,1/2/2019 +PU-Net: Point Cloud Upsampling Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_PU-Net_Point_Cloud_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yulequan/PU-Net,117,1/2/2019 +Scale-Recurrent Network for Deep Image Deblurring,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tao_Scale-Recurrent_Network_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiangsutx/SRN-Deblur,159,1/2/2019 +"WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation",http://openaccess.thecvf.com/content_cvpr_2017/html/Durand_WILDCAT_Weakly_Supervised_CVPR_2017_paper.html,CVPR,2017,https://github.com/durandtibo/wildcat.pytorch,116,1/2/2019 +Noisy Natural Gradient as Variational Inference,http://proceedings.mlr.press/v80/zhang18l.html,ICML,2018,https://github.com/wlwkgus/NoisyNaturalGradient,108,1/2/2019 +Video Frame Synthesis Using Deep Voxel Flow,http://openaccess.thecvf.com/content_iccv_2017/html/Liu_Video_Frame_Synthesis_ICCV_2017_paper.html,ICCV,2017,https://github.com/liuziwei7/voxel-flow,114,1/2/2019 +Working hard to know your neighbor's margins: Local descriptor learning loss,http://papers.nips.cc/paper/7068-working-hard-to-know-your-neighbors-margins-local-descriptor-learning-loss.pdf,NIPS,2017,https://github.com/DagnyT/hardnet,128,1/2/2019 +Domain Adaptive Faster R-CNN for Object Detection in the Wild,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Domain_Adaptive_Faster_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yuhuayc/da-faster-rcnn,123,1/2/2019 +"Train longer, generalize better: closing the generalization gap in large batch training of neural networks",http://papers.nips.cc/paper/6770-train-longer-generalize-better-closing-the-generalization-gap-in-large-batch-training-of-neural-networks.pdf,NIPS,2017,https://github.com/eladhoffer/bigBatch,112,1/2/2019 +Natural Language Object 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Scenes,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_DenseASPP_for_Semantic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/DeepMotionAIResearch/DenseASPP,151,1/2/2019 +ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression,http://openaccess.thecvf.com/content_iccv_2017/html/Luo_ThiNet_A_Filter_ICCV_2017_paper.html,ICCV,2017,https://github.com/Roll920/ThiNet,105,1/2/2019 +Graph R-CNN for Scene Graph Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Jianwei_Yang_Graph_R-CNN_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/jwyang/graph-rcnn.pytorch,144,1/2/2019 +"Factoring Shape, Pose, and Layout From the 2D Image of a 3D Scene",http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulsiani_Factoring_Shape_Pose_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shubhtuls/factored3d,114,1/2/2019 +Multi-View Supervision for Single-View Reconstruction via Differentiable Ray 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Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Density-Aware_Single_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hezhangsprinter/DID-MDN,118,1/2/2019 +Weakly Supervised Deep Detection Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Bilen_Weakly_Supervised_Deep_CVPR_2016_paper.html,CVPR,2016,https://github.com/hbilen/WSDDN,103,1/2/2019 +Task-based End-to-end Model Learning in Stochastic Optimization,http://papers.nips.cc/paper/7132-task-based-end-to-end-model-learning-in-stochastic-optimization.pdf,NIPS,2017,https://github.com/locuslab/e2e-model-learning,100,1/2/2019 +MAttNet: Modular Attention Network for Referring Expression Comprehension,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_MAttNet_Modular_Attention_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lichengunc/MAttNet,104,1/2/2019 +Interleaved Group 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Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Multi-Scale_Continuous_CRFs_CVPR_2017_paper.html,CVPR,2017,https://github.com/danxuhk/ContinuousCRF-CNN,93,1/2/2019 +Attention-based Deep Multiple Instance Learning,http://proceedings.mlr.press/v80/ilse18a.html,ICML,2018,https://github.com/AMLab-Amsterdam/AttentionDeepMIL,109,1/2/2019 +Multi-View Consistency as Supervisory Signal for Learning Shape and Pose Prediction,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tulsiani_Multi-View_Consistency_as_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shubhtuls/mvcSnP,80,1/2/2019 +Macro-Micro Adversarial Network for Human Parsing,http://openaccess.thecvf.com/content_ECCV_2018/html/Yawei_Luo_Macro-Micro_Adversarial_Network_ECCV_2018_paper.html,ECCV,2018,https://github.com/RoyalVane/MMAN,98,1/2/2019 +A Convolutional Neural Network Cascade for Face 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Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Dongqing_Zhang_Optimized_Quantization_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/Microsoft/LQ-Nets,103,1/2/2019 +Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Spatial-Temporal_Regularized_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lifeng9472/STRCF,86,1/2/2019 +Learning Spatially Regularized Correlation Filters for Visual Tracking,http://openaccess.thecvf.com/content_iccv_2015/html/Danelljan_Learning_Spatially_Regularized_ICCV_2015_paper.html,ICCV,2015,https://github.com/lifeng9472/STRCF,86,1/2/2019 +DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data,http://openaccess.thecvf.com/content_cvpr_2017/html/Gurumurthy_DeLiGAN__Generative_CVPR_2017_paper.html,CVPR,2017,https://github.com/val-iisc/deligan,78,1/2/2019 +A PID Controller Approach for Stochastic Optimization of Deep Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/An_A_PID_Controller_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tensorboy/PIDOptimizer,87,1/2/2019 +A-NICE-MC: Adversarial Training for MCMC,http://papers.nips.cc/paper/7099-a-nice-mc-adversarial-training-for-mcmc.pdf,NIPS,2017,https://github.com/jiamings/a-nice-mc,80,1/2/2019 +Coarse-To-Fine Volumetric Prediction for Single-Image 3D Human Pose,http://openaccess.thecvf.com/content_cvpr_2017/html/Pavlakos_Coarse-To-Fine_Volumetric_Prediction_CVPR_2017_paper.html,CVPR,2017,https://github.com/geopavlakos/c2f-vol-train,80,1/2/2019 +Synthesizing Images of Humans in Unseen Poses,http://openaccess.thecvf.com/content_cvpr_2018/papers/Balakrishnan_Synthesizing_Images_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/balakg/posewarp-cvpr2018,88,1/2/2019 +Tell Me Where to Look: Guided Attention Inference 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New Baseline,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Future_Frame_Prediction_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/StevenLiuWen/ano_pred_cvpr2018,92,1/2/2019 +Hard-Aware Deeply Cascaded Embedding,http://openaccess.thecvf.com/content_iccv_2017/html/Yuan_Hard-Aware_Deeply_Cascaded_ICCV_2017_paper.html,ICCV,2017,https://github.com/PkuRainBow/Hard-Aware-Deeply-Cascaded-Embedding_release,75,1/2/2019 +Query-Guided Regression Network With Context Policy for Phrase Grounding,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Query-Guided_Regression_Network_ICCV_2017_paper.html,ICCV,2017,https://github.com/kanchen-usc/QRC-Net,72,1/2/2019 +End-To-End Instance Segmentation With Recurrent Attention,http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_End-To-End_Instance_Segmentation_CVPR_2017_paper.html,CVPR,2017,https://github.com/renmengye/rec-attend-public,78,1/2/2019 +Improved Stereo Matching With Constant Highway Networks and Reflective Confidence 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CNNs,http://openaccess.thecvf.com/content_cvpr_2016/html/Ge_Robust_3D_Hand_CVPR_2016_paper.html,CVPR,2016,https://github.com/geliuhao/CVPR2016_HandPoseEstimation,70,1/2/2019 +Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Yikang_LI_Factorizable_Net_An_ECCV_2018_paper.html,ECCV,2018,https://github.com/yikang-li/FactorizableNet,78,1/2/2019 +Saliency Detection by Multi-Context Deep Learning,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhao_Saliency_Detection_by_2015_CVPR_paper.html,CVPR,2015,https://github.com/Robert0812/deepsaldet,66,1/2/2019 +Self-Supervised Learning of Visual Features Through Embedding Images Into Text Topic Spaces,http://openaccess.thecvf.com/content_cvpr_2017/html/Gomez_Self-Supervised_Learning_of_CVPR_2017_paper.html,CVPR,2017,https://github.com/lluisgomez/TextTopicNet,69,1/2/2019 +SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance 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Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Toderici_Full_Resolution_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/1zb/pytorch-image-comp-rnn,66,1/2/2019 +CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_CSRNet_Dilated_Convolutional_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/leeyeehoo/CSRNet-pytorch,87,1/2/2019 +"Deep Learning Face Representation from Predicting 10,000 Classes",http://openaccess.thecvf.com/content_cvpr_2014/html/Sun_Deep_Learning_Face_2014_CVPR_paper.html,CVPR,2014,https://github.com/joyhuang9473/deepid-implementation,62,1/2/2019 +Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Learning_Attentions_Residual_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/foolwood/RASNet,67,1/2/2019 +“Zero-Shot” Super-Resolution Using Deep Internal Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shocher_Zero-Shot_Super-Resolution_Using_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/assafshocher/ZSSR,84,1/2/2019 +Generative Neural Machine Translation,http://arxiv.org/abs/1806.05138v1,NIPS,2018,https://github.com/ZhenYangIACAS/NMT_GAN,68,1/2/2019 +Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Physically-Based_Rendering_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/yindaz/pbrs,67,1/2/2019 +AdaGAN: Boosting Generative Models,http://papers.nips.cc/paper/7126-adagan-boosting-generative-models.pdf,NIPS,2017,https://github.com/tolstikhin/adagan,59,1/2/2019 +Progressive Neural Architecture Search,http://openaccess.thecvf.com/content_ECCV_2018/html/Chenxi_Liu_Progressive_Neural_Architecture_ECCV_2018_paper.html,ECCV,2018,https://github.com/titu1994/progressive-neural-architecture-search,68,1/2/2019 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Processes,http://papers.nips.cc/paper/7045-doubly-stochastic-variational-inference-for-deep-gaussian-processes.pdf,NIPS,2017,https://github.com/ICL-SML/Doubly-Stochastic-DGP,66,1/2/2019 +Toward Controlled Generation of Text,http://proceedings.mlr.press/v70/hu17e.html,ICML,2017,https://github.com/GBLin5566/toward-controlled-generation-of-text-pytorch,63,1/2/2019 +Learning to Reweight Examples for Robust Deep Learning,http://proceedings.mlr.press/v80/ren18a.html,ICML,2018,https://github.com/danieltan07/learning-to-reweight-examples,76,1/2/2019 +Dance Dance Convolution,http://proceedings.mlr.press/v70/donahue17a.html,ICML,2017,https://github.com/chrisdonahue/ddc,65,1/2/2019 +Generate to Adapt: Aligning Domains Using Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Generate_to_Adapt_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yogeshbalaji/Generate_To_Adapt,67,1/2/2019 +Image-To-Image Translation With Conditional Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/williamFalcon/pix2pix-keras,70,1/2/2019 +Decorrelated Batch Normalization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Decorrelated_Batch_Normalization_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/umich-vl/DecorrelatedBN,57,1/2/2019 +Xception: Deep Learning With Depthwise Separable Convolutions,http://openaccess.thecvf.com/content_cvpr_2017/html/Chollet_Xception_Deep_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/tstandley/Xception-PyTorch,71,1/2/2019 +Geometry-Aware Learning of Maps for Camera Localization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Brahmbhatt_Geometry-Aware_Learning_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/samarth-robo/MapNet,63,1/2/2019 +Improving Generalization via Scalable Neighborhood Component Analysis,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhirong_Wu_Improving_Embedding_Generalization_ECCV_2018_paper.html,ECCV,2018,https://github.com/Microsoft/snca.pytorch,76,1/2/2019 +Convolutional Gaussian Processes,http://papers.nips.cc/paper/6877-convolutional-gaussian-processes.pdf,NIPS,2017,https://github.com/markvdw/convgp/,57,9/16/2018 +Path-Level Network Transformation for Efficient Architecture Search,http://proceedings.mlr.press/v80/cai18a.html,ICML,2018,https://github.com/han-cai/PathLevel-EAS,73,1/2/2019 +Ordinal Depth Supervision for 3D Human Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Pavlakos_Ordinal_Depth_Supervision_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/geopavlakos/ordinal-pose3d,74,1/2/2019 +Escape From Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models,http://openaccess.thecvf.com/content_iccv_2017/html/Klokov_Escape_From_Cells_ICCV_2017_paper.html,ICCV,2017,https://github.com/fxia22/kdnet.pytorch,68,1/2/2019 +Object Level Visual Reasoning in Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Fabien_Baradel_Object_Level_Visual_ECCV_2018_paper.html,ECCV,2018,https://github.com/fabienbaradel/object_level_visual_reasoning,71,1/2/2019 +Regularizing RNNs for Caption Generation by Reconstructing the Past With the Present,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Regularizing_RNNs_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chenxinpeng/ARNet,70,1/2/2019 +Disentangled Person Image Generation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ma_Disentangled_Person_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/charliememory/Disentangled-Person-Image-Generation,75,1/2/2019 +Diverse Image-to-Image Translation via Disentangled Representations,http://openaccess.thecvf.com/content_ECCV_2018/html/Hsin-Ying_Lee_Diverse_Image-to-Image_Translation_ECCV_2018_paper.html,ECCV,2018,https://github.com/taki0112/DRIT-Tensorflow,72,1/2/2019 +A Distributional Perspective on Reinforcement Learning,http://proceedings.mlr.press/v70/bellemare17a.html,ICML,2017,https://github.com/Silvicek/distributional-dqn,68,1/2/2019 +Neural Program Synthesis from Diverse Demonstration Videos,http://proceedings.mlr.press/v80/sun18a.html,ICML,2018,https://github.com/shaohua0116/demo2program,62,1/2/2019 +Pointwise Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hua_Pointwise_Convolutional_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/scenenn/pointwise,67,1/2/2019 +Modeling Relationships in Referential Expressions With Compositional Modular Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Modeling_Relationships_in_CVPR_2017_paper.html,CVPR,2017,https://github.com/ronghanghu/cmn,57,1/2/2019 +Deep Subspace Clustering Networks,http://papers.nips.cc/paper/6608-deep-subspace-clustering-networks.pdf,NIPS,2017,https://github.com/panji1990/Deep-subspace-clustering-networks,68,1/2/2019 +Multi-Channel Weighted Nuclear Norm Minimization for Real Color Image Denoising,http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Multi-Channel_Weighted_Nuclear_ICCV_2017_paper.html,ICCV,2017,https://github.com/csjunxu/MCWNNM-ICCV2017,61,1/2/2019 +Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency,http://openaccess.thecvf.com/content_ECCV_2018/html/Xingyi_Zhou_Unsupervised_Domain_Adaptation_ECCV_2018_paper.html,ECCV,2018,https://github.com/xingyizhou/3DKeypoints-DA,60,1/2/2019 +Learning Less Is More - 6D Camera Localization via 3D Surface Regression,http://openaccess.thecvf.com/content_cvpr_2018/papers/Brachmann_Learning_Less_Is_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/vislearn/LessMore,72,1/2/2019 +End-To-End 3D Face Reconstruction With Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Dou_End-To-End_3D_Face_CVPR_2017_paper.html,CVPR,2017,https://github.com/ShownX/mxnet-E2FAR,60,1/2/2019 +Learning Latent Super-Events to Detect Multiple Activities in Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Piergiovanni_Learning_Latent_Super-Events_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/piergiaj/super-events-cvpr18,67,1/2/2019 +Factorized Bilinear Models for Image Recognition,http://openaccess.thecvf.com/content_iccv_2017/html/Li_Factorized_Bilinear_Models_ICCV_2017_paper.html,ICCV,2017,https://github.com/lyttonhao/Factorized-Bilinear-Network,55,1/2/2019 +Depth-aware CNN for RGB-D Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Weiyue_Wang_Depth-aware_CNN_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/laughtervv/DepthAwareCNN,88,1/2/2019 +Online and Linear-Time Attention by Enforcing Monotonic Alignments,http://proceedings.mlr.press/v70/raffel17a.html,ICML,2017,https://github.com/craffel/mad,56,1/2/2019 +Unsupervised Discovery of Object Landmarks as Structural Representations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Unsupervised_Discovery_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/YutingZhang/lmdis-rep,61,1/2/2019 +Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Crafting_a_Toolchain_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yuke93/RL-Restore,77,1/2/2019 +SparseMAP: Differentiable Sparse Structured Inference,http://proceedings.mlr.press/v80/niculae18a.html,ICML,2018,https://github.com/vene/sparsemap,75,1/2/2019 +Adversarial Feature Augmentation for Unsupervised Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Volpi_Adversarial_Feature_Augmentation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ricvolpi/adversarial-feature-augmentation,67,1/2/2019 +Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Self-Supervised_Adversarial_Hashing_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lelan-li/SSAH,72,1/2/2019 +Unsupervised Learning by Predicting Noise,http://proceedings.mlr.press/v70/bojanowski17a.html,ICML,2017,https://github.com/facebookresearch/noise-as-targets,60,1/2/2019 +Fast and Accurate Single Image Super-Resolution via Information Distillation Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hui_Fast_and_Accurate_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Zheng222/IDN-Caffe,71,1/2/2019 +CoupleNet: Coupling Global Structure With Local Parts for Object Detection,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_CoupleNet_Coupling_Global_ICCV_2017_paper.html,ICCV,2017,https://github.com/tshizys/CoupleNet,59,1/2/2019 +A Deep Regression Architecture With Two-Stage Re-Initialization for High Performance Facial Landmark Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Lv_A_Deep_Regression_CVPR_2017_paper.html,CVPR,2017,https://github.com/shaoxiaohu/Face_Alignment_Two_Stage_Re-initialization,57,1/2/2019 +On-the-fly Operation Batching in Dynamic Computation Graphs,http://papers.nips.cc/paper/6986-on-the-fly-operation-batching-in-dynamic-computation-graphs.pdf,NIPS,2017,https://github.com/neulab/dynet-benchmark,54,1/2/2019 +Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes With Deep Generative Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Soltani_Synthesizing_3D_Shapes_CVPR_2017_paper.html,CVPR,2017,https://github.com/Amir-Arsalan/Synthesize3DviaDepthOrSil,65,1/2/2019 +Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Curriculum_Domain_Adaptation_ICCV_2017_paper.html,ICCV,2017,https://github.com/YangZhang4065/AdaptationSeg,64,1/2/2019 +Deep Compositional Captioning: Describing Novel Object Categories Without Paired Training Data,http://openaccess.thecvf.com/content_cvpr_2016/html/Hendricks_Deep_Compositional_Captioning_CVPR_2016_paper.html,CVPR,2016,https://github.com/LisaAnne/DCC,57,1/2/2019 +Neural Style Transfer via Meta Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Neural_Style_Transfer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/FalongShen/styletransfer,59,1/2/2019 +Deep Marching Cubes: Learning Explicit Surface Representations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liao_Deep_Marching_Cubes_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yiyiliao/deep_marching_cubes,56,1/2/2019 +Shift-Net: Image Inpainting via Deep Feature Rearrangement,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhaoyi_Yan_Shift-Net_Image_Inpainting_ECCV_2018_paper.html,ECCV,2018,https://github.com/Zhaoyi-Yan/Shift-Net_pytorch,74,1/2/2019 +Dense-Captioning Events in Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Krishna_Dense-Captioning_Events_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/ranjaykrishna/densevid_eval,55,1/2/2019 +Cascade R-CNN: Delving Into High Quality Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cai_Cascade_R-CNN_Delving_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/guoruoqian/cascade-rcnn_Pytorch,93,1/2/2019 +Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee,http://papers.nips.cc/paper/6910-net-trim-convex-pruning-of-deep-neural-networks-with-performance-guarantee.pdf,NIPS,2017,https://github.com/DNNToolBox/Net-Trim-v1,54,1/2/2019 +Leveraging Unlabeled Data for Crowd Counting by Learning to Rank,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Leveraging_Unlabeled_Data_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xialeiliu/CrowdCountingCVPR18,56,1/2/2019 +Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sankaranarayanan_Learning_From_Synthetic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/swamiviv/LSD-seg,56,1/2/2019 +Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Weakly-Supervised_Semantic_Segmentation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/speedinghzl/DSRG,71,1/2/2019 +SST: Single-Stream Temporal Action Proposals,http://openaccess.thecvf.com/content_cvpr_2017/html/Buch_SST_Single-Stream_Temporal_CVPR_2017_paper.html,CVPR,2017,https://github.com/ranjaykrishna/SST,51,1/2/2019 +Fighting Fake News: Image Splice Detection via Learned Self-Consistency,http://openaccess.thecvf.com/content_ECCV_2018/html/Jacob_Huh_Fighting_Fake_News_ECCV_2018_paper.html,ECCV,2018,https://github.com/minyoungg/selfconsistency,62,1/2/2019 +Curiosity-driven Exploration by Self-supervised Prediction,http://proceedings.mlr.press/v70/pathak17a.html,ICML,2017,https://github.com/kimhc6028/pytorch-noreward-rl,56,1/2/2019 +Deep IV: A Flexible Approach for Counterfactual Prediction,http://proceedings.mlr.press/v70/hartford17a.html,ICML,2017,https://github.com/jhartford/DeepIV,52,1/2/2019 +Hierarchical Long-term Video Prediction without Supervision,http://proceedings.mlr.press/v80/wichers18a.html,ICML,2018,https://github.com/brain-research/long-term-video-prediction-without-supervision,60,1/2/2019 +PDE-Net: Learning PDEs from Data,http://proceedings.mlr.press/v80/long18a.html,ICML,2018,https://github.com/ZichaoLong/PDE-Net,75,1/2/2019 +Efficient 3D Room Shape Recovery From a Single Panorama,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Efficient_3D_Room_CVPR_2016_paper.html,CVPR,2016,https://github.com/YANG-H/Panoramix,55,1/2/2019 +Learning Discrete Representations via Information Maximizing Self-Augmented Training,http://proceedings.mlr.press/v70/hu17b.html,ICML,2017,https://github.com/weihua916/imsat,49,1/2/2019 +Video Segmentation via Object Flow,http://openaccess.thecvf.com/content_cvpr_2016/html/Tsai_Video_Segmentation_via_CVPR_2016_paper.html,CVPR,2016,https://github.com/wasidennis/ObjectFlow,50,1/2/2019 +Person Search With Natural Language Description,http://openaccess.thecvf.com/content_cvpr_2017/html/Li_Person_Search_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/ShuangLI59/Person-Search-with-Natural-Language-Description,61,1/2/2019 +Discriminability Objective for Training Descriptive Captions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Luo_Discriminability_Objective_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ruotianluo/DiscCaptioning,54,1/2/2019 +Triangle Generative Adversarial Networks,http://papers.nips.cc/paper/7109-triangle-generative-adversarial-networks.pdf,NIPS,2017,https://github.com/LiqunChen0606/Triangle-GAN,51,1/2/2019 +The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process,http://papers.nips.cc/paper/7252-the-neural-hawkes-process-a-neurally-self-modulating-multivariate-point-process.pdf,NIPS,2017,https://github.com/HMEIatJHU/neurawkes,56,1/2/2019 +Finding Action Tubes,http://openaccess.thecvf.com/content_cvpr_2015/html/Gkioxari_Finding_Action_Tubes_2015_CVPR_paper.html,CVPR,2015,https://github.com/gkioxari/ActionTubes,51,1/2/2019 +Differentiable Learning of Logical Rules for Knowledge Base Reasoning,http://papers.nips.cc/paper/6826-differentiable-learning-of-logical-rules-for-knowledge-base-reasoning.pdf,NIPS,2017,https://github.com/fanyangxyz/Neural-LP,62,1/2/2019 +L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space,http://openaccess.thecvf.com/content_cvpr_2017/html/Tian_L2-Net_Deep_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/yuruntian/L2-Net,51,1/2/2019 +Visual Question Generation as Dual Task of Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Visual_Question_Generation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yikang-li/iQAN,50,1/2/2019 +DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency,http://openaccess.thecvf.com/content_ECCV_2018/html/Yuliang_Zou_DF-Net_Unsupervised_Joint_ECCV_2018_paper.html,ECCV,2018,https://github.com/vt-vl-lab/DF-Net,82,1/2/2019 +BlockDrop: Dynamic Inference Paths in Residual Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_BlockDrop_Dynamic_Inference_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Tushar-N/blockdrop,54,1/2/2019 +Efficient end-to-end learning for quantizable representations,http://proceedings.mlr.press/v80/jeong18a.html,ICML,2018,https://github.com/maestrojeong/Deep-Hash-Table-ICML18,50,1/2/2019 +Predicting Deeper Into the Future of Semantic Segmentation,http://openaccess.thecvf.com/content_iccv_2017/html/Luc_Predicting_Deeper_Into_ICCV_2017_paper.html,ICCV,2017,https://github.com/facebookresearch/SegmPred,51,1/2/2019 +Towards Diverse and Natural Image Descriptions via a Conditional GAN,http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Towards_Diverse_and_ICCV_2017_paper.html,ICCV,2017,https://github.com/doubledaibo/gancaption_iccv2017,53,1/2/2019 +CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Shou_CDC_Convolutional-De-Convolutional_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/ColumbiaDVMM/CDC,53,1/2/2019 +Category-Specific Object Reconstruction From a Single Image,http://openaccess.thecvf.com/content_cvpr_2015/html/Kar_Category-Specific_Object_Reconstruction_2015_CVPR_paper.html,CVPR,2015,https://github.com/akar43/CategoryShapes,48,1/2/2019 +Learning to Find Good Correspondences,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yi_Learning_to_Find_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/vcg-uvic/learned-correspondence-release,72,1/2/2019 +Neural Expectation Maximization,http://papers.nips.cc/paper/7246-neural-expectation-maximization.pdf,NIPS,2017,https://github.com/sjoerdvansteenkiste/Neural-EM,56,1/2/2019 +Semantic Video CNNs Through Representation 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Labeling,http://openaccess.thecvf.com/content_cvpr_2015/html/Liu_Multi-Objective_Convolutional_Learning_2015_CVPR_paper.html,CVPR,2015,https://github.com/Liusifei/Face_Parsing_2016,55,1/2/2019 +Wasserstein Introspective Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_Wasserstein_Introspective_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kjunelee/WINN,51,1/2/2019 +Conditional Probability Models for Deep Image Compression,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mentzer_Conditional_Probability_Models_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/fab-jul/imgcomp-cvpr,54,1/2/2019 +Efficient Diffusion on Region Manifolds: Recovering Small Objects With Compact CNN Representations,http://openaccess.thecvf.com/content_cvpr_2017/html/Iscen_Efficient_Diffusion_on_CVPR_2017_paper.html,CVPR,2017,https://github.com/ahmetius/diffusion-retrieval,48,1/2/2019 +Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Peng_Jointly_Optimize_Data_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhiqiangdon/pose-adv-aug,54,1/2/2019 +PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction,http://openaccess.thecvf.com/content_ECCV_2018/html/Yifei_Shi_PlaneMatch_Patch_Coplanarity_ECCV_2018_paper.html,ECCV,2018,https://github.com/yifeishi/PlaneMatch,57,1/2/2019 +Learning to Navigate for Fine-grained Classification,http://openaccess.thecvf.com/content_ECCV_2018/html/Ze_Yang_Learning_to_Navigate_ECCV_2018_paper.html,ECCV,2018,https://github.com/yangze0930/NTS-Net,74,1/2/2019 +Hybrid Reward Architecture for Reinforcement Learning,http://papers.nips.cc/paper/7123-hybrid-reward-architecture-for-reinforcement-learning.pdf,NIPS,2017,https://github.com/Maluuba/hra,50,1/2/2019 +Localizing Moments in Video With Natural Language,http://openaccess.thecvf.com/content_iccv_2017/html/Hendricks_Localizing_Moments_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/LisaAnne/LocalizingMoments,60,1/2/2019 +FOTS: Fast Oriented Text Spotting With a Unified Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_FOTS_Fast_Oriented_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiangxiluning/FOTS.PyTorch,118,1/2/2019 +Grammar Variational Autoencoder,http://proceedings.mlr.press/v70/kusner17a.html,ICML,2017,https://github.com/episodeyang/grammar_variational_autoencoder,46,1/2/2019 +Measuring abstract reasoning in neural networks,http://proceedings.mlr.press/v80/santoro18a.html,ICML,2018,https://github.com/deepmind/abstract-reasoning-matrices,51,1/2/2019 +Unsupervised Attention-guided Image-to-Image Translation,https://arxiv.org/abs/1806.02311,NIPS,2018,https://github.com/AlamiMejjati/Unsupervised-Attention-guided-Image-to-Image-Translation,110,1/2/2019 +Visual Translation Embedding Network for Visual Relation Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Visual_Translation_Embedding_CVPR_2017_paper.html,CVPR,2017,https://github.com/zawlin/cvpr17_vtranse,54,1/2/2019 +Learning towards Minimum Hyperspherical Energy,http://arxiv.org/abs/1805.09298v4,NIPS,2018,https://github.com/wy1iu/MHE,54,1/2/2019 +Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network,http://papers.nips.cc/paper/6854-predicting-organic-reaction-outcomes-with-weisfeiler-lehman-network.pdf,NIPS,2017,https://github.com/wengong-jin/nips17-rexgen,46,1/2/2019 +Structured Bayesian Pruning via Log-Normal Multiplicative Noise,http://papers.nips.cc/paper/7254-structured-bayesian-pruning-via-log-normal-multiplicative-noise.pdf,NIPS,2017,https://github.com/necludov/group-sparsity-sbp,44,1/2/2019 +Modulating early visual processing by language,http://papers.nips.cc/paper/7237-modulating-early-visual-processing-by-language.pdf,NIPS,2017,https://github.com/GuessWhatGame/guesswhat,49,1/2/2019 +Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam,http://proceedings.mlr.press/v80/khan18a.html,ICML,2018,https://github.com/emtiyaz/vadam,49,1/2/2019 +A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning,http://papers.nips.cc/paper/6951-a-disentangled-recognition-and-nonlinear-dynamics-model-for-unsupervised-learning.pdf,NIPS,2017,https://github.com/simonkamronn/kvae,53,1/2/2019 +Learning Pose Specific Representations by Predicting Different Views,http://openaccess.thecvf.com/content_cvpr_2018/papers/Poier_Learning_Pose_Specific_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/poier/PreView,44,1/2/2019 +Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation,http://openaccess.thecvf.com/content_ECCV_2018/html/Zhaoyang_Lv_Learning_Rigidity_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/NVlabs/learningrigidity,61,1/2/2019 +Adversarial Examples for Semantic Segmentation and Object Detection,http://openaccess.thecvf.com/content_iccv_2017/html/Xie_Adversarial_Examples_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/cihangxie/DAG,49,1/2/2019 +BING: Binarized Normed Gradients for Objectness Estimation at 300fps,http://openaccess.thecvf.com/content_cvpr_2014/html/Cheng_BING_Binarized_Normed_2014_CVPR_paper.html,CVPR,2014,https://github.com/alessandroferrari/BING-Objectness,44,1/2/2019 +Video Pixel Networks,http://proceedings.mlr.press/v70/kalchbrenner17a.html,ICML,2017,https://github.com/3ammor/Video-Pixel-Networks,45,1/2/2019 +Learning Residual Images for Face Attribute Manipulation,http://openaccess.thecvf.com/content_cvpr_2017/html/Shen_Learning_Residual_Images_CVPR_2017_paper.html,CVPR,2017,https://github.com/Zhongdao/FaceAttributeManipulation,43,1/2/2019 +Differentiable Compositional Kernel Learning for Gaussian Processes,http://proceedings.mlr.press/v80/sun18e.html,ICML,2018,https://github.com/ssydasheng/Neural-Kernel-Network,45,1/2/2019 +Learned D-AMP: Principled Neural Network based Compressive Image Recovery,http://papers.nips.cc/paper/6774-learned-d-amp-principled-neural-network-based-compressive-image-recovery.pdf,NIPS,2017,https://github.com/ricedsp/D-AMP_Toolbox,47,1/2/2019 +Accurate Optical Flow via Direct Cost Volume Processing,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Accurate_Optical_Flow_CVPR_2017_paper.html,CVPR,2017,https://github.com/IntelVCL/dcflow,42,1/2/2019 +Learning From Massive Noisy Labeled Data for Image Classification,http://openaccess.thecvf.com/content_cvpr_2015/html/Xiao_Learning_From_Massive_2015_CVPR_paper.html,CVPR,2015,https://github.com/Cysu/noisy_label,45,1/2/2019 +Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition,http://openaccess.thecvf.com/content_ECCV_2018/html/Chaojian_Yu_Hierarchical_Bilinear_Pooling_ECCV_2018_paper.html,ECCV,2018,https://github.com/ChaojianYu/Hierarchical-Bilinear-Pooling,57,1/2/2019 +CRAFT Objects From Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_CRAFT_Objects_From_CVPR_2016_paper.html,CVPR,2016,https://github.com/byangderek/CRAFT,41,1/2/2019 +Semantic Compositional Networks for Visual Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Gan_Semantic_Compositional_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/zhegan27/Semantic_Compositional_Nets,45,1/2/2019 +Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Exploit_the_Unknown_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Yu-Wu/Exploit-Unknown-Gradually,59,1/2/2019 +Real-World Anomaly Detection in Surveillance Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sultani_Real-World_Anomaly_Detection_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/WaqasSultani/AnomalyDetectionCVPR2018,72,1/2/2019 +Deriving Neural Architectures from Sequence and Graph Kernels,http://proceedings.mlr.press/v70/lei17a.html,ICML,2017,https://github.com/taolei87/icml17_knn,44,1/2/2019 +DeepVS: A Deep Learning Based Video Saliency Prediction Approach,http://openaccess.thecvf.com/content_ECCV_2018/html/Lai_Jiang_DeepVS_A_Deep_ECCV_2018_paper.html,ECCV,2018,https://github.com/remega/OMCNN_2CLSTM,53,1/2/2019 +Slicing Convolutional Neural Network for Crowd Video Understanding,http://openaccess.thecvf.com/content_cvpr_2016/html/Shao_Slicing_Convolutional_Neural_CVPR_2016_paper.html,CVPR,2016,https://github.com/amandajshao/Slicing-CNN,40,1/2/2019 +A Linear-Time Kernel Goodness-of-Fit Test,http://papers.nips.cc/paper/6630-a-linear-time-kernel-goodness-of-fit-test.pdf,NIPS,2017,https://github.com/wittawatj/kernel-gof,40,1/2/2019 +Stabilizing Training of Generative Adversarial Networks through Regularization,http://papers.nips.cc/paper/6797-stabilizing-training-of-generative-adversarial-networks-through-regularization.pdf,NIPS,2017,https://github.com/rothk/Stabilizing_GANs,45,1/2/2019 +RayNet: Learning Volumetric 3D Reconstruction With Ray Potentials,http://openaccess.thecvf.com/content_cvpr_2018/papers/Paschalidou_RayNet_Learning_Volumetric_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/paschalidoud/raynet,51,1/2/2019 +Rotation-Sensitive Regression for Oriented Scene Text Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liao_Rotation-Sensitive_Regression_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MhLiao/RRD,61,1/2/2019 +Learning Intrinsic Image Decomposition From Watching the World,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Intrinsic_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lixx2938/unsupervised-learning-intrinsic-images,45,1/2/2019 +Learning Efficient Single-stage Pedestrian Detectors by Asymptotic Localization Fitting,http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html,ECCV,2018,https://github.com/liuwei16/ALFNet,52,1/2/2019 +Neural Scene De-Rendering,http://openaccess.thecvf.com/content_cvpr_2017/html/Wu_Neural_Scene_De-Rendering_CVPR_2017_paper.html,CVPR,2017,https://github.com/jiajunwu/nsd,40,1/2/2019 +P-CNN: Pose-Based CNN Features for Action Recognition,http://openaccess.thecvf.com/content_iccv_2015/html/Cheron_P-CNN_Pose-Based_CNN_ICCV_2015_paper.html,ICCV,2015,https://github.com/gcheron/P-CNN,45,1/2/2019 +Video Re-localization,http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_Feng_Video_Re-localization_via_ECCV_2018_paper.html,ECCV,2018,https://github.com/fengyang0317/video_reloc,46,1/2/2019 +Image Manipulation with Perceptual Discriminators,http://openaccess.thecvf.com/content_ECCV_2018/html/Diana_Sungatullina_Image_Manipulation_with_ECCV_2018_paper.html,ECCV,2018,https://github.com/egorzakharov/PerceptualGAN,45,1/2/2019 +Unsupervised Adaptation for Deep Stereo,http://openaccess.thecvf.com/content_iccv_2017/html/Tonioni_Unsupervised_Adaptation_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/CVLAB-Unibo/Unsupervised-Adaptation-for-Deep-Stereo,44,1/2/2019 +Generalized Orderless Pooling Performs Implicit Salient Matching,http://openaccess.thecvf.com/content_iccv_2017/html/Simon_Generalized_Orderless_Pooling_ICCV_2017_paper.html,ICCV,2017,https://github.com/cvjena/alpha_pooling,42,1/2/2019 +Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,http://openaccess.thecvf.com/content_ECCV_2018/html/Baris_Gecer_Semi-supervised_Adversarial_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/barisgecer/facegan,55,1/2/2019 +Comparative 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Defocus,http://openaccess.thecvf.com/content_cvpr_2015/html/Barron_Fast_Bilateral-Space_Stereo_2015_CVPR_paper.html,CVPR,2015,https://github.com/tvandenzegel/fast_bilateral_space_stereo,29,1/2/2019 +Gated Fusion Network for Single Image Dehazing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ren_Gated_Fusion_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rwenqi/GFN-dehazing,35,1/2/2019 +Isolating Sources of Disentanglement in Variational Autoencoders,http://arxiv.org/abs/1802.04942v2,NIPS,2018,https://github.com/rtqichen/beta-tcvae,62,1/2/2019 +Learning Semantic Representations for Unsupervised Domain Adaptation,http://proceedings.mlr.press/v80/xie18c.html,ICML,2018,https://github.com/Mid-Push/Moving-Semantic-Transfer-Network,39,1/2/2019 +GP CaKe: Effective brain connectivity with causal kernels,http://papers.nips.cc/paper/6696-gp-cake-effective-brain-connectivity-with-causal-kernels.pdf,NIPS,2017,https://github.com/LucaAmbrogioni/GP-CaKe-project,46,1/2/2019 +CleanNet: Transfer Learning for Scalable Image Classifier Training With Label Noise,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_CleanNet_Transfer_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kuanghuei/clean-net,33,1/2/2019 +Recurrent Convolutional Neural Network for Object Recognition,http://openaccess.thecvf.com/content_cvpr_2015/html/Liang_Recurrent_Convolutional_Neural_2015_CVPR_paper.html,CVPR,2015,https://github.com/JimLee4530/RCNN,32,1/2/2019 +On the Robustness of Semantic Segmentation Models to Adversarial Attacks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Arnab_On_the_Robustness_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hmph/adversarial-attacks,31,1/2/2019 +3D Point Cloud Registration for Localization Using a Deep Neural Network Auto-Encoder,http://openaccess.thecvf.com/content_cvpr_2017/html/Elbaz_3D_Point_Cloud_CVPR_2017_paper.html,CVPR,2017,https://github.com/gilbaz/LORAX,32,1/2/2019 +Continual Learning Through Synaptic Intelligence,http://proceedings.mlr.press/v70/zenke17a.html,ICML,2017,https://github.com/ganguli-lab/pathint,31,1/2/2019 +In Defense of Color-Based Model-Free Tracking,http://openaccess.thecvf.com/content_cvpr_2015/html/Possegger_In_Defense_of_2015_CVPR_paper.html,CVPR,2015,https://github.com/foolwood/DAT,30,1/2/2019 +SeGAN: Segmenting and Generating the Invisible,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_SeGAN_Segmenting_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ehsanik/SeGAN,36,1/2/2019 +Unsupervised Learning of Disentangled Representations from Video,http://papers.nips.cc/paper/7028-unsupervised-learning-of-disentangled-representations-from-video.pdf,NIPS,2017,https://github.com/edenton/drnet-py,32,1/2/2019 +Deeply Learned Attributes for Crowded Scene Understanding,http://openaccess.thecvf.com/content_cvpr_2015/html/Shao_Deeply_Learned_Attributes_2015_CVPR_paper.html,CVPR,2015,https://github.com/amandajshao/www_deep_crowd,27,1/2/2019 +Parsimonious 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Grammar,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Human-Centric_Indoor_Scene_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/SiyuanQi/human-centric-scene-synthesis,33,1/2/2019 +The Sound of Pixels,http://openaccess.thecvf.com/content_ECCV_2018/html/Hang_Zhao_The_Sound_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/roudimit/MUSIC_dataset,40,1/2/2019 +Video Rain Streak Removal by Multiscale Convolutional Sparse Coding,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Video_Rain_Streak_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MinghanLi/MS-CSC-Rain-Streak-Removal,29,1/2/2019 +Adversarial Logit Pairing,http://arxiv.org/abs/1803.06373v1,NIPS,2018,https://github.com/labsix/adversarial-logit-pairing-analysis,32,1/2/2019 +Deflecting Adversarial Attacks With Pixel Deflection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Prakash_Deflecting_Adversarial_Attacks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/iamaaditya/pixel-deflection,34,1/2/2019 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Estimation,http://openaccess.thecvf.com/content_cvpr_2016/html/Chu_Structured_Feature_Learning_CVPR_2016_paper.html,CVPR,2016,https://github.com/chuxiaoselena/StructuredFeature,29,1/2/2019 +Dense Semantic Image Segmentation with Objects and Attributes,http://openaccess.thecvf.com/content_cvpr_2014/html/Zheng_Dense_Semantic_Image_2014_CVPR_paper.html,CVPR,2014,https://github.com/bittnt/ImageSpirit,28,1/2/2019 +Scene-Independent Group Profiling in Crowd,http://openaccess.thecvf.com/content_cvpr_2014/html/Shao_Scene-Independent_Group_Profiling_2014_CVPR_paper.html,CVPR,2014,https://github.com/amandajshao/crowd_group_profile,28,1/2/2019 +Hierarchical Boundary-Aware Neural Encoder for Video Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Baraldi_Hierarchical_Boundary-Aware_Neural_CVPR_2017_paper.html,CVPR,2017,https://github.com/Yugnaynehc/banet,33,1/2/2019 +Neural Guided Constraint Logic Programming for Program Synthesis,http://arxiv.org/abs/1809.02840v2,NIPS,2018,https://github.com/xuexue/neuralkanren,32,1/2/2019 +Ordinal Regression With Multiple Output CNN for Age Estimation,http://openaccess.thecvf.com/content_cvpr_2016/html/Niu_Ordinal_Regression_With_CVPR_2016_paper.html,CVPR,2016,https://github.com/luoyetx/OrdinalRegression,30,1/2/2019 +Unsupervised Learning of Edges,http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Unsupervised_Learning_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/happyharrycn/unsupervised_edges,29,1/2/2019 +TOM-Net: Learning Transparent Object Matting From a Single Image,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_TOM-Net_Learning_Transparent_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/guanyingc/TOM-Net,30,1/2/2019 +Harvesting Multiple Views for Marker-Less 3D Human Pose Annotations,http://openaccess.thecvf.com/content_cvpr_2017/html/Pavlakos_Harvesting_Multiple_Views_CVPR_2017_paper.html,CVPR,2017,https://github.com/geopavlakos/harvesting,27,1/2/2019 +PatchBatch: A Batch Augmented Loss for Optical Flow,http://openaccess.thecvf.com/content_cvpr_2016/html/Gadot_PatchBatch_A_Batch_CVPR_2016_paper.html,CVPR,2016,https://github.com/DediGadot/PatchBatch,27,1/2/2019 +Real-Time Monocular Depth Estimation Using Synthetic Data With Domain Adaptation via Image Style Transfer,http://openaccess.thecvf.com/content_cvpr_2018/papers/Atapour-Abarghouei_Real-Time_Monocular_Depth_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/atapour/monocularDepth-Inference,37,1/2/2019 +Deep Co-Occurrence Feature Learning for Visual Object Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Shih_Deep_Co-Occurrence_Feature_CVPR_2017_paper.html,CVPR,2017,https://github.com/yafangshih/Deep-COOC,29,1/2/2019 +"Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition",http://openaccess.thecvf.com/content_cvpr_2015/html/Zhu_Understanding_Tools_Task-Oriented_2015_CVPR_paper.html,CVPR,2015,https://github.com/xiaozhuchacha/Kinect2Toolbox,27,1/2/2019 +Quaternion Convolutional Neural Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Xuanyu_Zhu_Quaternion_Convolutional_Neural_ECCV_2018_paper.html,ECCV,2018,https://github.com/TParcollet/Quaternion-Convolutional-Neural-Networks-for-End-to-End-Automatic-Speech-Recognition,30,1/2/2019 +Learning Dynamic Memory Networks for Object Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Tianyu_Yang_Learning_Dynamic_Memory_ECCV_2018_paper.html,ECCV,2018,https://github.com/skyoung/MemTrack,32,1/2/2019 +Viewpoints and Keypoints,http://openaccess.thecvf.com/content_cvpr_2015/html/Tulsiani_Viewpoints_and_Keypoints_2015_CVPR_paper.html,CVPR,2015,https://github.com/shubhtuls/ViewpointsAndKeypoints,25,1/2/2019 +DeepCD: Learning Deep Complementary Descriptors for Patch Representations,http://openaccess.thecvf.com/content_iccv_2017/html/Yang_DeepCD_Learning_Deep_ICCV_2017_paper.html,ICCV,2017,https://github.com/shamangary/DeepCD,26,1/2/2019 +Interpretable Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Interpretable_Convolutional_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/seongjunyun/CNN-with-Dual-Local-and-Global-Attention,40,1/2/2019 +Learning to Detect Salient Objects With Image-Level Supervision,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Learning_to_Detect_CVPR_2017_paper.html,CVPR,2017,https://github.com/scott89/WSS,26,1/2/2019 +Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields,http://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Realtime_Multi-Person_2D_CVPR_2017_paper.html,CVPR,2017,https://github.com/PoseAIChallenger/mxnet_pose_for_AI_challenger,29,1/2/2019 +Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Liang_Deep_Variation-Structured_Reinforcement_CVPR_2017_paper.html,CVPR,2017,https://github.com/nexusapoorvacus/DeepVariationStructuredRL,32,1/2/2019 +State-Frequency Memory Recurrent Neural Networks,http://proceedings.mlr.press/v70/hu17c.html,ICML,2017,https://github.com/hhkunming/State-Frequency-Memory-Recurrent-Neural-Networks,27,1/2/2019 +Deep 360 Pilot: Learning a Deep Agent for Piloting Through 360deg Sports Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Hu_Deep_360_Pilot_CVPR_2017_paper.html,CVPR,2017,https://github.com/eborboihuc/Deep360Pilot-CVPR17,27,1/2/2019 +Mask-Guided Contrastive Attention Model for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_Mask-Guided_Contrastive_Attention_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/developfeng/MGCAM,41,1/2/2019 +Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon,http://papers.nips.cc/paper/7071-learning-to-prune-deep-neural-networks-via-layer-wise-optimal-brain-surgeon.pdf,NIPS,2017,https://github.com/csyhhu/L-OBS,31,1/2/2019 +Neural Message Passing for Quantum Chemistry,http://proceedings.mlr.press/v70/gilmer17a.html,ICML,2017,https://github.com/brain-research/mpnn,27,1/2/2019 +Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure,http://papers.nips.cc/paper/6760-stochastic-optimization-with-variance-reduction-for-infinite-datasets-with-finite-sum-structure.pdf,NIPS,2017,https://github.com/albietz/stochs,26,1/2/2019 +Recurrent Scene Parsing With Perspective Understanding in the Loop,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kong_Recurrent_Scene_Parsing_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/aimerykong/Recurrent-Scene-Parsing-with-Perspective-Understanding-in-the-loop,29,1/2/2019 +Disentangling by Factorising,http://proceedings.mlr.press/v80/kim18b.html,ICML,2018,https://github.com/1Konny/FactorVAE,37,1/2/2019 +Actionness Estimation Using Hybrid Fully Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Actionness_Estimation_Using_CVPR_2016_paper.html,CVPR,2016,https://github.com/wanglimin/Actionness-Estimation,26,1/2/2019 +Tangent Convolutions for Dense Prediction in 3D,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tatarchenko_Tangent_Convolutions_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tatarchm/tangent_conv,37,1/2/2019 +SketchyScene: Richly-Annotated Scene Sketches,http://openaccess.thecvf.com/content_ECCV_2018/html/Changqing_Zou_SketchyScene_Richly-Annotated_Scene_ECCV_2018_paper.html,ECCV,2018,https://github.com/SketchyScene/SketchyScene,31,1/2/2019 +Learning to Evaluate Image Captioning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cui_Learning_to_Evaluate_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/richardaecn/cvpr18-caption-eval,38,1/2/2019 +Joint distribution optimal transportation for domain adaptation,http://papers.nips.cc/paper/6963-joint-distribution-optimal-transportation-for-domain-adaptation.pdf,NIPS,2017,https://github.com/rflamary/JDOT,29,1/2/2019 +Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors,http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_SpeedAccuracy_Trade-Offs_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/rayanelleuch/Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors,26,1/2/2019 +Unconstrained 3D Face Reconstruction,http://openaccess.thecvf.com/content_cvpr_2015/html/Roth_Unconstrained_3D_Face_2015_CVPR_paper.html,CVPR,2015,https://github.com/NJUPole/CVPR2015-Unconstrained-3D-Face-Reconstruction,26,1/2/2019 +Adversarially Learned One-Class Classifier for Novelty Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sabokrou_Adversarially_Learned_One-Class_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/khalooei/ALOCC-CVPR2018,37,1/2/2019 +Layer-structured 3D Scene Inference via View Synthesis,http://openaccess.thecvf.com/content_ECCV_2018/html/Shubham_Tulsiani_Layer-structured_3D_Scene_ECCV_2018_paper.html,ECCV,2018,https://github.com/google/layered-scene-inference,28,1/2/2019 +Learning Spread-Out Local Feature Descriptors,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Learning_Spread-Out_Local_ICCV_2017_paper.html,ICCV,2017,https://github.com/ColumbiaDVMM/Spread-out_Local_Feature_Descriptor,28,1/2/2019 +Recurrent Attention Models for Depth-Based Person Identification,http://openaccess.thecvf.com/content_cvpr_2016/html/Haque_Recurrent_Attention_Models_CVPR_2016_paper.html,CVPR,2016,https://github.com/ahaque/ram_person_id,24,9/16/2018 +Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Lei_Zhu_Bi-directional_Feature_Pyramid_ECCV_2018_paper.html,ECCV,2018,https://github.com/zijundeng/BDRAR,32,1/2/2019 +Controllable Video Generation With Sparse Trajectories,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hao_Controllable_Video_Generation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zekunhao1995/ControllableVideoGen,28,1/2/2019 +First Order Generative Adversarial Networks,http://proceedings.mlr.press/v80/seward18a.html,ICML,2018,https://github.com/zalandoresearch/first_order_gan,25,1/2/2019 +Data-Driven 3D Voxel Patterns for Object Category Recognition,http://openaccess.thecvf.com/content_cvpr_2015/html/Xiang_Data-Driven_3D_Voxel_2015_CVPR_paper.html,CVPR,2015,https://github.com/yuxng/3DVP,24,1/2/2019 +Blazingly Fast Video Object Segmentation With Pixel-Wise Metric Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Blazingly_Fast_Video_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yuhuayc/fast-vos,30,1/2/2019 +Revisiting Video Saliency: A Large-Scale Benchmark and a New Model,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Revisiting_Video_Saliency_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wenguanwang/DHF1K,30,1/2/2019 +Temporal Context Network for Activity Localization in Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Dai_Temporal_Context_Network_ICCV_2017_paper.html,ICCV,2017,https://github.com/vdavid70619/TCN,24,1/2/2019 +Universal Adversarial Perturbations,http://openaccess.thecvf.com/content_cvpr_2017/html/Moosavi-Dezfooli_Universal_Adversarial_Perturbations_CVPR_2017_paper.html,CVPR,2017,https://github.com/val-iisc/fast-feature-fool,24,1/2/2019 +Shrinkage Fields for Effective Image Restoration,http://openaccess.thecvf.com/content_cvpr_2014/html/Schmidt_Shrinkage_Fields_for_2014_CVPR_paper.html,CVPR,2014,https://github.com/uschmidt83/shrinkage-fields,25,1/2/2019 +Interpretable Intuitive Physics Model,http://openaccess.thecvf.com/content_ECCV_2018/html/Tian_Ye_Interpretable_Intuitive_Physics_ECCV_2018_paper.html,ECCV,2018,https://github.com/tianye95/interpretable-intuitive-physics-model,27,1/2/2019 +Holistically-Nested Edge Detection,http://openaccess.thecvf.com/content_iccv_2015/html/Xie_Holistically-Nested_Edge_Detection_ICCV_2015_paper.html,ICCV,2015,https://github.com/s9xie/hed_release-deprecated,25,1/2/2019 +Improved Variational Autoencoders for Text Modeling using Dilated Convolutions,http://proceedings.mlr.press/v70/yang17d.html,ICML,2017,https://github.com/ryokamoi/dcnn_textvae,26,1/2/2019 +YASS: Yet Another Spike Sorter,http://papers.nips.cc/paper/6989-yass-yet-another-spike-sorter.pdf,NIPS,2017,https://github.com/paninski-lab/yass,25,1/2/2019 +Phase-Based Frame Interpolation for Video,http://openaccess.thecvf.com/content_cvpr_2015/html/Meyer_Phase-Based_Frame_Interpolation_2015_CVPR_paper.html,CVPR,2015,https://github.com/owang/PhaseBasedInterpolation,28,1/2/2019 +Going Deeper With Convolutions,http://openaccess.thecvf.com/content_cvpr_2015/html/Szegedy_Going_Deeper_With_2015_CVPR_paper.html,CVPR,2015,https://github.com/nutszebra/googlenet,25,1/2/2019 +Shading Annotations in the Wild,http://openaccess.thecvf.com/content_cvpr_2017/html/Kovacs_Shading_Annotations_in_CVPR_2017_paper.html,CVPR,2017,https://github.com/kovibalu/saw_release,24,1/2/2019 +Deep Texture Manifold for Ground Terrain Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xue_Deep_Texture_Manifold_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiaxue1993/Deep-Encoding-Pooling-Network-DEP-,25,1/2/2019 +Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Structured_Attention_Guided_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/danxuhk/StructuredAttentionDepthEstimation,46,1/2/2019 +IQA: Visual Question Answering in Interactive Environments,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gordon_IQA_Visual_Question_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/danielgordon10/thor-iqa-cvpr-2018,60,1/2/2019 +Real-Time Neural Style Transfer for Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Huang_Real-Time_Neural_Style_CVPR_2017_paper.html,CVPR,2017,https://github.com/curaai00/RT-StyleTransfer-forVideo,30,1/2/2019 +Deep Regression Tracking with Shrinkage Loss,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiankai_Lu_Deep_Regression_Tracking_ECCV_2018_paper.html,ECCV,2018,https://github.com/chaoma99/DSLT,34,1/2/2019 +Multi-Agent Diverse Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ghosh_Multi-Agent_Diverse_Generative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/arnabgho/MADGAN,23,9/16/2018 +Reducing Reparameterization Gradient Variance,http://papers.nips.cc/paper/6961-reducing-reparameterization-gradient-variance.pdf,NIPS,2017,https://github.com/andymiller/ReducedVarianceReparamGradients,24,1/2/2019 +"You Only Look Once: Unified, Real-Time Object Detection",http://openaccess.thecvf.com/content_cvpr_2016/html/Redmon_You_Only_Look_CVPR_2016_paper.html,CVPR,2016,https://github.com/andersy005/keras-yolo,26,1/2/2019 +Fast Training of Triplet-Based Deep Binary Embedding Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhuang_Fast_Training_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/xwzy/Triplet-deep-hash-pytorch,25,1/2/2019 +L0TV: A New Method for Image Restoration in the Presence of Impulse Noise,http://openaccess.thecvf.com/content_cvpr_2015/html/Yuan_L0TV_A_New_2015_CVPR_paper.html,CVPR,2015,https://github.com/peisuke/L0TV,22,1/2/2019 +Adaptive Color Attributes for Real-Time Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2014/html/Danelljan_Adaptive_Color_Attributes_2014_CVPR_paper.html,CVPR,2014,https://github.com/mostafaizz/ColorTracker,25,1/2/2019 +Domain-Adaptive Deep Network Compression,http://openaccess.thecvf.com/content_iccv_2017/html/Masana_Domain-Adaptive_Deep_Network_ICCV_2017_paper.html,ICCV,2017,https://github.com/mmasana/DALR,24,1/2/2019 +Interspecies Knowledge Transfer for Facial Keypoint Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Rashid_Interspecies_Knowledge_Transfer_CVPR_2017_paper.html,CVPR,2017,https://github.com/menorashid/animal_human_kp,25,1/2/2019 +Zero-Order Reverse Filtering,http://openaccess.thecvf.com/content_iccv_2017/html/Tao_Zero-Order_Reverse_Filtering_ICCV_2017_paper.html,ICCV,2017,https://github.com/jiangsutx/DeFilter,23,1/2/2019 +Reconstructing the World* in Six Days *(As Captured by the Yahoo 100 Million Image Dataset),http://openaccess.thecvf.com/content_cvpr_2015/html/Heinly_Reconstructing_the_World_2015_CVPR_paper.html,CVPR,2015,https://github.com/jheinly/streaming_connected_component_discovery,25,1/2/2019 +Learning High Dynamic Range From Outdoor Panoramas,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Learning_High_Dynamic_ICCV_2017_paper.html,ICCV,2017,https://github.com/jacenfox/ldr2hdr-public,26,1/2/2019 +A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering,http://papers.nips.cc/paper/6734-a-dirichlet-mixture-model-of-hawkes-processes-for-event-sequence-clustering.pdf,NIPS,2017,https://github.com/HongtengXu/Hawkes-Process-Toolkit,24,1/2/2019 +Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Multimodal_Transfer_A_CVPR_2017_paper.html,CVPR,2017,https://github.com/fullfanta/multimodal_transfer,22,1/2/2019 +Contrastive Learning for Image Captioning,http://papers.nips.cc/paper/6691-contrastive-learning-for-image-captioning.pdf,NIPS,2017,https://github.com/doubledaibo/clcaption_nips2017,26,1/2/2019 +Graph-Cut RANSAC,http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/danini/graph-cut-ransac,32,1/2/2019 +A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising,http://openaccess.thecvf.com/content_ECCV_2018/html/XU_JUN_A_Trilateral_Weighted_ECCV_2018_paper.html,ECCV,2018,https://github.com/csjunxu/TWSC-ECCV2018,30,1/2/2019 +Phrase Localization and Visual Relationship Detection With Comprehensive Image-Language Cues,http://openaccess.thecvf.com/content_iccv_2017/html/Plummer_Phrase_Localization_and_ICCV_2017_paper.html,ICCV,2017,https://github.com/BryanPlummer/pl-clc,27,1/2/2019 +Conditional Image-to-Image Translation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Conditional_Image-to-Image_Translation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/znxlwm/pytorch-Conditional-image-to-image-translation,25,1/2/2019 +Learning to Promote Saliency Detectors,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zeng_Learning_to_Promote_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zengxianyu/lps,21,1/2/2019 +LF-Net: Learning Local Features from Images,https://arxiv.org/abs/1805.09662,NIPS,2018,https://github.com/vcg-uvic/lf-net-release,55,1/2/2019 +Straight to Shapes: Real-Time Detection of Encoded Shapes,http://openaccess.thecvf.com/content_cvpr_2017/html/Jetley_Straight_to_Shapes_CVPR_2017_paper.html,CVPR,2017,https://github.com/torrvision/straighttoshapes,23,1/2/2019 +Visualizing the Loss Landscape of Neural Nets,http://arxiv.org/abs/1712.09913v2,NIPS,2018,https://github.com/tomgoldstein/loss-landscape,724,1/2/2019 +First Person Action Recognition Using Deep Learned Descriptors,http://openaccess.thecvf.com/content_cvpr_2016/html/Singh_First_Person_Action_CVPR_2016_paper.html,CVPR,2016,https://github.com/suriyasingh/EgoConvNet,21,1/2/2019 +Exploring Disentangled Feature Representation Beyond Face Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Exploring_Disentangled_Feature_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sciencefans/D2AE-Face-Generator,29,1/2/2019 +Between-Class Learning for Image Classification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tokozume_Between-Class_Learning_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mil-tokyo/bc_learning_image,26,1/2/2019 +CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Batsos_CBMV_A_Coalesced_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kbatsos/CBMV,25,1/2/2019 +Dense Human Body Correspondences Using Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Dense_Human_Body_CVPR_2016_paper.html,CVPR,2016,https://github.com/halimacc/DenseHumanBodyCorrespondences,27,1/2/2019 +Hash Embeddings for Efficient Word Representations,http://papers.nips.cc/paper/7078-hash-embeddings-for-efficient-word-representations.pdf,NIPS,2017,https://github.com/dsv77/hashembedding/,21,9/16/2018 +Exploiting Saliency for Object Segmentation From Image Level Labels,http://openaccess.thecvf.com/content_cvpr_2017/html/Oh_Exploiting_Saliency_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/coallaoh/GuidedLabelling,24,1/2/2019 +Improving Shape Deformation in Unsupervised Image-to-Image Translation,http://openaccess.thecvf.com/content_ECCV_2018/html/Aaron_Gokaslan_Improving_Shape_Deformation_ECCV_2018_paper.html,ECCV,2018,https://github.com/brownvc/ganimorph,33,1/2/2019 +Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net,http://papers.nips.cc/paper/7026-variational-walkback-learning-a-transition-operator-as-a-stochastic-recurrent-net.pdf,NIPS,2017,https://github.com/anirudh9119/walkback_nips17,23,1/2/2019 +Eye In-Painting With Exemplar Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Dolhansky_Eye_In-Painting_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhangqianhui/Exemplar-GAN-Eye-Inpainting-Tensorflow,35,1/2/2019 +EC-Net: an Edge-aware Point set Consolidation Network,http://openaccess.thecvf.com/content_ECCV_2018/html/Lequan_Yu_EC-Net_an_Edge-aware_ECCV_2018_paper.html,ECCV,2018,https://github.com/yulequan/EC-Net,27,1/2/2019 +Asymmetric Tri-training for Unsupervised Domain Adaptation,http://proceedings.mlr.press/v70/saito17a.html,ICML,2017,https://github.com/vtddggg/ATDA,24,1/2/2019 +Detecting Vanishing Points Using Global Image Context in a Non-Manhattan World,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhai_Detecting_Vanishing_Points_CVPR_2016_paper.html,CVPR,2016,https://github.com/viibridges/gc-horizon-detector,22,1/2/2019 +STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling,http://openaccess.thecvf.com/content_cvpr_2017/html/He_STD2P_RGBD_Semantic_CVPR_2017_paper.html,CVPR,2017,https://github.com/SSAW14/STD2P,22,1/2/2019 +Deep Mean-Shift Priors for Image Restoration,http://papers.nips.cc/paper/6678-deep-mean-shift-priors-for-image-restoration.pdf,NIPS,2017,https://github.com/siavashBigdeli/DMSP,20,1/2/2019 +Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Beyond_Frontal_Faces_2015_CVPR_paper.html,CVPR,2015,https://github.com/sciencefans/Beyond-Frontal-Faces,21,1/2/2019 +SimplE Embedding for Link Prediction in Knowledge Graphs,http://arxiv.org/abs/1802.04868v1,NIPS,2018,https://github.com/Mehran-k/SimplE,42,1/2/2019 +Learning Continuous Semantic Representations of Symbolic Expressions,http://proceedings.mlr.press/v70/allamanis17a.html,ICML,2017,https://github.com/mast-group/eqnet,22,1/2/2019 +CondenseNet: An Efficient DenseNet Using Learned Group Convolutions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_CondenseNet_An_Efficient_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/markdtw/condensenet-tensorflow,22,1/2/2019 +The Numerics of GANs,http://papers.nips.cc/paper/6779-the-numerics-of-gans.pdf,NIPS,2017,https://github.com/LMescheder/TheNumericsOfGANs,20,1/2/2019 +Dense Captioning With Joint Inference and Visual Context,http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Dense_Captioning_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/linjieyangsc/densecap,24,1/2/2019 +Learning Convolutional Networks for Content-Weighted Image Compression,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Learning_Convolutional_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/limuhit/ImageCompression,25,1/2/2019 +SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Faraone_SYQ_Learning_Symmetric_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/julianfaraone/SYQ,24,1/2/2019 +Weakly-Supervised Learning of Visual Relations,http://openaccess.thecvf.com/content_iccv_2017/html/Peyre_Weakly-Supervised_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/jpeyre/unrel,20,1/2/2019 +CSGNet: Neural Shape Parser for Constructive Solid Geometry,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sharma_CSGNet_Neural_Shape_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Hippogriff/CSGNet,21,1/2/2019 +Towards Accurate Multi-Person Pose Estimation in the Wild,http://openaccess.thecvf.com/content_cvpr_2017/html/Papandreou_Towards_Accurate_Multi-Person_CVPR_2017_paper.html,CVPR,2017,https://github.com/hackiey/keypoints,30,1/2/2019 +Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Nguyen_Improved_Fusion_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cvlab-tohoku/Dense-CoAttention-Network,33,1/2/2019 +Real-time 'Actor-Critic' Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Boyu_Chen_Real-time_Actor-Critic_Tracking_ECCV_2018_paper.html,ECCV,2018,https://github.com/bychen515/ACT,46,1/2/2019 +Flow-Grounded Spatial-Temporal Video Prediction from Still Images,http://openaccess.thecvf.com/content_ECCV_2018/html/Yijun_Li_Flow-Grounded_Spatial-Temporal_Video_ECCV_2018_paper.html,ECCV,2018,https://github.com/Yijunmaverick/FlowGrounded-VideoPrediction,32,1/2/2019 +Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings,http://proceedings.mlr.press/v80/co-reyes18a.html,ICML,2018,https://github.com/wyndwarrior/Sectar,29,1/2/2019 +Dual Discriminator Generative Adversarial Nets,http://papers.nips.cc/paper/6860-dual-discriminator-generative-adversarial-nets.pdf,NIPS,2017,https://github.com/tund/D2GAN,23,1/2/2019 +Partial Transfer Learning With Selective Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Partial_Transfer_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/thuml/SAN,26,1/2/2019 +Learning Single-View 3D Reconstruction with Limited Pose Supervision,http://openaccess.thecvf.com/content_ECCV_2018/html/Guandao_Yang_A_Unified_Framework_ECCV_2018_paper.html,ECCV,2018,https://github.com/stevenygd/3d-recon,33,1/2/2019 +Cross-Modal Deep Variational Hand Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Spurr_Cross-Modal_Deep_Variational_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/spurra/vae-hands-3d,26,1/2/2019 +Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search,http://proceedings.mlr.press/v80/suganuma18a.html,ICML,2018,https://github.com/sg-nm/Evolutionary-Autoencoders,23,1/2/2019 +Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization,http://openaccess.thecvf.com/content_iccv_2017/html/Coskun_Long_Short-Term_Memory_ICCV_2017_paper.html,ICCV,2017,https://github.com/Seleucia/lstmkf_ICCV2017,24,1/2/2019 +Speaker-Follower Models for Vision-and-Language Navigation,https://arxiv.org/abs/1806.02724,NIPS,2018,https://github.com/ronghanghu/speaker_follower,33,1/2/2019 +Learning Mid-level Filters for Person Re-identification,http://openaccess.thecvf.com/content_cvpr_2014/html/Zhao_Learning_Mid-level_Filters_2014_CVPR_paper.html,CVPR,2014,https://github.com/Robert0812/midfilter_reid,20,1/2/2019 +Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Liang-Chieh_Chen_Encoder-Decoder_with_Atrous_ECCV_2018_paper.html,ECCV,2018,https://github.com/qixuxiang/deeplabv3plus,28,1/2/2019 +Deep Growing Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Wang_Deep_Growing_Learning_ICCV_2017_paper.html,ICCV,2017,https://github.com/QData/deep2Read,21,1/2/2019 +When Unsupervised Domain Adaptation Meets Tensor Representations,http://openaccess.thecvf.com/content_iccv_2017/html/Lu_When_Unsupervised_Domain_ICCV_2017_paper.html,ICCV,2017,https://github.com/poppinace/TAISL,22,1/2/2019 +DropoutNet: Addressing Cold Start in Recommender Systems,http://papers.nips.cc/paper/7081-dropoutnet-addressing-cold-start-in-recommender-systems.pdf,NIPS,2017,https://github.com/layer6ai-labs/DropoutNet,27,1/2/2019 +Incremental Learning of Object Detectors Without Catastrophic Forgetting,http://openaccess.thecvf.com/content_iccv_2017/html/Shmelkov_Incremental_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/kshmelkov/incremental_detectors,24,1/2/2019 +Adversarial Feature Matching for Text Generation,http://proceedings.mlr.press/v70/zhang17b.html,ICML,2017,https://github.com/Jeff-HOU/UROP-Adversarial-Feature-Matching-for-Text-Generation,18,1/2/2019 +Explicit Inductive Bias for Transfer Learning with Convolutional Networks,http://proceedings.mlr.press/v80/li18a.html,ICML,2018,https://github.com/holyseven/TransferLearningClassification,24,1/2/2019 +Learning to Blend Photos,http://openaccess.thecvf.com/content_ECCV_2018/html/Wei-Chih_Hung_Learning_to_Blend_ECCV_2018_paper.html,ECCV,2018,https://github.com/hfslyc/LearnToBlend,42,1/2/2019 +Open Set Domain Adaptation,http://openaccess.thecvf.com/content_iccv_2017/html/Busto_Open_Set_Domain_ICCV_2017_paper.html,ICCV,2017,https://github.com/Heliot7/open-set-da,25,1/2/2019 +Learning to Pivot with Adversarial Networks,http://papers.nips.cc/paper/6699-learning-to-pivot-with-adversarial-networks.pdf,NIPS,2017,https://github.com/glouppe/paper-learning-to-pivot,21,1/2/2019 +A Generative Adversarial Approach for Zero-Shot Learning From Noisy Texts,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhu_A_Generative_Adversarial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/EthanZhu90/ZSL_GAN_CVPR18,122,1/2/2019 +Event-Based Visual Inertial Odometry,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Event-Based_Visual_Inertial_CVPR_2017_paper.html,CVPR,2017,https://github.com/daniilidis-group/event_feature_tracking,27,1/2/2019 +Hyperbolic Neural Networks,http://arxiv.org/abs/1805.09112v2,NIPS,2018,https://github.com/dalab/hyperbolic_nn,37,1/2/2019 +LEGO: Learning Edge With Geometry All at Once by Watching Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_LEGO_Learning_Edge_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhenheny/LEGO,24,1/2/2019 +Audio-Visual Event Localization in Unconstrained Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Yapeng_Tian_Audio-Visual_Event_Localization_ECCV_2018_paper.html,ECCV,2018,https://github.com/YapengTian/AVE-ECCV18,25,1/2/2019 +Learning Dynamic Siamese Network for Visual Object Tracking,http://openaccess.thecvf.com/content_iccv_2017/html/Guo_Learning_Dynamic_Siamese_ICCV_2017_paper.html,ICCV,2017,https://github.com/tsingqguo/DSiam,21,1/2/2019 +Structured Generative Adversarial Networks,http://papers.nips.cc/paper/6979-structured-generative-adversarial-networks.pdf,NIPS,2017,https://github.com/thudzj/StructuredGAN,19,1/2/2019 +Neural Code Comprehension: A Learnable Representation of Code Semantics,http://arxiv.org/abs/1806.07336v2,NIPS,2018,https://github.com/spcl/ncc,35,1/2/2019 +Im2Flow: Motion Hallucination From Static Images for Action Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gao_Im2Flow_Motion_Hallucination_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/rhgao/Im2Flow,22,1/2/2019 +Deep Reinforcement Learning of Marked Temporal Point Processes,http://arxiv.org/abs/1805.09360v1,NIPS,2018,https://github.com/Networks-Learning/tpprl,24,1/2/2019 +Understanding Deep Features With Computer-Generated Imagery,http://openaccess.thecvf.com/content_iccv_2015/html/Aubry_Understanding_Deep_Features_ICCV_2015_paper.html,ICCV,2015,https://github.com/mathieuaubry/features_analysis,19,1/2/2019 +Single Shot Scene Text Retrieval,http://openaccess.thecvf.com/content_ECCV_2018/html/Lluis_Gomez_Single_Shot_Scene_ECCV_2018_paper.html,ECCV,2018,https://github.com/lluisgomez/single-shot-str,29,1/2/2019 +Deep Randomized Ensembles for Metric Learning,http://openaccess.thecvf.com/content_ECCV_2018/html/Hong_Xuan_Randomized_Ensemble_Embeddings_ECCV_2018_paper.html,ECCV,2018,https://github.com/littleredxh/DREML,30,1/2/2019 +Image Super-Resolution Using Dense Skip Connections,http://openaccess.thecvf.com/content_iccv_2017/html/Tong_Image_Super-Resolution_Using_ICCV_2017_paper.html,ICCV,2017,https://github.com/kweisamx/TensorFlow-SR-DenseNet,22,1/2/2019 +Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Hallucinated-IQA_No-Reference_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kwanyeelin/HIQA,22,1/2/2019 +Neural Architecture Search with Bayesian Optimisation and Optimal Transport,https://arxiv.org/abs/1802.07191,NIPS,2018,https://github.com/kirthevasank/nasbot,39,1/2/2019 +Joint Gap Detection and Inpainting of Line Drawings,http://openaccess.thecvf.com/content_cvpr_2017/html/Sasaki_Joint_Gap_Detection_CVPR_2017_paper.html,CVPR,2017,https://github.com/kaidlc/CVPR2017_linedrawings,19,1/2/2019 +Learning to Multitask,http://arxiv.org/abs/1805.07541v1,NIPS,2018,https://github.com/jfutoma/MGP-RNN,22,1/2/2019 +Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier,http://proceedings.mlr.press/v70/futoma17a.html,ICML,2017,https://github.com/jfutoma/MGP-RNN,22,1/2/2019 +Combined Group and Exclusive Sparsity for Deep Neural Networks,http://proceedings.mlr.press/v70/yoon17a.html,ICML,2017,https://github.com/jaehong-yoon93/CGES,21,1/2/2019 +Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Skeleton_Key_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/feiyu1990/Skeleton-key,20,1/2/2019 +Deep High Dynamic Range Imaging with Large Foreground Motions,http://openaccess.thecvf.com/content_ECCV_2018/html/Shangzhe_Wu_Deep_High_Dynamic_ECCV_2018_paper.html,ECCV,2018,https://github.com/elliottwu/DeepHDR,30,1/2/2019 +Who Let the Dogs Out? Modeling Dog Behavior From Visual Data,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ehsani_Who_Let_the_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ehsanik/dogTorch,27,1/2/2019 +GraphBit: Bitwise Interaction Mining via Deep Reinforcement Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Duan_GraphBit_Bitwise_Interaction_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/duanyq14/GraphBit,20,1/2/2019 +Stochastic Generative Hashing,http://proceedings.mlr.press/v70/dai17a.html,ICML,2017,https://github.com/doubling/Stochastic_Generative_Hashing,18,1/2/2019 +Minimal Scene Descriptions from Structure from Motion Models,http://openaccess.thecvf.com/content_cvpr_2014/html/Cao_Minimal_Scene_Descriptions_2014_CVPR_paper.html,CVPR,2014,https://github.com/caosong/minimal_scene,22,1/2/2019 +Context Selection for Embedding 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Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_PiCANet_Learning_Pixel-Wise_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Ugness/PiCANet-Implementation,28,1/2/2019 +A Bayesian Data Augmentation Approach for Learning Deep Models,http://papers.nips.cc/paper/6872-a-bayesian-data-augmentation-approach-for-learning-deep-models.pdf,NIPS,2017,https://github.com/toantm/keras-bda,18,1/2/2019 +Attentive Semantic Video Generation Using Captions,http://openaccess.thecvf.com/content_iccv_2017/html/Marwah_Attentive_Semantic_Video_ICCV_2017_paper.html,ICCV,2017,https://github.com/Singularity42/cap2vid,18,1/2/2019 +Diversity Regularized Spatiotemporal Attention for Video-Based Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Diversity_Regularized_Spatiotemporal_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ShuangLI59/Diversity-Regularized-Spatiotemporal-Attention,25,1/2/2019 +Accumulated Stability Voting: A Robust Descriptor From Descriptors of Multiple Scales,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Accumulated_Stability_Voting_CVPR_2016_paper.html,CVPR,2016,https://github.com/shamangary/ASV,19,1/2/2019 +PieAPP: Perceptual Image-Error Assessment Through Pairwise Preference,http://openaccess.thecvf.com/content_cvpr_2018/papers/Prashnani_PieAPP_Perceptual_Image-Error_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/prashnani/PerceptualImageError,36,1/2/2019 +Link Prediction Based on Graph Neural Networks,http://arxiv.org/abs/1802.09691v2,NIPS,2018,https://github.com/muhanzhang/SEAL,41,1/2/2019 +Multi-scale Residual Network for Image Super-Resolution,http://openaccess.thecvf.com/content_ECCV_2018/html/Juncheng_Li_Multi-scale_Residual_Network_ECCV_2018_paper.html,ECCV,2018,https://github.com/MIVRC/MSRN-PyTorch,41,1/2/2019 +Learning Compact Geometric Features,http://openaccess.thecvf.com/content_iccv_2017/html/Khoury_Learning_Compact_Geometric_ICCV_2017_paper.html,ICCV,2017,https://github.com/marckhoury/CGF,19,1/2/2019 +GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints,http://openaccess.thecvf.com/content_ECCV_2018/html/Zixin_Luo_Learning_Local_Descriptors_ECCV_2018_paper.html,ECCV,2018,https://github.com/lzx551402/geodesc,32,1/2/2019 +Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow,http://openaccess.thecvf.com/content_cvpr_2014/html/Bao_Fast_Edge-Preserving_PatchMatch_2014_CVPR_paper.html,CVPR,2014,https://github.com/linchaobao/EPPM,18,1/2/2019 +Scene Parsing With Global Context Embedding,http://openaccess.thecvf.com/content_iccv_2017/html/Hung_Scene_Parsing_With_ICCV_2017_paper.html,ICCV,2017,https://github.com/hfslyc/GCPNet,20,1/2/2019 +DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors,http://arxiv.org/abs/1805.07445v3,NIPS,2018,https://github.com/dojoteef/dvae,18,1/2/2019 +Deep Metric Learning via Facility Location,http://openaccess.thecvf.com/content_cvpr_2017/html/Song_Deep_Metric_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/CongWeilin/cluster-loss-tensorflow,20,1/2/2019 +Proposal Flow,http://openaccess.thecvf.com/content_cvpr_2016/html/Ham_Proposal_Flow_CVPR_2016_paper.html,CVPR,2016,https://github.com/bsham/ProposalFlow,20,1/2/2019 +Semantic Component Analysis,http://openaccess.thecvf.com/content_iccv_2015/html/Murdock_Semantic_Component_Analysis_ICCV_2015_paper.html,ICCV,2015,https://github.com/aubry74/visual-word2vec,17,1/2/2019 +Learning Large-Scale Automatic Image Colorization,http://openaccess.thecvf.com/content_iccv_2015/html/Deshpande_Learning_Large-Scale_Automatic_ICCV_2015_paper.html,ICCV,2015,https://github.com/aditya12agd5/iccv15_lscolorization,17,1/2/2019 +Predictive-Corrective Networks for Action Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Dave_Predictive-Corrective_Networks_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/achalddave/predictive-corrective,18,1/2/2019 +MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_MDNet_A_Semantically_CVPR_2017_paper.html,CVPR,2017,https://github.com/zizhaozhang/mdnet-cvpr2017,18,1/2/2019 +Scale-Aware Alignment of Hierarchical Image Segmentation,http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Scale-Aware_Alignment_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/yuhuayc/align-hier,20,1/2/2019 +Dimensionality-Driven Learning with Noisy Labels,http://proceedings.mlr.press/v80/ma18d.html,ICML,2018,https://github.com/xingjunm/dimensionality-driven-learning,20,1/2/2019 +Estimating Mutual Information for Discrete-Continuous Mixtures,http://papers.nips.cc/paper/7180-estimating-mutual-information-for-discrete-continuous-mixtures.pdf,NIPS,2017,https://github.com/wgao9/mixed_KSG,16,1/2/2019 +Learning to Push the Limits of Efficient FFT-Based Image Deconvolution,http://openaccess.thecvf.com/content_iccv_2017/html/Kruse_Learning_to_Push_ICCV_2017_paper.html,ICCV,2017,https://github.com/uschmidt83/fourier-deconvolution-network,16,1/2/2019 +Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM,http://papers.nips.cc/paper/6850-accuracy-first-selecting-a-differential-privacy-level-for-accuracy-constrained-erm.pdf,NIPS,2017,https://github.com/steven7woo/Accuracy-First-Differential-Privacy,21,1/2/2019 +Crowd Counting With Deep Negative Correlation Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shi_Crowd_Counting_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shizenglin/Deep-NCL,20,1/2/2019 +Triplet Loss in Siamese Network for Object Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Xingping_Dong_Triplet_Loss_with_ECCV_2018_paper.html,ECCV,2018,https://github.com/shenjianbing/TripletTracking,17,1/2/2019 +Learning Generative ConvNets via Multi-Grid Modeling and Sampling,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gao_Learning_Generative_ConvNets_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ruiqigao/Multigrid_learning,17,1/2/2019 +Explainable Neural Computation via Stack Neural Module Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Ronghang_Hu_Explainable_Neural_Computation_ECCV_2018_paper.html,ECCV,2018,https://github.com/ronghanghu/snmn,29,1/2/2019 +FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Verma_FeaStNet_Feature-Steered_Graph_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nitika-verma/FeaStNet,18,1/2/2019 +Deep Future Gaze: Gaze Anticipation on Egocentric Videos Using Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Deep_Future_Gaze_CVPR_2017_paper.html,CVPR,2017,https://github.com/Mengmi/deepfuturegaze_gan,17,1/2/2019 +3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data,https://arxiv.org/abs/1807.02547,NIPS,2018,https://github.com/mariogeiger/se3cnn,33,1/2/2019 +FALKON: An Optimal Large Scale Kernel Method,http://papers.nips.cc/paper/6978-falkon-an-optimal-large-scale-kernel-method.pdf,NIPS,2017,https://github.com/LCSL/FALKON_paper,17,1/2/2019 +Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Towards_Faster_Training_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jiangtaoxie/fast-MPN-COV,40,1/2/2019 +Simultaneous Feature Learning and Hash Coding With Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2015/html/Lai_Simultaneous_Feature_Learning_2015_CVPR_paper.html,CVPR,2015,https://github.com/HYPJUDY/caffe-dnnh,16,1/2/2019 +POSEidon: Face-From-Depth for Driver Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Borghi_POSEidon_Face-From-Depth_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/gdubrg/POSEidon-Biwi,20,1/2/2019 +Semantic Segmentation With Boundary Neural Fields,http://openaccess.thecvf.com/content_cvpr_2016/html/Bertasius_Semantic_Segmentation_With_CVPR_2016_paper.html,CVPR,2016,https://github.com/gberta/BNF_globalization,19,1/2/2019 +InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations,http://papers.nips.cc/paper/6971-infogail-interpretable-imitation-learning-from-visual-demonstrations.pdf,NIPS,2017,https://github.com/ermongroup/infogail,20,1/2/2019 +Neural system identification for large populations separating “what” and “where”,http://papers.nips.cc/paper/6942-neural-system-identification-for-large-populations-separating-what-and-where.pdf,NIPS,2017,https://github.com/david-klindt/NIPS2017,17,1/2/2019 +Zero-Inflated Exponential Family Embeddings,http://proceedings.mlr.press/v70/liu17a.html,ICML,2017,https://github.com/blei-lab/zero-inflated-embedding,20,1/2/2019 +Visual Question Reasoning on General Dependency Tree,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_Visual_Question_Reasoning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/bezorro/ACMN-Pytorch,17,1/2/2019 +Deep Unsupervised Similarity Learning Using Partially Ordered Sets,http://openaccess.thecvf.com/content_cvpr_2017/html/Bautista_Deep_Unsupervised_Similarity_CVPR_2017_paper.html,CVPR,2017,https://github.com/asanakoy/deep_unsupervised_posets,17,1/2/2019 +Disentangling Factors of Variation with Cycle-Consistent Variational 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Detection",http://openaccess.thecvf.com/content_iccv_2017/html/Zolfaghari_Chained_Multi-Stream_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/mzolfaghari/chained-multistream-networks,19,1/2/2019 +BIER - Boosting Independent Embeddings Robustly,http://openaccess.thecvf.com/content_iccv_2017/html/Opitz_BIER_-_Boosting_ICCV_2017_paper.html,ICCV,2017,https://github.com/mop/bier,18,1/2/2019 +Seeing 3D Chairs: Exemplar Part-based 2D-3D Alignment using a Large Dataset of CAD Models,http://openaccess.thecvf.com/content_cvpr_2014/html/Aubry_Seeing_3D_Chairs_2014_CVPR_paper.html,CVPR,2014,https://github.com/mathieuaubry/seeing3Dchairs,15,1/2/2019 +Deep One-Class Classification,http://proceedings.mlr.press/v80/ruff18a.html,ICML,2018,https://github.com/lukasruff/Deep-SVDD,34,1/2/2019 +Coded Sparse Matrix Multiplication,http://proceedings.mlr.press/v80/wang18e.html,ICML,2018,https://github.com/ksopyla/CudaDotProd,16,1/2/2019 +Product Sparse Coding,http://openaccess.thecvf.com/content_cvpr_2014/html/Ge_Product_Sparse_Coding_2014_CVPR_paper.html,CVPR,2014,https://github.com/ksopyla/CudaDotProd,16,1/2/2019 +Learning Descriptor Networks for 3D Shape Synthesis and Analysis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xie_Learning_Descriptor_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jianwen-xie/3DDescriptorNet,19,1/2/2019 +Automatic Discovery of the Statistical Types of Variables in a Dataset,http://proceedings.mlr.press/v70/valera17a.html,ICML,2017,https://github.com/ivaleraM/DataTypes,15,1/2/2019 +3D Object Reconstruction From Hand-Object Interactions,http://openaccess.thecvf.com/content_iccv_2015/html/Tzionas_3D_Object_Reconstruction_ICCV_2015_paper.html,ICCV,2015,https://github.com/dimtziwnas/InHandScanningICCV15_Reconstruction,15,1/2/2019 +Structure From Motion With Objects,http://openaccess.thecvf.com/content_cvpr_2016/html/Crocco_Structure_From_Motion_CVPR_2016_paper.html,CVPR,2016,https://github.com/danylaksono/Android-SfM-client,17,1/2/2019 +EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth From Light Field Images,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shin_EPINET_A_Fully-Convolutional_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chshin10/epinet,18,1/2/2019 +Deep Learning with Topological Signatures,http://papers.nips.cc/paper/6761-deep-learning-with-topological-signatures.pdf,NIPS,2017,https://github.com/c-hofer/nips2017,17,1/2/2019 +Conditional Image-Text Embedding Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Bryan_Plummer_Conditional_Image-Text_Embedding_ECCV_2018_paper.html,ECCV,2018,https://github.com/BryanPlummer/cite,18,1/2/2019 +Functional Gradient Boosting based on Residual Network Perception,http://proceedings.mlr.press/v80/nitanda18a.html,ICML,2018,https://github.com/anitan0925/ResFGB,16,1/2/2019 +Deep Multitask Architecture for Integrated 2D and 3D Human Sensing,http://openaccess.thecvf.com/content_cvpr_2017/html/Popa_Deep_Multitask_Architecture_CVPR_2017_paper.html,CVPR,2017,https://github.com/alinionutpopa/dmhs,16,1/2/2019 +Action Sets: Weakly Supervised Action Segmentation Without Ordering Constraints,http://openaccess.thecvf.com/content_cvpr_2018/papers/Richard_Action_Sets_Weakly_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/alexanderrichard/action-sets,14,1/2/2019 +Grounding Referring Expressions in Images by Variational Context,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Grounding_Referring_Expressions_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yuleiniu/vc,15,1/2/2019 +Automatic Spatially-Aware Fashion Concept Discovery,http://openaccess.thecvf.com/content_iccv_2017/html/Han_Automatic_Spatially-Aware_Fashion_ICCV_2017_paper.html,ICCV,2017,https://github.com/xthan/fashion-200k,20,1/2/2019 +Single-Image Crowd Counting via Multi-Column Convolutional Neural Network,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Single-Image_Crowd_Counting_CVPR_2016_paper.html,CVPR,2016,https://github.com/uestcchicken/crowd-counting-MCNN,19,1/2/2019 +Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems,http://openaccess.thecvf.com/content_iccv_2017/html/Meinhardt_Learning_Proximal_Operators_ICCV_2017_paper.html,ICCV,2017,https://github.com/tum-vision/learn_prox_ops,15,1/2/2019 +A Spectral Approach to Gradient Estimation for Implicit Distributions,http://proceedings.mlr.press/v80/shi18a.html,ICML,2018,https://github.com/thjashin/spectral-stein-grad,17,1/2/2019 +Toward Characteristic-Preserving Image-based Virtual Try-On Network,http://openaccess.thecvf.com/content_ECCV_2018/html/Bochao_Wang_Toward_Characteristic-Preserving_Image-based_ECCV_2018_paper.html,ECCV,2018,https://github.com/sergeywong/cp-vton,29,1/2/2019 +Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cui_Large_Scale_Fine-Grained_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/richardaecn/cvpr18-inaturalist-transfer,31,1/2/2019 +Weakly- and Semi-Supervised Panoptic Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Anurag_Arnab_Weakly-_and_Semi-Supervised_ECCV_2018_paper.html,ECCV,2018,https://github.com/qizhuli/Weakly-Supervised-Panoptic-Segmentation,46,1/2/2019 +Quantized Convolutional Neural Networks for Mobile Devices,http://openaccess.thecvf.com/content_cvpr_2016/html/Wu_Quantized_Convolutional_Neural_CVPR_2016_paper.html,CVPR,2016,https://github.com/OluwoleOyetoke/Computer_Vision_Using_TensorFlowLite,20,1/2/2019 +Fully-Adaptive Feature Sharing in Multi-Task Networks With Applications in Person Attribute Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Lu_Fully-Adaptive_Feature_Sharing_CVPR_2017_paper.html,CVPR,2017,https://github.com/luyongxi/deep_share,19,1/2/2019 +StyleBank: An Explicit Representation for Neural Image Style Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Chen_StyleBank_An_Explicit_CVPR_2017_paper.html,CVPR,2017,https://github.com/jxcodetw/Stylebank,16,1/2/2019 +ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_ISTA-Net_Interpretable_Optimization-Inspired_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jianzhangcs/ISTA-Net,22,1/2/2019 +Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes,http://openaccess.thecvf.com/content_cvpr_2017/html/Golestaneh_Spatially-Varying_Blur_Detection_CVPR_2017_paper.html,CVPR,2017,https://github.com/isalirezag/HiFST,16,1/2/2019 +Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition,http://openaccess.thecvf.com/content_ECCV_2018/html/Huang_Predicting_Gaze_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/hyf015/egocentric-gaze-prediction,16,1/2/2019 +Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation,http://openaccess.thecvf.com/content_ECCV_2018/html/Helge_Rhodin_Unsupervised_Geometry-Aware_Representation_ECCV_2018_paper.html,ECCV,2018,https://github.com/hrhodin/UnsupervisedGeometryAwareRepresentationLearning,37,1/2/2019 +RoomNet: End-To-End Room Layout Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Lee_RoomNet_End-To-End_Room_ICCV_2017_paper.html,ICCV,2017,https://github.com/GitBoSun/roomnet,17,1/2/2019 +Federated Multi-Task Learning,http://papers.nips.cc/paper/7029-federated-multi-task-learning.pdf,NIPS,2017,https://github.com/gingsmith/fmtl,16,1/2/2019 +Revisiting Deep Intrinsic Image Decompositions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Fan_Revisiting_Deep_Intrinsic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/fqnchina/IntrinsicImage,17,1/2/2019 +Few-Shot Learning Through an Information Retrieval Lens,http://papers.nips.cc/paper/6820-few-shot-learning-through-an-information-retrieval-lens.pdf,NIPS,2017,https://github.com/eleniTriantafillou/few_shot_mAP_public,16,1/2/2019 +Learning Temporal Embeddings for Complex Video Analysis,http://openaccess.thecvf.com/content_iccv_2015/html/Ramanathan_Learning_Temporal_Embeddings_ICCV_2015_paper.html,ICCV,2015,https://github.com/eevignesh/videovector,14,1/2/2019 +Streaming Weak Submodularity: Interpreting Neural Networks on the Fly,http://papers.nips.cc/paper/6993-streaming-weak-submodularity-interpreting-neural-networks-on-the-fly.pdf,NIPS,2017,https://github.com/eelenberg/streak,14,1/2/2019 +Structure-Measure: A New Way to Evaluate Foreground Maps,http://openaccess.thecvf.com/content_iccv_2017/html/Fan_Structure-Measure_A_New_ICCV_2017_paper.html,ICCV,2017,https://github.com/DengPingFan/S-measure,15,1/2/2019 +Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Stacked_Conditional_Generative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/DeepInsight-PCALab/ST-CGAN,20,1/2/2019 +Structured Feature Selection,http://openaccess.thecvf.com/content_iccv_2015/html/Gao_Structured_Feature_Selection_ICCV_2015_paper.html,ICCV,2015,https://github.com/csliangdu/FSASL,17,1/2/2019 +Convolutional Sequence to Sequence Model for Human Dynamics,http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Convolutional_Sequence_to_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chaneyddtt/Convolutional-Sequence-to-Sequence-Model-for-Human-Dynamics,15,1/2/2019 +Bayesian Optimization of Combinatorial Structures,http://proceedings.mlr.press/v80/baptista18a.html,ICML,2018,https://github.com/baptistar/BOCS,18,1/2/2019 +Off-policy evaluation for slate recommendation,http://papers.nips.cc/paper/6954-off-policy-evaluation-for-slate-recommendation.pdf,NIPS,2017,https://github.com/adith387/slates_semisynth_expts,15,1/2/2019 +Interactive Segmentation on RGBD Images via Cue Selection,http://openaccess.thecvf.com/content_cvpr_2016/html/Feng_Interactive_Segmentation_on_CVPR_2016_paper.html,CVPR,2016,https://github.com/ZVsion/rgbd_image_segmentation,14,1/2/2019 +Weakly Supervised Affordance Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Sawatzky_Weakly_Supervised_Affordance_CVPR_2017_paper.html,CVPR,2017,https://github.com/ykztawas/Weakly-Supervised-Affordance-Detection,13,1/2/2019 +3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration,http://openaccess.thecvf.com/content_ECCV_2018/html/Zi_Jian_Yew_3DFeat-Net_Weakly_Supervised_ECCV_2018_paper.html,ECCV,2018,https://github.com/yewzijian/3DFeatNet,27,1/2/2019 +Towards Human-Machine Cooperation: Self-Supervised Sample Mining for Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Towards_Human-Machine_Cooperation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yanxp/SSM,13,1/2/2019 +Captioning Images With Diverse Objects,http://openaccess.thecvf.com/content_cvpr_2017/html/Venugopalan_Captioning_Images_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/vsubhashini/noc,15,1/2/2019 +NAG: Network for Adversary Generation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mopuri_NAG_Network_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/val-iisc/nag,16,1/2/2019 +Variational Dropout Sparsifies Deep Neural Networks,http://proceedings.mlr.press/v70/molchanov17a.html,ICML,2017,https://github.com/soskek/variational_dropout_sparsifies_dnn,15,1/2/2019 +Fast Video Object Segmentation by Reference-Guided Mask Propagation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Oh_Fast_Video_Object_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/seoungwugoh/RGMP,27,1/2/2019 +Oriented Edge Forests for Boundary Detection,http://openaccess.thecvf.com/content_cvpr_2015/html/Hallman_Oriented_Edge_Forests_2015_CVPR_paper.html,CVPR,2015,https://github.com/samhallman/oef,13,1/2/2019 +Learning to See by Moving,http://openaccess.thecvf.com/content_iccv_2015/html/Agrawal_Learning_to_See_ICCV_2015_paper.html,ICCV,2015,https://github.com/pulkitag/learning-to-see-by-moving,14,1/2/2019 +Multi-Scale Weighted Nuclear Norm Image Restoration,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yair_Multi-Scale_Weighted_Nuclear_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/noamyairTC/MSWNNM,14,1/2/2019 +"Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies",http://openaccess.thecvf.com/content_cvpr_2018/papers/Joo_Total_Capture_A_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Myzhencai/Total-Capture,17,1/2/2019 +Recurrent 3D Pose Sequence Machines,http://openaccess.thecvf.com/content_cvpr_2017/html/Lin_Recurrent_3D_Pose_CVPR_2017_paper.html,CVPR,2017,https://github.com/MudeLin/RPSM,15,1/2/2019 +Hierarchical Relational Networks for Group Activity Recognition and Retrieval,http://openaccess.thecvf.com/content_ECCV_2018/html/Mostafa_Ibrahim_Hierarchical_Relational_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/mostafa-saad/hierarchical-relational-network,22,1/2/2019 +Collaborative and Adversarial Network for Unsupervised Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Collaborative_and_Adversarial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mahfuj9346449/iCAN,22,1/2/2019 +Wasserstein Generative Adversarial Networks,http://proceedings.mlr.press/v70/arjovsky17a.html,ICML,2017,https://github.com/luslab/scRNAseq-WGAN-GP,15,1/2/2019 +ReconNet: Non-Iterative Reconstruction of Images From Compressively Sensed Measurements,http://openaccess.thecvf.com/content_cvpr_2016/html/Kulkarni_ReconNet_Non-Iterative_Reconstruction_CVPR_2016_paper.html,CVPR,2016,https://github.com/KuldeepKulkarni/ReconNet,15,1/2/2019 +Adversarial Attack on Graph Structured Data,http://proceedings.mlr.press/v80/dai18b.html,ICML,2018,https://github.com/Hanjun-Dai/graph_adversarial_attack,17,1/2/2019 +To Trust Or Not To Trust A Classifier,http://arxiv.org/abs/1805.11783v1,NIPS,2018,https://github.com/google/TrustScore,23,1/2/2019 +Efficient Neural Audio Synthesis,http://proceedings.mlr.press/v80/kalchbrenner18a.html,ICML,2018,https://github.com/fedden/TensorFlow-Efficient-Neural-Audio-Synthesis,15,1/2/2019 +Visual Coreference Resolution in Visual Dialog using Neural Module Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Satwik_Kottur_Visual_Coreference_Resolution_ECCV_2018_paper.html,ECCV,2018,https://github.com/facebookresearch/corefnmn,25,1/2/2019 +"ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events",http://papers.nips.cc/paper/6932-extremeweather-a-large-scale-climate-dataset-for-semi-supervised-detection-localization-and-understanding-of-extreme-weather-events.pdf,NIPS,2017,https://github.com/eracah/hur-detect,13,1/2/2019 +Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach,http://papers.nips.cc/paper/7023-estimating-accuracy-from-unlabeled-data-a-probabilistic-logic-approach.pdf,NIPS,2017,https://github.com/eaplatanios/makina,16,1/2/2019 +Spherical convolutions and their application in molecular modelling,http://papers.nips.cc/paper/6935-spherical-convolutions-and-their-application-in-molecular-modelling.pdf,NIPS,2017,https://github.com/deepfold/NIPS2017,14,1/2/2019 +Multi-Information Source Optimization,http://papers.nips.cc/paper/7016-multi-information-source-optimization.pdf,NIPS,2017,https://github.com/deepfold/NIPS2017,14,1/2/2019 +Learning 3D Shape Completion From Laser Scan Data With Weak Supervision,http://openaccess.thecvf.com/content_cvpr_2018/papers/Stutz_Learning_3D_Shape_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/davidstutz/cvpr2018-shape-completion,17,1/2/2019 +VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation,http://openaccess.thecvf.com/content_iccv_2017/html/Gan_VQS_Linking_Segmentations_ICCV_2017_paper.html,ICCV,2017,https://github.com/Cold-Winter/vqs,14,1/2/2019 +Neural Face Editing With Intrinsic Image Disentangling,http://openaccess.thecvf.com/content_cvpr_2017/html/Shu_Neural_Face_Editing_CVPR_2017_paper.html,CVPR,2017,https://github.com/zhixinshu/NeuralFaceEditing,14,1/2/2019 +Convexified Convolutional Neural Networks,http://proceedings.mlr.press/v70/zhang17f.html,ICML,2017,https://github.com/zhangyuc/CCNN,12,1/2/2019 +Adversarial Complementary Learning for Weakly Supervised Object Localization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Adversarial_Complementary_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xiaomengyc/ACoL,39,1/2/2019 +Awesome Typography: Statistics-Based Text Effects Transfer,http://openaccess.thecvf.com/content_cvpr_2017/html/Yang_Awesome_Typography_Statistics-Based_CVPR_2017_paper.html,CVPR,2017,https://github.com/williamyang1991/Text-Effects-Transfer,17,1/2/2019 +"Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs",http://papers.nips.cc/paper/6614-hunt-for-the-unique-stable-sparse-and-fast-feature-learning-on-graphs.pdf,NIPS,2017,https://github.com/vermaMachineLearning/FGSD,13,1/2/2019 +Consensus Convolutional Sparse Coding,http://openaccess.thecvf.com/content_iccv_2017/html/Choudhury_Consensus_Convolutional_Sparse_ICCV_2017_paper.html,ICCV,2017,https://github.com/vccimaging/CCSC_code_ICCV2017,13,1/2/2019 +Reflection Removal Using Ghosting Cues,http://openaccess.thecvf.com/content_cvpr_2015/html/Shih_Reflection_Removal_Using_2015_CVPR_paper.html,CVPR,2015,https://github.com/thongnguyendev/single_image,14,1/2/2019 +Streaming Sparse Gaussian Process Approximations,http://papers.nips.cc/paper/6922-streaming-sparse-gaussian-process-approximations.pdf,NIPS,2017,https://github.com/thangbui/streaming_sparse_gp,17,1/2/2019 +Image Transformer,http://proceedings.mlr.press/v80/parmar18a.html,ICML,2018,https://github.com/ssingal05/ImageTransformer,14,1/2/2019 +Semantic Filtering,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Semantic_Filtering_CVPR_2016_paper.html,CVPR,2016,https://github.com/shenshen-hungry/Semantic-CNN,16,1/2/2019 +Objects that Sound,http://openaccess.thecvf.com/content_ECCV_2018/html/Relja_Arandjelovic_Objects_that_Sound_ECCV_2018_paper.html,ECCV,2018,https://github.com/rohitrango/objects-that-sound,20,1/2/2019 +Arbitrary Style Transfer With Deep Feature Reshuffle,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gu_Arbitrary_Style_Transfer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/msracver/Style-Feature-Reshuffle,17,1/2/2019 +StoryGraphs: Visualizing Character Interactions as a Timeline,http://openaccess.thecvf.com/content_cvpr_2014/html/Tapaswi_StoryGraphs_Visualizing_Character_2014_CVPR_paper.html,CVPR,2014,https://github.com/makarandtapaswi/StoryGraphs_CVPR2014,14,1/2/2019 +Deep Supervised Discrete Hashing,http://papers.nips.cc/paper/6842-deep-supervised-discrete-hashing.pdf,NIPS,2017,https://github.com/liqi-casia/DSDH-HashingCode,16,1/2/2019 +Convolutional Neural Networks for No-Reference Image Quality Assessment,http://openaccess.thecvf.com/content_cvpr_2014/html/Kang_Convolutional_Neural_Networks_2014_CVPR_paper.html,CVPR,2014,https://github.com/lidq92/CNNIQA,16,1/2/2019 +Realistic Dynamic Facial Textures From a Single Image Using GANs,http://openaccess.thecvf.com/content_iccv_2017/html/Olszewski_Realistic_Dynamic_Facial_ICCV_2017_paper.html,ICCV,2017,https://github.com/leehomyc/ICCV-2017-Paper,14,1/2/2019 +Unrolled Memory Inner-Products: An Abstract GPU Operator for Efficient Vision-Related Computations,http://openaccess.thecvf.com/content_iccv_2017/html/Lin_Unrolled_Memory_Inner-Products_ICCV_2017_paper.html,ICCV,2017,https://github.com/johnjohnlin/UMI,12,1/2/2019 +CTAP: Complementary Temporal Action Proposal Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Jiyang_Gao_CTAP_Complementary_Temporal_ECCV_2018_paper.html,ECCV,2018,https://github.com/jiyanggao/CTAP,18,1/2/2019 +Deep Cross-Modal Hashing,http://openaccess.thecvf.com/content_cvpr_2017/html/Jiang_Deep_Cross-Modal_Hashing_CVPR_2017_paper.html,CVPR,2017,https://github.com/jiangqy/DCMH-CVPR2017,22,1/2/2019 +Coordinated Multi-Agent Imitation Learning,http://proceedings.mlr.press/v70/le17a.html,ICML,2017,https://github.com/hoangminhle/MultiAgent-ImitationLearning,12,1/2/2019 +Convolutional Neural Network Architecture for Geometric Matching,http://openaccess.thecvf.com/content_cvpr_2017/html/Rocco_Convolutional_Neural_Network_CVPR_2017_paper.html,CVPR,2017,https://github.com/hjweide/convnet-for-geometric-matching,14,1/2/2019 +Parallax-tolerant Image Stitching,http://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Parallax-tolerant_Image_Stitching_2014_CVPR_paper.html,CVPR,2014,https://github.com/gain2217/Robust_Elastic_Warping,20,1/2/2019 +Decouple Learning for Parameterized Image Operators,http://openaccess.thecvf.com/content_ECCV_2018/html/Qingnan_Fan_Learning_to_Learn_ECCV_2018_paper.html,ECCV,2018,https://github.com/fqnchina/DecoupleLearning,12,1/2/2019 +Local Spectral Graph Convolution for Point Set Feature Learning,http://openaccess.thecvf.com/content_ECCV_2018/html/Chu_Wang_Local_Spectral_Graph_ECCV_2018_paper.html,ECCV,2018,https://github.com/fate3439/LocalSpecGCN,21,1/2/2019 +Low-Shot Learning With Large-Scale Diffusion,http://openaccess.thecvf.com/content_cvpr_2018/papers/Douze_Low-Shot_Learning_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/facebookresearch/low-shot-with-diffusion,19,1/2/2019 +Glimpse Clouds: Human Activity Recognition From Unstructured Feature Points,http://openaccess.thecvf.com/content_cvpr_2018/papers/Baradel_Glimpse_Clouds_Human_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/fabienbaradel/glimpse_clouds,18,1/2/2019 +Learning and Using the Arrow of Time,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wei_Learning_and_Using_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/donglaiw/AoT_TCAM,14,1/2/2019 +Nonparametric Part Transfer for Fine-grained Recognition,http://openaccess.thecvf.com/content_cvpr_2014/html/Goring_Nonparametric_Part_Transfer_2014_CVPR_paper.html,CVPR,2014,https://github.com/cvjena/finegrained-cvpr2014,13,1/2/2019 +Multigrid Neural Architectures,http://openaccess.thecvf.com/content_cvpr_2017/html/Ke_Multigrid_Neural_Architectures_CVPR_2017_paper.html,CVPR,2017,https://github.com/buttomnutstoast/Multigrid-Neural-Architectures,12,1/2/2019 +Attributes2Classname: A Discriminative Model for Attribute-Based Unsupervised Zero-Shot Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Demirel_Attributes2Classname_A_Discriminative_ICCV_2017_paper.html,ICCV,2017,https://github.com/berkandemirel/attributes2classname,14,1/2/2019 +Gesture Recognition: Focus on the Hands,http://openaccess.thecvf.com/content_cvpr_2018/papers/Narayana_Gesture_Recognition_Focus_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/beckabec/HandDetection,12,1/2/2019 +IM2CAD,http://openaccess.thecvf.com/content_cvpr_2017/html/Izadinia_IM2CAD_CVPR_2017_paper.html,CVPR,2017,https://github.com/yyong119/IM2CAD,11,1/2/2019 +Deep Spatial-Semantic Attention for Fine-Grained Sketch-Based Image Retrieval,http://openaccess.thecvf.com/content_iccv_2017/html/Song_Deep_Spatial-Semantic_Attention_ICCV_2017_paper.html,ICCV,2017,https://github.com/yuchuochuo1023/Deep_SBIR_tf,16,1/2/2019 +Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace,http://proceedings.mlr.press/v80/lee18a.html,ICML,2018,https://github.com/yoonholee/MT-net,13,1/2/2019 +Min-Entropy Latent Model for Weakly Supervised Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wan_Min-Entropy_Latent_Model_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Winfrand/MELM,13,1/2/2019 +Joint Learning of Object and Action Detectors,http://openaccess.thecvf.com/content_iccv_2017/html/Kalogeiton_Joint_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/vkalogeiton/joint-object-action-learning,13,1/2/2019 +Generalized Deep Image to Image Regression,http://openaccess.thecvf.com/content_cvpr_2017/html/Santhanam_Generalized_Deep_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/venkai/RBDN,11,1/2/2019 +HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cao_HashGAN_Deep_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/thuml/HashGAN,22,1/2/2019 +Future Person Localization in First-Person Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yagi_Future_Person_Localization_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/takumayagi/fpl,12,1/2/2019 +Sliced Wasserstein Distance for Learning Gaussian Mixture Models,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kolouri_Sliced_Wasserstein_Distance_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/skolouri/swgmm,17,1/2/2019 +Light Field Blind Motion Deblurring,http://openaccess.thecvf.com/content_cvpr_2017/html/Srinivasan_Light_Field_Blind_CVPR_2017_paper.html,CVPR,2017,https://github.com/pratulsrinivasan/Light_Field_Blind_Motion_Deblurring,13,1/2/2019 +Hierarchical Multi-Label Classification Networks,http://proceedings.mlr.press/v80/wehrmann18a.html,ICML,2018,https://github.com/omoju/receiptdID,11,1/2/2019 +Neural Sign Language Translation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Camgoz_Neural_Sign_Language_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/neccam/nslt,15,1/2/2019 +Scalable Multitask Representation Learning for Scene Classification,http://openaccess.thecvf.com/content_cvpr_2014/html/Lapin_Scalable_Multitask_Representation_2014_CVPR_paper.html,CVPR,2014,https://github.com/mlapin/cvpr14mtl,11,1/2/2019 +Asynchronous Stochastic Gradient Descent with Delay Compensation,http://proceedings.mlr.press/v70/zheng17b.html,ICML,2017,https://github.com/Microsoft/Delayed-Compensation-Asynchronous-Stochastic-Gradient-Descent-for-Multiverso,13,1/2/2019 +Learning Rich Features for Image Manipulation Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Learning_Rich_Features_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/LarryJiang134/Image_manipulation_detection,27,1/2/2019 +Hierarchical Novelty Detection for Visual Object Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_Hierarchical_Novelty_Detection_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kibok90/cvpr2018-hnd,17,1/2/2019 +Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification,http://papers.nips.cc/paper/7125-maximizing-subset-accuracy-with-recurrent-neural-networks-in-multi-label-classification.pdf,NIPS,2017,https://github.com/JinseokNam/mlc2seq,12,1/2/2019 +Differential Angular Imaging for Material Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Xue_Differential_Angular_Imaging_CVPR_2017_paper.html,CVPR,2017,https://github.com/jiaxue1993/DAIN,12,1/2/2019 +Where to Buy It: Matching Street Clothing Photos in Online Shops,http://openaccess.thecvf.com/content_iccv_2015/html/Kiapour_Where_to_Buy_ICCV_2015_paper.html,ICCV,2015,https://github.com/jfuentescpp/where_to_buy_it,14,1/2/2019 +On Fairness and Calibration,http://papers.nips.cc/paper/7151-on-fairness-and-calibration.pdf,NIPS,2017,https://github.com/gpleiss/equalized_odds_and_calibration,11,1/2/2019 +Learning to Forecast and Refine Residual Motion for Image-to-Video Generation,http://openaccess.thecvf.com/content_ECCV_2018/html/Long_Zhao_Learning_to_Forecast_ECCV_2018_paper.html,ECCV,2018,https://github.com/garyzhao/FRGAN,14,1/2/2019 +Convolutional Image Captioning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Aneja_Convolutional_Image_Captioning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/eladhoffer/captionGeneration.torch,11,1/2/2019 +Deep Expander Networks: Efficient Deep Networks from Graph Theory,http://openaccess.thecvf.com/content_ECCV_2018/html/Ameya_Prabhu_Deep_Expander_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/DrImpossible/Deep-Expander-Networks,19,1/2/2019 +From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur,http://openaccess.thecvf.com/content_cvpr_2017/html/Gong_From_Motion_Blur_CVPR_2017_paper.html,CVPR,2017,https://github.com/donggong1/motion-flow-syn,20,1/2/2019 +Face Aging With Identity-Preserved Conditional Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Face_Aging_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/dawei6875797/Face-Aging-with-Identity-Preserved-Conditional-Generative-Adversarial-Networks,23,1/2/2019 +Similarity Learning With Spatial Constraints for Person Re-Identification,http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Similarity_Learning_With_CVPR_2016_paper.html,CVPR,2016,https://github.com/dapengchen123/SCSP,11,1/2/2019 +Joint Optimization Framework for Learning With Noisy Labels,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tanaka_Joint_Optimization_Framework_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/DaikiTanaka-UT/JointOptimization,12,1/2/2019 +Predictive State Recurrent Neural Networks,http://papers.nips.cc/paper/7186-predictive-state-recurrent-neural-networks.pdf,NIPS,2017,https://github.com/cmdowney/psrnn,13,1/2/2019 +A Large-Scale Car Dataset for Fine-Grained Categorization and Verification,http://openaccess.thecvf.com/content_cvpr_2015/html/Yang_A_Large-Scale_Car_2015_CVPR_paper.html,CVPR,2015,https://github.com/bogger/caffe-multigpu,11,1/2/2019 +Dynamic Multimodal Instance Segmentation Guided by Natural Language Queries,http://openaccess.thecvf.com/content_ECCV_2018/html/Edgar_Margffoy-Tuay_Dynamic_Multimodal_Instance_ECCV_2018_paper.html,ECCV,2018,https://github.com/BCV-Uniandes/query-objseg,25,1/2/2019 +Learning Transferable Architectures for Scalable Image Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zoph_Learning_Transferable_Architectures_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/aussetg/nasnet.pytorch,12,1/2/2019 +Learning Conditioned Graph Structures for Interpretable Visual Question Answering,,NIPS,2018,https://github.com/aimbrain/vqa-project,57,1/2/2019 +Learning Diverse Image Colorization,http://openaccess.thecvf.com/content_cvpr_2017/html/Deshpande_Learning_Diverse_Image_CVPR_2017_paper.html,CVPR,2017,https://github.com/aditya12agd5/divcolor,15,1/2/2019 +Open Set Domain Adaptation by Backpropagation,http://openaccess.thecvf.com/content_ECCV_2018/html/Kuniaki_Saito_Adversarial_Open_Set_ECCV_2018_paper.html,ECCV,2018,https://github.com/YU1ut/openset-DA,15,1/2/2019 +Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks,https://arxiv.org/abs/1802.04034,NIPS,2018,https://github.com/ytsmiling/lmt,16,1/2/2019 +Mix and Match Networks: Encoder-Decoder Alignment for Zero-Pair Image Translation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Mix_and_Match_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yaxingwang/Mix-and-match-networks,12,1/2/2019 +Learning by Asking Questions,http://openaccess.thecvf.com/content_cvpr_2018/papers/Misra_Learning_by_Asking_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/yanghoonkim/question_generation,13,1/2/2019 +DESIRE: Distant Future Prediction in Dynamic Scenes With Interacting Agents,http://openaccess.thecvf.com/content_cvpr_2017/html/Lee_DESIRE_Distant_Future_CVPR_2017_paper.html,CVPR,2017,https://github.com/yadrimz/DESIRE,11,1/2/2019 +Densely Connected Attention Propagation for Reading Comprehension,https://nips.cc/Conferences/2018/Schedule?showEvent=11481,NIPS,2018,https://github.com/vanzytay/NIPS2018_DECAPROP,30,1/2/2019 +VegFru: A Domain-Specific Dataset for Fine-Grained Visual Categorization,http://openaccess.thecvf.com/content_iccv_2017/html/Hou_VegFru_A_Domain-Specific_ICCV_2017_paper.html,ICCV,2017,https://github.com/ustc-vim/vegfru,12,1/2/2019 +Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction,http://proceedings.mlr.press/v80/qi18a.html,ICML,2018,https://github.com/SiyuanQi/generalized-earley-parser,12,1/2/2019 +Multimodal Explanations: Justifying Decisions and Pointing to the Evidence,http://openaccess.thecvf.com/content_cvpr_2018/papers/Park_Multimodal_Explanations_Justifying_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Seth-Park/MultimodalExplanations,11,1/2/2019 +Pose Proposal Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Sekii_Pose_Proposal_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/salihkaragoz/MultiPerson-pose-estimation,15,1/2/2019 +Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory,http://proceedings.mlr.press/v80/amit18a.html,ICML,2018,https://github.com/ron-amit/meta-learning-adjusting-priors,11,1/2/2019 +f-GANs in an Information Geometric Nutshell,http://papers.nips.cc/paper/6649-f-gans-in-an-information-geometric-nutshell.pdf,NIPS,2017,https://github.com/qulizhen/fgan_info_geometric,10,1/2/2019 +Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin,http://papers.nips.cc/paper/7255-attend-and-predict-understanding-gene-regulation-by-selective-attention-on-chromatin.pdf,NIPS,2017,https://github.com/QData/AttentiveChrome,12,1/2/2019 +Adversarial Time-to-Event Modeling,http://proceedings.mlr.press/v80/chapfuwa18a.html,ICML,2018,https://github.com/paidamoyo/adversarial_time_to_event,12,1/2/2019 +Anonymous Walk Embeddings,http://proceedings.mlr.press/v80/ivanov18a.html,ICML,2018,https://github.com/nd7141/AWE,22,1/2/2019 +Learning Type-Aware Embeddings for Fashion Compatibility,http://openaccess.thecvf.com/content_ECCV_2018/html/Mariya_Vasileva_Learning_Type-Aware_Embeddings_ECCV_2018_paper.html,ECCV,2018,https://github.com/mvasil/fashion-compatibility,17,1/2/2019 +Learning to Understand Image Blur,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Learning_to_Understand_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Lotuslisa/Understand_Image_Blur,14,1/2/2019 +Scalable Log Determinants for Gaussian Process Kernel Learning,http://papers.nips.cc/paper/7212-scalable-log-determinants-for-gaussian-process-kernel-learning.pdf,NIPS,2017,https://github.com/kd383/GPML_SLD,9,1/2/2019 +Personalizing Human Video Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2016/html/Charles_Personalizing_Human_Video_CVPR_2016_paper.html,CVPR,2016,https://github.com/jjcharles/personalized_pose,10,1/2/2019 +High-Order Attention Models for Visual Question Answering,http://papers.nips.cc/paper/6957-high-order-attention-models-for-visual-question-answering.pdf,NIPS,2017,https://github.com/idansc/HighOrderAtten,11,1/2/2019 +Learned Contextual Feature Reweighting for Image Geo-Localization,http://openaccess.thecvf.com/content_cvpr_2017/html/Kim_Learned_Contextual_Feature_CVPR_2017_paper.html,CVPR,2017,https://github.com/hyojinie/crn,14,1/2/2019 +AON: Towards Arbitrarily-Oriented Text Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Cheng_AON_Towards_Arbitrarily-Oriented_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/huizhang0110/AON,26,1/2/2019 +Joint Pose and Expression Modeling for Facial Expression Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Joint_Pose_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/FFZhang1231/Facial-expression-recognition,15,1/2/2019 +Accelerating Natural Gradient with Higher-Order Invariance,http://proceedings.mlr.press/v80/song18a.html,ICML,2018,https://github.com/ermongroup/higher_order_invariance,11,1/2/2019 +Fully-Convolutional Point Networks for Large-Scale Point Clouds,http://openaccess.thecvf.com/content_ECCV_2018/html/Dario_Rethage_Fully-Convolutional_Point_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/drethage/fully-convolutional-point-network,20,1/2/2019 +Learning Cross-Modal Deep Representations for Robust Pedestrian Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Xu_Learning_Cross-Modal_Deep_CVPR_2017_paper.html,CVPR,2017,https://github.com/danxuhk/CMT-CNN,10,1/2/2019 +Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective,http://openaccess.thecvf.com/content_iccv_2017/html/Oh_Adversarial_Image_Perturbation_ICCV_2017_paper.html,ICCV,2017,https://github.com/coallaoh/AIP,11,1/2/2019 +Finding Influential Training Samples for Gradient Boosted Decision Trees,http://proceedings.mlr.press/v80/sharchilev18a.html,ICML,2018,https://github.com/bsharchilev/influence_boosting,13,1/2/2019 +Non-Local Deep Features for Salient Object Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Luo_Non-Local_Deep_Features_CVPR_2017_paper.html,CVPR,2017,https://github.com/AceCoooool/NLFD-pytorch,15,1/2/2019 +Max-value Entropy Search for Efficient Bayesian Optimization,http://proceedings.mlr.press/v70/wang17e.html,ICML,2017,https://github.com/zi-w/Max-value-Entropy-Search,11,1/2/2019 +CVAE-GAN: Fine-Grained Image Generation Through Asymmetric Training,http://openaccess.thecvf.com/content_iccv_2017/html/Bao_CVAE-GAN_Fine-Grained_Image_ICCV_2017_paper.html,ICCV,2017,https://github.com/yanzhicong/VAE-GAN,14,1/2/2019 +Removing Rain From Single Images via a Deep Detail Network,http://openaccess.thecvf.com/content_cvpr_2017/html/Fu_Removing_Rain_From_CVPR_2017_paper.html,CVPR,2017,https://github.com/XMU-smartdsp/Removing_Rain,12,1/2/2019 +Learning Superpixels With Segmentation-Aware Affinity Loss,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tu_Learning_Superpixels_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wctu/SEAL,20,1/2/2019 +Surface Normals in the Wild,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Surface_Normals_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/umich-vl/surface_normals,15,1/2/2019 +Appearance-Based Gaze Estimation in the Wild,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Appearance-Based_Gaze_Estimation_2015_CVPR_paper.html,CVPR,2015,https://github.com/trakaros/MPIIGaze,10,1/2/2019 +Fisher GAN,http://papers.nips.cc/paper/6845-fisher-gan.pdf,NIPS,2017,https://github.com/tomsercu/FisherGAN,11,1/2/2019 +Practical Data-Dependent Metric Compression with Provable Guarantees,http://papers.nips.cc/paper/6855-practical-data-dependent-metric-compression-with-provable-guarantees.pdf,NIPS,2017,https://github.com/talwagner/quadsketch,9,1/2/2019 +High Quality Structure From Small Motion for Rolling Shutter Cameras,http://openaccess.thecvf.com/content_iccv_2015/html/Im_High_Quality_Structure_ICCV_2015_paper.html,ICCV,2015,https://github.com/sunghoonim/SfSM,9,1/2/2019 +Deep Diffeomorphic Transformer Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Detlefsen_Deep_Diffeomorphic_Transformer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/SkafteNicki/ddtn,13,1/2/2019 +Predicting Human Activities Using Stochastic Grammar,http://openaccess.thecvf.com/content_iccv_2017/html/Qi_Predicting_Human_Activities_ICCV_2017_paper.html,ICCV,2017,https://github.com/SiyuanQi/grammar-activity-prediction,11,1/2/2019 +Synthesizing Robust Adversarial Examples,http://proceedings.mlr.press/v80/athalye18b.html,ICML,2018,https://github.com/prabhant/synthesizing-robust-adversarial-examples,13,1/2/2019 +Learning Motion Patterns in Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Tokmakov_Learning_Motion_Patterns_CVPR_2017_paper.html,CVPR,2017,https://github.com/pirahansiah/opencv,9,1/2/2019 +AMNet: Memorability Estimation With Attention,http://openaccess.thecvf.com/content_cvpr_2018/papers/Fajtl_AMNet_Memorability_Estimation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ok1zjf/AMNet,12,1/2/2019 +Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models,https://arxiv.org/abs/1808.04768,NIPS,2018,https://github.com/neitzal/adaptive-skip-intervals,12,1/2/2019 +Learning a Discriminative Feature Network for Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Yu_Learning_a_Discriminative_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/lxtGH/dfn_seg,26,1/2/2019 +Gradient descent GAN optimization is locally stable,http://papers.nips.cc/paper/7142-gradient-descent-gan-optimization-is-locally-stable.pdf,NIPS,2017,https://github.com/locuslab/gradient_regularized_gan,12,1/2/2019 +Hashing as Tie-Aware Learning to Rank,http://openaccess.thecvf.com/content_cvpr_2018/papers/He_Hashing_as_Tie-Aware_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kunhe/TALR,15,1/2/2019 +Visually Indicated Sounds,http://openaccess.thecvf.com/content_cvpr_2016/html/Owens_Visually_Indicated_Sounds_CVPR_2016_paper.html,CVPR,2016,https://github.com/kanchen-usc/VIG,9,1/2/2019 +Attentional Correlation Filter Network for Adaptive Visual Tracking,http://openaccess.thecvf.com/content_cvpr_2017/html/Choi_Attentional_Correlation_Filter_CVPR_2017_paper.html,CVPR,2017,https://github.com/jongwon20000/ACFN,10,1/2/2019 +Automatic Content-Aware Color and Tone Stylization,http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Automatic_Content-Aware_Color_CVPR_2016_paper.html,CVPR,2016,https://github.com/jinyu121/ACACTS,12,1/2/2019 +Attention in Convolutional LSTM for Gesture Recognition,https://nips.cc/Conferences/2018/Schedule?showEvent=11207,NIPS,2018,https://github.com/GuangmingZhu/AttentionConvLSTM,32,1/2/2019 +Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization,http://papers.nips.cc/paper/6611-breaking-the-nonsmooth-barrier-a-scalable-parallel-method-for-composite-optimization.pdf,NIPS,2017,https://github.com/fabianp/ProxASAGA,9,1/2/2019 +Rethinking the Form of Latent States in Image Captioning,http://openaccess.thecvf.com/content_ECCV_2018/html/Bo_Dai_Rethinking_the_Form_ECCV_2018_paper.html,ECCV,2018,https://github.com/doubledaibo/2dcaption_eccv2018,15,1/2/2019 +Higher-Order Integration of Hierarchical Convolutional Activations for Fine-Grained Visual Categorization,http://openaccess.thecvf.com/content_iccv_2017/html/Cai_Higher-Order_Integration_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/cssjcai/hihca,11,1/2/2019 +Confident Multiple Choice Learning,http://proceedings.mlr.press/v70/lee17b.html,ICML,2017,https://github.com/chhwang/cmcl,10,1/2/2019 +Do Deep Neural Networks Suffer from Crowding?,http://papers.nips.cc/paper/7146-do-deep-neural-networks-suffer-from-crowding.pdf,NIPS,2017,https://github.com/CBMM/eccentricity,9,1/2/2019 +Robust Image Filtering Using Joint Static and Dynamic Guidance,http://openaccess.thecvf.com/content_cvpr_2015/html/Ham_Robust_Image_Filtering_2015_CVPR_paper.html,CVPR,2015,https://github.com/bsham/SDFilter,10,1/2/2019 +Learning Dynamics of Linear Denoising Autoencoders,http://proceedings.mlr.press/v80/pretorius18a.html,ICML,2018,https://github.com/arnupretorius/lindaedynamics_icml2018,9,1/2/2019 +Variational Autoencoders for Deforming 3D Mesh Models,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tan_Variational_Autoencoders_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/aldehydecho/Mesh-VAE,13,1/2/2019 +Region Ranking SVM for Image Classification,http://openaccess.thecvf.com/content_cvpr_2016/html/Wei_Region_Ranking_SVM_CVPR_2016_paper.html,CVPR,2016,https://github.com/zijunwei/Region-Ranking-SVM,8,1/2/2019 +Disentangled Representation Learning GAN for Pose-Invariant Face Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Tran_Disentangled_Representation_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/zhangjunh/DR-GAN-by-pytorch,21,1/2/2019 +A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting,http://openaccess.thecvf.com/content_cvpr_2017/html/Queau_A_Non-Convex_Variational_CVPR_2017_paper.html,CVPR,2017,https://github.com/yqueau/robust_ps,9,1/2/2019 +Online multiclass boosting,http://papers.nips.cc/paper/6693-online-multiclass-boosting.pdf,NIPS,2017,https://github.com/yhjung88/OnlineBoostingWithVFDT,8,1/2/2019 +A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation,https://arxiv.org/abs/1809.01361,NIPS,2018,https://github.com/XenderLiu/UFDN,51,1/2/2019 +Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Anderson_Bottom-Up_and_Top-Down_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Wentong-DST/up-down-captioner,13,1/2/2019 +Salient Object Detection Driven by Fixation Prediction,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Salient_Object_Detection_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/wenguanwang/ASNet,9,1/2/2019 +Cost efficient gradient boosting,http://papers.nips.cc/paper/6753-cost-efficient-gradient-boosting.pdf,NIPS,2017,https://github.com/svenpeter42/LightGBM-CEGB,8,1/2/2019 +Excitation Backprop for RNNs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Bargal_Excitation_Backprop_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sbargal/Caffe-ExcitationBP-RNNs,9,1/2/2019 +DeepNav: Learning to Navigate Large Cities,http://openaccess.thecvf.com/content_cvpr_2017/html/Brahmbhatt_DeepNav_Learning_to_CVPR_2017_paper.html,CVPR,2017,https://github.com/samarth-robo/deepnav_cvpr17,8,1/2/2019 +Fast Information-theoretic Bayesian Optimisation,http://proceedings.mlr.press/v80/ru18a.html,ICML,2018,https://github.com/rubinxin/FITBO,8,1/2/2019 +DeepPermNet: Visual Permutation Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Santa_Cruz_DeepPermNet_Visual_Permutation_CVPR_2017_paper.html,CVPR,2017,https://github.com/rfsantacruz/deep-perm-net,10,1/2/2019 +Curriculum Dropout,http://openaccess.thecvf.com/content_iccv_2017/html/Morerio_Curriculum_Dropout_ICCV_2017_paper.html,ICCV,2017,https://github.com/pmorerio/curriculum-dropout,9,1/2/2019 +Input Switched Affine Networks: An RNN Architecture Designed for Interpretability,http://proceedings.mlr.press/v70/foerster17a.html,ICML,2017,https://github.com/philipperemy/tensorflow-isan-rnn,8,1/2/2019 +Deep Variational Reinforcement Learning for POMDPs,http://proceedings.mlr.press/v80/igl18a.html,ICML,2018,https://github.com/oxwhirl/Deep-Variational-Reinforcement-Learning,8,9/16/2018 +Gaze Embeddings for Zero-Shot Image Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Karessli_Gaze_Embeddings_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/Noura-kr/CVPR17,8,1/2/2019 +Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation,http://papers.nips.cc/paper/6821-formal-guarantees-on-the-robustness-of-a-classifier-against-adversarial-manipulation.pdf,NIPS,2017,https://github.com/max-andr/cross-lipschitz,11,1/2/2019 +Boosting Domain Adaptation by Discovering Latent Domains,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mancini_Boosting_Domain_Adaptation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/mancinimassimiliano/latent_domains_DA,11,1/2/2019 +Affinity Clustering: Hierarchical Clustering at Scale,http://papers.nips.cc/paper/7262-affinity-clustering-hierarchical-clustering-at-scale.pdf,NIPS,2017,https://github.com/MahsaDerakhshan/AffinityClustering,8,1/2/2019 +Revisiting IM2GPS in the Deep Learning Era,http://openaccess.thecvf.com/content_iccv_2017/html/Vo_Revisiting_IM2GPS_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/lugiavn/revisiting-im2gps,10,1/2/2019 +Partial Person Re-Identification,http://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Partial_Person_Re-Identification_ICCV_2015_paper.html,ICCV,2015,https://github.com/lingxiao-he/Deep-Spatial-Feature-Reconstruction-for-Partial-Person-Re-identification,9,1/2/2019 +Benchmarking Denoising Algorithms With Real Photographs,http://openaccess.thecvf.com/content_cvpr_2017/html/Plotz_Benchmarking_Denoising_Algorithms_CVPR_2017_paper.html,CVPR,2017,https://github.com/lbasek/image-denoising-benchmark,14,1/2/2019 +Cross-View Image Synthesis Using Conditional GANs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Regmi_Cross-View_Image_Synthesis_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kregmi/cross-view-image-synthesis,12,1/2/2019 +Boosting Object Proposals: From Pascal to 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Network,http://openaccess.thecvf.com/content_cvpr_2016/html/Molchanov_Online_Detection_and_CVPR_2016_paper.html,CVPR,2016,https://github.com/breadbread1984/R3DCNN,16,1/2/2019 +Pairwise Matching Through Max-Weight Bipartite Belief Propagation,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Pairwise_Matching_Through_CVPR_2016_paper.html,CVPR,2016,https://github.com/zzhang1987/HungarianBP,8,1/2/2019 +Detecting and Correcting for Label Shift with Black Box Predictors,http://proceedings.mlr.press/v80/lipton18a.html,ICML,2018,https://github.com/zackchase/label-shift,7,1/2/2019 +Attention-Aware Face Hallucination via Deep Reinforcement Learning,http://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Attention-Aware_Face_Hallucination_CVPR_2017_paper.html,CVPR,2017,https://github.com/ykshi/facehallucination,8,1/2/2019 +Conditional Prior Networks for Optical Flow,http://openaccess.thecvf.com/content_ECCV_2018/html/Yanchao_Yang_Conditional_Prior_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/YanchaoYang/Conditional-Prior-Networks,7,1/2/2019 +Fine-Grained Visual Categorization using Meta-Learning Optimization with Sample Selection of Auxiliary Data,http://openaccess.thecvf.com/content_ECCV_2018/html/Yabin_Zhang_Fine-Grained_Visual_Categorization_ECCV_2018_paper.html,ECCV,2018,https://github.com/YabinZhang1994/MetaFGNet,13,1/2/2019 +Diverse Image Annotation,http://openaccess.thecvf.com/content_cvpr_2017/html/Wu_Diverse_Image_Annotation_CVPR_2017_paper.html,CVPR,2017,https://github.com/wubaoyuan/DIA,6,1/2/2019 +Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images,http://openaccess.thecvf.com/content_iccv_2017/html/Orekondy_Towards_a_Visual_ICCV_2017_paper.html,ICCV,2017,https://github.com/tribhuvanesh/vpa,8,1/2/2019 +Live Repetition Counting,http://openaccess.thecvf.com/content_iccv_2015/html/Levy_Live_Repetition_Counting_ICCV_2015_paper.html,ICCV,2015,https://github.com/tomrunia/DeepRepICCV2015,8,1/2/2019 +Reflectance Adaptive Filtering Improves Intrinsic Image Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Nestmeyer_Reflectance_Adaptive_Filtering_CVPR_2017_paper.html,CVPR,2017,https://github.com/tnestmeyer/reflectance-filtering,8,1/2/2019 +Weakly Supervised Learning of Deep Metrics for Stereo Reconstruction,http://openaccess.thecvf.com/content_iccv_2017/html/Tulyakov_Weakly_Supervised_Learning_ICCV_2017_paper.html,ICCV,2017,https://github.com/tlkvstepan/mc-cnn-ws,7,1/2/2019 +Decoupled Parallel Backpropagation with Convergence Guarantee,http://proceedings.mlr.press/v80/huo18a.html,ICML,2018,https://github.com/slowbull/DDG,9,1/2/2019 +Generative Adversarial Learning Towards Fast Weakly Supervised Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Generative_Adversarial_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shenyunhang/GAL-fWSD,7,1/2/2019 +A Memory Network Approach for Story-Based Temporal Summarization of 360° Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lee_A_Memory_Network_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/sangho-vision/PFMN,6,1/2/2019 +oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis,http://proceedings.mlr.press/v80/ainsworth18a.html,ICML,2018,https://github.com/samuela/oi-vae,9,1/2/2019 +Model-Powered Conditional Independence Test,http://papers.nips.cc/paper/6888-model-powered-conditional-independence-test.pdf,NIPS,2017,https://github.com/rajatsen91/CCIT,8,1/2/2019 +Generative Probabilistic Novelty Detection with Adversarial Autoencoders,http://arxiv.org/abs/1807.02588v1,NIPS,2018,https://github.com/podgorskiy/GPND,16,1/2/2019 +Clipped Action Policy Gradient,http://proceedings.mlr.press/v80/fujita18a.html,ICML,2018,https://github.com/pfnet-research/capg,12,1/2/2019 +Learning to Explain: An Information-Theoretic Perspective on Model Interpretation,http://proceedings.mlr.press/v80/chen18j.html,ICML,2018,https://github.com/nickvosk/acl2015-dataset-learning-to-explain-entity-relationships,7,1/2/2019 +Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled,http://openaccess.thecvf.com/content_cvpr_2016/html/Koller_Deep_Hand_How_CVPR_2016_paper.html,CVPR,2016,https://github.com/neccam/TF-DeepHand,8,1/2/2019 +A Two-Step Disentanglement Method,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hadad_A_Two-Step_Disentanglement_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/naamahadad/A-Two-Step-Disentanglement-Method,7,1/2/2019 +Lost Relatives of the Gumbel Trick,http://proceedings.mlr.press/v70/balog17a.html,ICML,2017,https://github.com/matejbalog/gumbel-relatives,7,1/2/2019 +Where to Look: Focus Regions for Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2016/html/Shih_Where_to_Look_CVPR_2016_paper.html,CVPR,2016,https://github.com/kevjshih/wtl_vqa,7,1/2/2019 +Detecting Migrating Birds at Night,http://openaccess.thecvf.com/content_cvpr_2016/html/Huang_Detecting_Migrating_Birds_CVPR_2016_paper.html,CVPR,2016,https://github.com/jbhuang0604/BirdDetection,7,1/2/2019 +Cross-Domain Self-Supervised Multi-Task Feature Learning Using Synthetic Imagery,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ren_Cross-Domain_Self-Supervised_Multi-Task_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jason718/game-feature-learning,19,1/2/2019 +Supervised Discrete Hashing,http://openaccess.thecvf.com/content_cvpr_2015/html/Shen_Supervised_Discrete_Hashing_2015_CVPR_paper.html,CVPR,2015,https://github.com/goukoutaki/FSDH,7,1/2/2019 +PacGAN: The power of two samples in generative adversarial networks,http://arxiv.org/abs/1712.04086v2,NIPS,2018,https://github.com/fjxmlzn/PacGAN,10,1/2/2019 +Optimized Pre-Processing for Discrimination Prevention,http://papers.nips.cc/paper/6988-optimized-pre-processing-for-discrimination-prevention.pdf,NIPS,2017,https://github.com/fair-preprocessing/nips2017,9,1/2/2019 +Five-Point Fundamental Matrix Estimation for Uncalibrated Cameras,http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Five-Point_Fundamental_Matrix_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/danini/five-point-fundamental,8,1/2/2019 +Semantic Video Segmentation by Gated Recurrent Flow Propagation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Nilsson_Semantic_Video_Segmentation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/D-Nilsson/GRFP,9,1/2/2019 +RPAN: An End-To-End Recurrent Pose-Attention Network for Action Recognition in Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Du_RPAN_An_End-To-End_ICCV_2017_paper.html,ICCV,2017,https://github.com/agethen/RPAN,17,1/2/2019 +Geometry-Aware Scene Text Detection With Instance Transformation Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Geometry-Aware_Scene_Text_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zlmzju/itn,22,1/2/2019 +Investigating Haze-relevant Features in A Learning Framework for Image Dehazing,http://openaccess.thecvf.com/content_cvpr_2014/html/Tang_Investigating_Haze-relevant_Features_2014_CVPR_paper.html,CVPR,2014,https://github.com/zlinker/haze_2014,7,1/2/2019 +Progressive Attention Guided Recurrent Network for Salient Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Progressive_Attention_Guided_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhangxiaoning666/PAGR,7,1/2/2019 +Recurrent Attentional Networks for Saliency Detection,http://openaccess.thecvf.com/content_cvpr_2016/html/Kuen_Recurrent_Attentional_Networks_CVPR_2016_paper.html,CVPR,2016,https://github.com/zhangxiaoning666/PAGR,7,1/2/2019 +Practical Hash Functions for Similarity Estimation and Dimensionality Reduction,http://papers.nips.cc/paper/7239-practical-hash-functions-for-similarity-estimation-and-dimensionality-reduction.pdf,NIPS,2017,https://github.com/zera/Nips_MT,6,1/2/2019 +Low-Shot Learning With Imprinted Weights,http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Low-Shot_Learning_With_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/YU1ut/imprinted-weights,19,1/2/2019 +Reconstructing PASCAL VOC,http://openaccess.thecvf.com/content_cvpr_2014/html/Vicente_Reconstructing_PASCAL_VOC_2014_CVPR_paper.html,CVPR,2014,https://github.com/yihui-he/reconstructing-pascal-voc,6,1/2/2019 +SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters,http://openaccess.thecvf.com/content_ECCV_2018/html/Yifan_Xu_SpiderCNN_Deep_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/xyf513/SpiderCNN,15,1/2/2019 +Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Kuen_Stochastic_Downsampling_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xternalz/SDPoint,7,1/2/2019 +Scalable Planning with Tensorflow for Hybrid Nonlinear Domains,http://papers.nips.cc/paper/7207-scalable-planning-with-tensorflow-for-hybrid-nonlinear-domains.pdf,NIPS,2017,https://github.com/wuga214/TOOLBOX-Learning-and-Planning-through-Backpropagation,6,1/2/2019 +AttnGAN: Fine-Grained Text to Image Generation With Attentional Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_AttnGAN_Fine-Grained_Text_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Wentong-DST/attn-gan,7,1/2/2019 +Deep Crisp Boundaries,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Deep_Crisp_Boundaries_CVPR_2017_paper.html,CVPR,2017,https://github.com/Wangyupei/CED,9,1/2/2019 +Pooled Motion Features for First-Person Videos,http://openaccess.thecvf.com/content_cvpr_2015/html/Ryoo_Pooled_Motion_Features_2015_CVPR_paper.html,CVPR,2015,https://github.com/USCDataScience/hadoop-pot,6,1/2/2019 +Efficient and Robust Color Consistency for Community Photo Collections,http://openaccess.thecvf.com/content_cvpr_2016/html/Park_Efficient_and_Robust_CVPR_2016_paper.html,CVPR,2016,https://github.com/syncle/photo_consistency,7,1/2/2019 +Tensor Biclustering,http://papers.nips.cc/paper/6730-tensor-biclustering.pdf,NIPS,2017,https://github.com/SoheilFeizi/Tensor-Biclustering,6,1/2/2019 +Generalizing to Unseen Domains via Adversarial Data Augmentation,http://arxiv.org/abs/1805.12018v1,NIPS,2018,https://github.com/ricvolpi/generalize-unseen-domains,36,1/2/2019 +Unsupervised Pixel-Level Domain Adaptation With Generative Adversarial Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Bousmalis_Unsupervised_Pixel-Level_Domain_CVPR_2017_paper.html,CVPR,2017,https://github.com/rhythm92/Unsupervised-Pixel-Level-Domain-Adaptation-with-GAN,6,1/2/2019 +Following Gaze in Video,http://openaccess.thecvf.com/content_iccv_2017/html/Recasens_Following_Gaze_in_ICCV_2017_paper.html,ICCV,2017,https://github.com/recasens/Gaze-Following,8,1/2/2019 +Object Contour Detection With a Fully Convolutional Encoder-Decoder Network,http://openaccess.thecvf.com/content_cvpr_2016/html/Yang_Object_Contour_Detection_CVPR_2016_paper.html,CVPR,2016,https://github.com/Raj-08/tensorflow-object-contour-detection,14,1/2/2019 +Simpler Non-Parametric Methods Provide as Good or Better Results to Multiple-Instance Learning,http://openaccess.thecvf.com/content_iccv_2015/html/Venkatesan_Simpler_Non-Parametric_Methods_ICCV_2015_paper.html,ICCV,2015,https://github.com/ragavvenkatesan/np-mil,7,1/2/2019 +3D Shape Attributes,http://openaccess.thecvf.com/content_cvpr_2016/html/Fouhey_3D_Shape_Attributes_CVPR_2016_paper.html,CVPR,2016,https://github.com/petermalcolm/estimate3DStep,6,1/2/2019 +Finding Distractors In Images,http://openaccess.thecvf.com/content_cvpr_2015/html/Fried_Finding_Distractors_In_2015_CVPR_paper.html,CVPR,2015,https://github.com/ohadf/distractors,7,1/2/2019 +ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking,http://openaccess.thecvf.com/content_ECCV_2018/html/Oliver_Groth_ShapeStacks_Learning_Vision-Based_ECCV_2018_paper.html,ECCV,2018,https://github.com/ogroth/shapestacks,11,1/2/2019 +Riemannian approach to batch normalization,http://papers.nips.cc/paper/7107-riemannian-approach-to-batch-normalization.pdf,NIPS,2017,https://github.com/MinhyungCho/riemannian-batch-normalization,6,1/2/2019 +End-To-End Learning of Geometry and Context for Deep Stereo Regression,http://openaccess.thecvf.com/content_iccv_2017/html/Kendall_End-To-End_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/liuruijin17/RickLiuGC,9,1/2/2019 +Improving Training of Deep Neural Networks via Singular Value Bounding,http://openaccess.thecvf.com/content_cvpr_2017/html/Jia_Improving_Training_of_CVPR_2017_paper.html,CVPR,2017,https://github.com/kui-jia/svb,6,1/2/2019 +Bayesian inference on random simple graphs with power law degree distributions,http://proceedings.mlr.press/v70/lee17a.html,ICML,2017,https://github.com/juho-lee/powerlawgraph,6,1/2/2019 +Reasoning About Fine-Grained Attribute Phrases Using Reference Games,http://openaccess.thecvf.com/content_iccv_2017/html/Su_Reasoning_About_Fine-Grained_ICCV_2017_paper.html,ICCV,2017,https://github.com/jongchyisu/attribute_phrases,7,1/2/2019 +Deep Learning Under Privileged Information Using Heteroscedastic Dropout,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lambert_Deep_Learning_Under_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/johnwlambert/dlupi-heteroscedastic-dropout,14,1/2/2019 +Multi-Label Image Recognition by Recurrently Discovering Attentional Regions,http://openaccess.thecvf.com/content_iccv_2017/html/Wang_Multi-Label_Image_Recognition_ICCV_2017_paper.html,ICCV,2017,https://github.com/James-Yip/AttentionImageClass,20,1/2/2019 +Centered Weight Normalization in Accelerating Training of Deep Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Centered_Weight_Normalization_ICCV_2017_paper.html,ICCV,2017,https://github.com/huangleiBuaa/CenteredWN,6,1/2/2019 +Adversarial Learning with Local Coordinate Coding,http://proceedings.mlr.press/v80/cao18a.html,ICML,2018,https://github.com/guoyongcs/LCCGAN,7,1/2/2019 +On GANs and GMMs,http://arxiv.org/abs/1805.12462v1,NIPS,2018,https://github.com/eitanrich/gans-n-gmms,10,1/2/2019 +Building a Regular Decision Boundary With Deep Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Oyallon_Building_a_Regular_CVPR_2017_paper.html,CVPR,2017,https://github.com/edouardoyallon/deep_separation_contraction,6,1/2/2019 +Learning a Descriptor-Specific 3D Keypoint Detector,http://openaccess.thecvf.com/content_iccv_2015/html/Salti_Learning_a_Descriptor-Specific_ICCV_2015_paper.html,ICCV,2015,https://github.com/CVLAB-Unibo/Keypoint-Learning,10,1/2/2019 +Towards Open-Set Identity Preserving Face Synthesis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Bao_Towards_Open-Set_Identity_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chloeguoqing/Towards-Open-Set-Identity-Preserving-Face-Synthesis,9,1/2/2019 +Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification,http://openaccess.thecvf.com/content_cvpr_2016/html/Hou_Patch-Based_Convolutional_Neural_CVPR_2016_paper.html,CVPR,2016,https://github.com/cheersyouran/cancer-detector,9,1/2/2019 +Piecewise Flat Embedding for Image Segmentation,http://openaccess.thecvf.com/content_iccv_2015/html/Yu_Piecewise_Flat_Embedding_ICCV_2015_paper.html,ICCV,2015,https://github.com/chaoweifang/PFE,7,1/2/2019 +Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems,http://papers.nips.cc/paper/6838-analyzing-hidden-representations-in-end-to-end-automatic-speech-recognition-systems.pdf,NIPS,2017,https://github.com/boknilev/asr-repr-analysis,6,1/2/2019 +A generic decentralized trust management framework,http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2012/MSC/MSC-2012-22.pdf,SPE,2013,https://github.com/amitport/graphpack,6,1/2/2019 +Personalized Image Aesthetics,http://openaccess.thecvf.com/content_iccv_2017/html/Ren_Personalized_Image_Aesthetics_ICCV_2017_paper.html,ICCV,2017,https://github.com/alanspike/personalizedImageAesthetics,7,1/2/2019 +Banach Wasserstein GAN,http://arxiv.org/abs/1806.06621v1,NIPS,2018,https://github.com/adler-j/bwgan,7,1/2/2019 +Towards Open World 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Guidance for Viewpoint Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Szeto_Click_Here_Human-Localized_ICCV_2017_paper.html,ICCV,2017,https://github.com/rszeto/click-here-cnn,5,1/2/2019 +Regret Minimization in MDPs with Options without Prior Knowledge,http://papers.nips.cc/paper/6909-regret-minimization-in-mdps-with-options-without-prior-knowledge.pdf,NIPS,2017,https://github.com/RonanFR/UCRL,8,1/2/2019 +Learning to Separate Object Sounds by Watching Unlabeled Video,http://openaccess.thecvf.com/content_ECCV_2018/html/Ruohan_Gao_Learning_to_Separate_ECCV_2018_paper.html,ECCV,2018,https://github.com/rhgao/separating-object-sounds,23,1/2/2019 +Ultra Large-Scale Feature Selection using Count-Sketches,http://proceedings.mlr.press/v80/aghazadeh18a.html,ICML,2018,https://github.com/rdspring1/MISSION,6,1/2/2019 +Transfer Learning via Learning to Transfer,http://proceedings.mlr.press/v80/wei18a.html,ICML,2018,https://github.com/QuebecAI/webcam-transfer-learning-v1,5,1/2/2019 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Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Jiren_Zhu_HiDDeN_Hiding_Data_ECCV_2018_paper.html,ECCV,2018,https://github.com/jirenz/HiDDeN,21,1/2/2019 +Robust Adversarial Reinforcement Learning,http://proceedings.mlr.press/v70/pinto17a.html,ICML,2017,https://github.com/Jekyll1021/RARL,6,1/2/2019 +K-Medoids For K-Means Seeding,http://papers.nips.cc/paper/7104-k-medoids-for-k-means-seeding.pdf,NIPS,2017,https://github.com/idiap/zentas,6,1/2/2019 +Orthogonally Decoupled Variational Gaussian Processes,http://arxiv.org/abs/1809.08820v1,NIPS,2018,https://github.com/hughsalimbeni/orth_decoupled_var_gps,6,1/2/2019 +Unsupervised holistic image generation from key local patches,http://openaccess.thecvf.com/content_ECCV_2018/html/Donghoon_Lee_Unsupervised_holistic_image_ECCV_2018_paper.html,ECCV,2018,https://github.com/hellbell/KeyPatchGan,6,1/2/2019 +Testing and Learning on Distributions with Symmetric Noise Invariance,http://papers.nips.cc/paper/6733-testing-and-learning-on-distributions-with-symmetric-noise-invariance.pdf,NIPS,2017,https://github.com/hcllaw/phase_learn,5,1/2/2019 +Dense Semantic Correspondence Where Every Pixel is a Classifier,http://openaccess.thecvf.com/content_iccv_2015/html/Bristow_Dense_Semantic_Correspondence_ICCV_2015_paper.html,ICCV,2015,https://github.com/hbristow/epic,5,1/2/2019 +Learning Steady-States of Iterative Algorithms over Graphs,http://proceedings.mlr.press/v80/dai18a.html,ICML,2018,https://github.com/Hanjun-Dai/steady_state_embedding,7,1/2/2019 +"Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference",http://papers.nips.cc/paper/7268-sticking-the-landing-simple-lower-variance-gradient-estimators-for-variational-inference.pdf,NIPS,2017,https://github.com/geoffroeder/iwae,5,1/2/2019 +Beyond Local Search: Tracking Objects Everywhere With Instance-Specific Proposals,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhu_Beyond_Local_Search_CVPR_2016_paper.html,CVPR,2016,https://github.com/GaoCode/EBT,5,1/2/2019 +NeuralFDR: Learning Discovery Thresholds from Hypothesis Features,http://papers.nips.cc/paper/6752-neuralfdr-learning-discovery-thresholds-from-hypothesis-features.pdf,NIPS,2017,https://github.com/fxia22/NeuralFDR,5,1/2/2019 +Inter and Intra Topic Structure Learning with Word Embeddings,http://proceedings.mlr.press/v80/zhao18a.html,ICML,2018,https://github.com/ethanhezhao/WEDTM,5,1/2/2019 +Modeling Sparse Deviations for Compressed Sensing using Generative Models,http://proceedings.mlr.press/v80/dhar18a.html,ICML,2018,https://github.com/ermongroup/sparse_gen,9,1/2/2019 +Diving into the shallows: a computational perspective on large-scale shallow learning,http://papers.nips.cc/paper/6968-diving-into-the-shallows-a-computational-perspective-on-large-scale-shallow-learning.pdf,NIPS,2017,https://github.com/EigenPro/EigenPro-tensorflow,5,1/2/2019 +Rotation Equivariant Vector Field Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Marcos_Rotation_Equivariant_Vector_ICCV_2017_paper.html,ICCV,2017,https://github.com/dmarcosg/RotEqNet,5,1/2/2019 +Neural Architecture Optimization,http://arxiv.org/abs/1808.07233v3,NIPS,2018,https://github.com/dicarlolab/archconvnets,5,1/2/2019 +"Pixels, Voxels, and Views: A Study of Shape Representations for Single View 3D Object Shape Prediction",http://openaccess.thecvf.com/content_cvpr_2018/papers/Shin_Pixels_Voxels_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/daeyun/object-shapes-cvpr18,9,1/2/2019 +Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web Prior,http://openaccess.thecvf.com/content_ECCV_2018/html/Sijia_Cai_Weakly-supervised_Video_Summarization_ECCV_2018_paper.html,ECCV,2018,https://github.com/cssjcai/vesd,5,1/2/2019 +Recursive Sampling for the Nystrom Method,http://papers.nips.cc/paper/6973-recursive-sampling-for-the-nystrom-method.pdf,NIPS,2017,https://github.com/cnmusco/recursive-nystrom,5,1/2/2019 +Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations,http://proceedings.mlr.press/v80/chen18g.html,ICML,2018,https://github.com/chentingpc/kdcode-lm,8,1/2/2019 +Constraint-Aware Deep Neural Network Compression,http://openaccess.thecvf.com/content_ECCV_2018/html/Changan_Chen_Constraints_Matter_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/ChanganVR/ConstraintAwareCompression,9,1/2/2019 +Functional Faces: Groupwise Dense Correspondence Using Functional Maps,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Functional_Faces_Groupwise_CVPR_2016_paper.html,CVPR,2016,https://github.com/cazhang/funcFaces,5,1/2/2019 +The Mirage of Action-Dependent Baselines in Reinforcement Learning,http://proceedings.mlr.press/v80/tucker18a.html,ICML,2018,https://github.com/brain-research/mirage-rl,7,1/2/2019 +Learning From Video and Text via Large-Scale Discriminative Clustering,http://openaccess.thecvf.com/content_iccv_2017/html/Miech_Learning_From_Video_ICCV_2017_paper.html,ICCV,2017,https://github.com/antoine77340/iccv17learning,5,1/2/2019 +Don’t Just Assume Look and Answer: Overcoming Priors for Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Agrawal_Dont_Just_Assume_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/AishwaryaAgrawal/GVQA,7,1/2/2019 +Cognitive Mapping and Planning for Visual 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Information in Images,http://openaccess.thecvf.com/content_cvpr_2018/papers/Orekondy_Connecting_Pixels_to_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tribhuvanesh/visual_redactions,4,1/2/2019 +Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking,http://openaccess.thecvf.com/content_ECCV_2018/html/Yingjie_Yao_Joint_Representation_and_ECCV_2018_paper.html,ECCV,2018,https://github.com/tourmaline612/RTINet,4,1/2/2019 +Predicting Salient Face in Multiple-Face Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Liu_Predicting_Salient_Face_CVPR_2017_paper.html,CVPR,2017,https://github.com/tonysy/salient-face-in-MUVFET,4,1/2/2019 +Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification,http://openaccess.thecvf.com/content_ECCV_2018/html/Eric_Muller-Budack_Geolocation_Estimation_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/TIBHannover/GeoEstimation,4,1/2/2019 +Superdifferential Cuts for Binary Energies,http://openaccess.thecvf.com/content_cvpr_2015/html/Taniai_Superdifferential_Cuts_for_2015_CVPR_paper.html,CVPR,2015,https://github.com/t-taniai/SDC_CVPR2015,4,1/2/2019 +Global optimization of Lipschitz functions,http://proceedings.mlr.press/v70/malherbe17a.html,ICML,2017,https://github.com/Sycor4x/lipo,5,1/2/2019 +Pose Induction for Novel Object Categories,http://openaccess.thecvf.com/content_iccv_2015/html/Tulsiani_Pose_Induction_for_ICCV_2015_paper.html,ICCV,2015,https://github.com/shubhtuls/poseInduction,4,1/2/2019 +Multi-View Convolutional Neural Networks for 3D Shape Recognition,http://openaccess.thecvf.com/content_iccv_2015/html/Su_Multi-View_Convolutional_Neural_ICCV_2015_paper.html,ICCV,2015,https://github.com/shawnxu1318/MVCNN-Multi-View-Convolutional-Neural-Networks,7,1/2/2019 +Learning Cooperative Visual Dialog Agents With Deep Reinforcement Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Das_Learning_Cooperative_Visual_ICCV_2017_paper.html,ICCV,2017,https://github.com/schopra8/Cooperative_Vis_Diag_RL,4,1/2/2019 +Estimating the Success of Unsupervised Image to Image Translation,http://openaccess.thecvf.com/content_ECCV_2018/html/Lior_Wolf_Estimating_the_Success_ECCV_2018_paper.html,ECCV,2018,https://github.com/sagiebenaim/gan_bound,5,1/2/2019 +Bottleneck Conditional Density Estimation,http://proceedings.mlr.press/v70/shu17a.html,ICML,2017,https://github.com/RuiShu/bcde,4,1/2/2019 +Quadrature-based features for kernel approximation,http://arxiv.org/abs/1802.03832v3,NIPS,2018,https://github.com/quffka/quffka,4,1/2/2019 +Towards Realistic Predictors,http://openaccess.thecvf.com/content_ECCV_2018/html/Pei_Wang_Towards_Realistic_Predictors_ECCV_2018_paper.html,ECCV,2018,https://github.com/peiwang062/towards-realistic-predictors,7,1/2/2019 +ROAM: A Rich Object Appearance Model With Application to 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Models,http://openaccess.thecvf.com/content_iccv_2017/html/Huijser_Active_Decision_Boundary_ICCV_2017_paper.html,ICCV,2017,https://github.com/MiriamHu/ActiveBoundary,5,1/2/2019 +Differentially Private Database Release via Kernel Mean Embeddings,http://proceedings.mlr.press/v80/balog18a.html,ICML,2018,https://github.com/matejbalog/RKHS-private-database,4,1/2/2019 +Mutual Information Neural Estimation,http://proceedings.mlr.press/v80/belghazi18a.html,ICML,2018,https://github.com/MasanoriYamada/Mine_pytorch,39,1/2/2019 +Simultaneous Deep Transfer Across Domains and Tasks,http://openaccess.thecvf.com/content_iccv_2015/html/Tzeng_Simultaneous_Deep_Transfer_ICCV_2015_paper.html,ICCV,2015,https://github.com/mahfujau/domain_adaptation_iccv15,6,1/2/2019 +Inference Suboptimality in Variational Autoencoders,http://proceedings.mlr.press/v80/cremer18a.html,ICML,2018,https://github.com/lxuechen/inference-suboptimality,4,1/2/2019 +Classification from Pairwise Similarity and Unlabeled 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+Robust Physical-World Attacks on Deep Learning Visual Classification,http://openaccess.thecvf.com/content_cvpr_2018/papers/Eykholt_Robust_Physical-World_Attacks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/evtimovi/robust_physical_perturbations,11,1/2/2019 +Understanding Black-box Predictions via Influence Functions,http://proceedings.mlr.press/v70/koh17a.html,ICML,2017,https://github.com/eolecvk/InfluenceFunctions,5,1/2/2019 +"Decoupling ""when to update"" from ""how to update""",http://papers.nips.cc/paper/6697-decoupling-when-to-update-from-how-to-update.pdf,NIPS,2017,https://github.com/emalach/UpdateByDisagreement,5,1/2/2019 +Deep Recurrent Neural Network-Based Identification of Precursor microRNAs,http://papers.nips.cc/paper/6882-deep-recurrent-neural-network-based-identification-of-precursor-micrornas.pdf,NIPS,2017,https://github.com/eleventh83/deepMiRGene,4,1/2/2019 +Differentially private Bayesian learning on distributed data,http://papers.nips.cc/paper/6915-differentially-private-bayesian-learning-on-distributed-data.pdf,NIPS,2017,https://github.com/DPBayes/dca-nips2017,5,1/2/2019 +Grad-CAM: Visual Explanations From Deep Networks via Gradient-Based Localization,http://openaccess.thecvf.com/content_iccv_2017/html/Selvaraju_Grad-CAM_Visual_Explanations_ICCV_2017_paper.html,ICCV,2017,https://github.com/cydonia999/Grad-CAM-in-TensorFlow,5,1/2/2019 +Guarantees for Greedy Maximization of Non-submodular Functions with Applications,http://proceedings.mlr.press/v70/bian17a.html,ICML,2017,https://github.com/bianan/non-submodular-max,4,1/2/2019 +Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains,http://openaccess.thecvf.com/content_cvpr_2018/papers/Pang_Zoom_and_Learn_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Artifineuro/zole,6,1/2/2019 +Question Asking as Program 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Parameterization,http://proceedings.mlr.press/v80/zhang18g.html,ICML,2018,https://github.com/zhangjiong724/spectral-RNN,3,1/2/2019 +Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving,http://openaccess.thecvf.com/content_ECCV_2018/html/Peiliang_LI_Stereo_Vision-based_Semantic_ECCV_2018_paper.html,ECCV,2018,https://github.com/zhanghanduo/stereo_semantic_mapping,5,1/2/2019 +A Unified View of Multi-Label Performance Measures,http://proceedings.mlr.press/v70/wu17a.html,ICML,2017,https://github.com/YuriWu/LIMO,2,1/2/2019 +Robust Saliency Detection via Regularized Random Walks Ranking,http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Robust_Saliency_Detection_2015_CVPR_paper.html,CVPR,2015,https://github.com/yuanyc06/rr,3,1/2/2019 +A Joint Sequence Fusion Model for Video Question Answering and Retrieval,http://openaccess.thecvf.com/content_ECCV_2018/html/Youngjae_Yu_A_Joint_Sequence_ECCV_2018_paper.html,ECCV,2018,https://github.com/yj-yu/lsmdc,11,1/2/2019 +SegStereo: Exploiting Semantic Information for Disparity Estimation,http://openaccess.thecvf.com/content_ECCV_2018/html/Guorun_Yang_SegStereo_Exploiting_Semantic_ECCV_2018_paper.html,ECCV,2018,https://github.com/yangguorun/SegStereo,16,1/2/2019 +Gaze Prediction in Dynamic 360° Immersive Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Gaze_Prediction_in_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/xuyanyu-shh/VR-EyeTracking,3,1/2/2019 +Saliency Detection in 360° Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Ziheng_Zhang_Saliency_Detection_in_ECCV_2018_paper.html,ECCV,2018,https://github.com/xuyanyu-shh/Saliency-detection-in-360-video,9,1/2/2019 +Image Super-Resolution via Dual-State Recurrent Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Han_Image_Super-Resolution_via_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/WeiHan3/dsrn,1,1/2/2019 +Ring Loss: Convex Feature Normalization for Face Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zheng_Ring_Loss_Convex_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/vsatyakumar/Ring-Loss-Keras,3,1/2/2019 +Multi-Label Cross-Modal Retrieval,http://openaccess.thecvf.com/content_iccv_2015/html/Ranjan_Multi-Label_Cross-Modal_Retrieval_ICCV_2015_paper.html,ICCV,2015,https://github.com/Viresh-R/ml-CCA,4,1/2/2019 +Feedback-Prop: Convolutional Neural Network Inference Under Partial Evidence,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Feedback-Prop_Convolutional_Neural_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/uvavision/feedbackprop,4,1/2/2019 +Rolling-Shutter-Aware Differential SfM and Image Rectification,http://openaccess.thecvf.com/content_iccv_2017/html/Zhuang_Rolling-Shutter-Aware_Differential_SfM_ICCV_2017_paper.html,ICCV,2017,https://github.com/ThomasZiegler/RS-aware-differential-SfM,5,1/2/2019 +Learning to Branch,http://proceedings.mlr.press/v80/balcan18a.html,ICML,2018,https://github.com/StoneyJackson/github-workflow-activity,3,1/2/2019 +Sidekick Policy Learning for Active Visual Exploration,http://openaccess.thecvf.com/content_ECCV_2018/html/Santhosh_Kumar_Ramakrishnan_Sidekick_Policy_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/srama2512/sidekicks,5,1/2/2019 +Spatially-Adaptive Filter Units for Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Tabernik_Spatially-Adaptive_Filter_Units_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/skokec/DAU-ConvNet,3,1/2/2019 +Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs,http://papers.nips.cc/paper/7049-near-optimal-edge-evaluation-in-explicit-generalized-binomial-graphs.pdf,NIPS,2017,https://github.com/sanjibac/matlab_learning_collision_checking,3,1/2/2019 +Large Margin Object Tracking With Circulant Feature Maps,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Large_Margin_Object_CVPR_2017_paper.html,CVPR,2017,https://github.com/sallymmx/LMCF,3,1/2/2019 +Adversarial Surrogate Losses for Ordinal Regression,http://papers.nips.cc/paper/6659-adversarial-surrogate-losses-for-ordinal-regression.pdf,NIPS,2017,https://github.com/rizalzaf/adversarial-ordinal,3,1/2/2019 +DenseCap: Fully Convolutional Localization Networks for Dense Captioning,http://openaccess.thecvf.com/content_cvpr_2016/html/Johnson_DenseCap_Fully_Convolutional_CVPR_2016_paper.html,CVPR,2016,https://github.com/rampage644/densecap-tensorflow,4,1/2/2019 +Encoder Based Lifelong Learning,http://openaccess.thecvf.com/content_iccv_2017/html/Rannen_Encoder_Based_Lifelong_ICCV_2017_paper.html,ICCV,2017,https://github.com/rahafaljundi/Encoder-Based-Lifelong-learning,4,1/2/2019 +Counting Everyday Objects in Everyday Scenes,http://openaccess.thecvf.com/content_cvpr_2017/html/Chattopadhyay_Counting_Everyday_Objects_CVPR_2017_paper.html,CVPR,2017,https://github.com/prithv1/cvpr2017_counting,3,1/2/2019 +Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System,http://papers.nips.cc/paper/6849-toward-goal-driven-neural-network-models-for-the-rodent-whisker-trigeminal-system.pdf,NIPS,2017,https://github.com/neuroailab/whisker_model,3,1/2/2019 +Alternating Direction Graph Matching,http://openaccess.thecvf.com/content_cvpr_2017/html/Le-Huu_Alternating_Direction_Graph_CVPR_2017_paper.html,CVPR,2017,https://github.com/netw0rkf10w/adgm,4,1/2/2019 +Deep Burst 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Videos,http://openaccess.thecvf.com/content_iccv_2015/html/Sedaghat_Unsupervised_Generation_of_ICCV_2015_paper.html,ICCV,2015,https://github.com/lmb-freiburg/unsup-car-dataset,5,1/2/2019 +Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems,http://papers.nips.cc/paper/6798-expectation-propagation-with-stochastic-kinetic-model-in-complex-interaction-systems.pdf,NIPS,2017,https://github.com/lefangcs/Expectation-Propagation-with-Stochastic-Kinetic-Model-in-Complex-Interaction-Systems,3,1/2/2019 +Simultaneous Video Defogging and Stereo Reconstruction,http://openaccess.thecvf.com/content_cvpr_2015/html/Li_Simultaneous_Video_Defogging_2015_CVPR_paper.html,CVPR,2015,https://github.com/Lashuk1729/DIP-Project-Video-Dehazing,3,1/2/2019 +Hyperspectral Super-Resolution by Coupled Spectral Unmixing,http://openaccess.thecvf.com/content_iccv_2015/html/Lanaras_Hyperspectral_Super-Resolution_by_ICCV_2015_paper.html,ICCV,2015,https://github.com/lanha/SupResPALM,3,1/2/2019 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Learning,http://arxiv.org/abs/1807.00801v1,NIPS,2018,https://github.com/hyejikim1/Deepcode,4,1/2/2019 +Disentangling Factors of Variation by Mixing Them,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Disentangling_Factors_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/HuQyang/Disentangling-Factors-of-Variation-by-Mixing-Them,5,1/2/2019 +Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization,http://openaccess.thecvf.com/content_cvpr_2015/html/Oh_Fast_Randomized_Singular_2015_CVPR_paper.html,CVPR,2015,https://github.com/HlG4399/FRSVT,5,1/2/2019 +Learning Answer Embeddings for Visual Question Answering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Learning_Answer_Embeddings_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hexiang-hu/answer_embedding,3,1/2/2019 +Context-Aware Gaussian Fields for Non-Rigid Point Set Registration,http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Context-Aware_Gaussian_Fields_CVPR_2016_paper.html,CVPR,2016,https://github.com/gwang-cv/CA-LapGF-Demo,3,1/2/2019 +Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach,http://openaccess.thecvf.com/content_cvpr_2017/html/Patrini_Making_Deep_Neural_CVPR_2017_paper.html,CVPR,2017,https://github.com/GarrettLee/label_noise_correction,5,1/2/2019 +Oriented Object Proposals,http://openaccess.thecvf.com/content_iccv_2015/html/He_Oriented_Object_Proposals_ICCV_2015_paper.html,ICCV,2015,https://github.com/frutuozo29/WebServiceRESTFul,3,1/2/2019 +Segment Graph Based Image Filtering: Fast Structure-Preserving Smoothing,http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Segment_Graph_Based_ICCV_2015_paper.html,ICCV,2015,https://github.com/feihuzhang/SGF,5,1/2/2019 +A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control,http://papers.nips.cc/paper/7177-a-framework-for-multi-armedbandit-testing-with-online-fdr-control.pdf,NIPS,2017,https://github.com/fanny-yang/MABFDR,3,1/2/2019 +kNN Hashing With Factorized Neighborhood Representation,http://openaccess.thecvf.com/content_iccv_2015/html/Ding_kNN_Hashing_With_ICCV_2015_paper.html,ICCV,2015,https://github.com/dooook/kNN-hashing,3,1/2/2019 +Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care,http://proceedings.mlr.press/v80/schwab18a.html,ICML,2018,https://github.com/d909b/DSMT-Nets,3,1/2/2019 +Minimum Barrier Salient Object Detection at 80 FPS,http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Minimum_Barrier_Salient_ICCV_2015_paper.html,ICCV,2015,https://github.com/coderSkyChen/MBS_Cplus_c-,3,1/2/2019 +Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning,http://papers.nips.cc/paper/7154-unifying-pac-and-regret-uniform-pac-bounds-for-episodic-reinforcement-learning.pdf,NIPS,2017,https://github.com/chrodan/FiniteEpisodicRL.jl,3,1/2/2019 +High-Resolution Image Synthesis and Semantic Manipulation With Conditional GANs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_High-Resolution_Image_Synthesis_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/chenxli/High-Resolution-Image-Synthesis-and-Semantic-Manipulation-with-Conditional-GANsl-,8,1/2/2019 +Parallel Bayesian Network Structure Learning,http://proceedings.mlr.press/v80/gao18b.html,ICML,2018,https://github.com/bign8/PyStruct,3,1/2/2019 +Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms,http://papers.nips.cc/paper/6652-continuous-dr-submodular-maximization-structure-and-algorithms.pdf,NIPS,2017,https://github.com/bianan,3,9/16/2018 +On Structured Prediction Theory with Calibrated Convex Surrogate Losses,http://papers.nips.cc/paper/6634-on-structured-prediction-theory-with-calibrated-convex-surrogate-losses.pdf,NIPS,2017,https://github.com/aosokin/consistentSurrogates_derivations,4,1/2/2019 +Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings,http://openaccess.thecvf.com/content_iccv_2017/html/Thewlis_Unsupervised_Learning_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/alldbi/Factorized-Spatial-Embeddings,6,1/2/2019 +Compatible Reward Inverse Reinforcement Learning,http://papers.nips.cc/paper/6800-compatible-reward-inverse-reinforcement-learning.pdf,NIPS,2017,https://github.com/albertometelli/crirl,3,1/2/2019 +Tensor Belief Propagation,http://proceedings.mlr.press/v70/wrigley17a.html,ICML,2017,https://github.com/akxlr/tbp,6,1/2/2019 +Convergent Tree Backup and Retrace with Function Approximation,http://proceedings.mlr.press/v80/touati18a.html,ICML,2018,https://github.com/ahmed-touati/convergent-off-policy,3,1/2/2019 +Efficient Globally Optimal 2D-To-3D Deformable Shape Matching,http://openaccess.thecvf.com/content_cvpr_2016/html/Lahner_Efficient_Globally_Optimal_CVPR_2016_paper.html,CVPR,2016,https://github.com/zorah/Elastic2D3D,2,1/2/2019 +Batched High-dimensional Bayesian Optimization via Structural Kernel Learning,http://proceedings.mlr.press/v70/wang17h.html,ICML,2017,https://github.com/zi-w/Structural-Kernel-Learning-for-HDBBO,2,1/2/2019 +Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhang_Dynamic_Scene_Deblurring_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhjwustc/cvpr18_rnn_deblur_matcaffe,6,1/2/2019 +Learning Fully Convolutional Networks for Iterative Non-Blind Deconvolution,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Learning_Fully_Convolutional_CVPR_2017_paper.html,CVPR,2017,https://github.com/zhjwustc/cvpr17_iter_deblur_testing_matconvnet,2,1/2/2019 +End-to-End Flow Correlation Tracking With Spatial-Temporal Attention,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhu_End-to-End_Flow_Correlation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/zhengzhugithub/FlowTrack,3,1/2/2019 +Discriminative Bimodal Networks for Visual Localization and Detection With Natural Language Queries,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Discriminative_Bimodal_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/YutingZhang/dbnet-caffe-matlab,3,1/2/2019 +Permutation-based Causal Inference Algorithms with Interventions,http://papers.nips.cc/paper/7164-permutation-based-causal-inference-algorithms-with-interventions.pdf,NIPS,2017,https://github.com/yuhaow/sp-intervention,2,1/2/2019 +An Egocentric Look at Video Photographer Identity,http://openaccess.thecvf.com/content_cvpr_2016/html/Hoshen_An_Egocentric_Look_CVPR_2016_paper.html,CVPR,2016,https://github.com/Yedid/ego,2,1/2/2019 +Learning to Super-Resolve Blurry Face and Text Images,http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Learning_to_Super-Resolve_ICCV_2017_paper.html,ICCV,2017,https://github.com/xuxy09/joint_SR_Deblur,2,1/2/2019 +Joint Person Segmentation and Identification in Synchronized First- and Third-person Videos,http://openaccess.thecvf.com/content_ECCV_2018/html/Mingze_Xu_Joint_Person_Segmentation_ECCV_2018_paper.html,ECCV,2018,https://github.com/xumingze0308/firstthird-eccv2018,2,1/2/2019 +Learning Non-Maximum Suppression,http://openaccess.thecvf.com/content_cvpr_2017/html/Hosang_Learning_Non-Maximum_Suppression_CVPR_2017_paper.html,CVPR,2017,https://github.com/XingchenYu/pedestrian_detection_iosapp,3,1/2/2019 +Inferring Forces and Learning Human Utilities From Videos,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhu_Inferring_Forces_and_CVPR_2016_paper.html,CVPR,2016,https://github.com/xiaozhuchacha/ChairPerson,2,1/2/2019 +Weakly Supervised Object Localization With Progressive Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2016/html/Li_Weakly_Supervised_Object_CVPR_2016_paper.html,CVPR,2016,https://github.com/wupeng78/Weakly-Supervised-Object-Localization-with-Progressive-Domain-Adaptation-CVPR-2016-,2,1/2/2019 +AOD-Net: All-In-One Dehazing Network,http://openaccess.thecvf.com/content_iccv_2017/html/Li_AOD-Net_All-In-One_Dehazing_ICCV_2017_paper.html,ICCV,2017,https://github.com/weber0522bb/AODnet-by-pytorch,6,1/2/2019 +CIDEr: Consensus-Based Image Description Evaluation,http://openaccess.thecvf.com/content_cvpr_2015/html/Vedantam_CIDEr_Consensus-Based_Image_2015_CVPR_paper.html,CVPR,2015,https://github.com/vrama91/cider-matlab,2,1/2/2019 +A Weighted Sparse Sampling and Smoothing Frame Transition Approach for Semantic Fast-Forward First-Person Videos,http://openaccess.thecvf.com/content_cvpr_2018/papers/Silva_A_Weighted_Sparse_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/verlab/SemanticFastForward_CVPR_2018,2,1/2/2019 +Black Box FDR,http://proceedings.mlr.press/v80/tansey18a.html,ICML,2018,https://github.com/tansey/bb-fdr,4,1/2/2019 +Joint Recovery of Dense Correspondence and Cosegmentation in Two Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Taniai_Joint_Recovery_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/t-taniai/TSS_CVPR2016_Demo,2,1/2/2019 +Conditional Neural Processes,http://proceedings.mlr.press/v80/garnelo18a.html,ICML,2018,https://github.com/suyashnigam/ConditionalNeuralProcesses,2,1/2/2019 +Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes,http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_He_Diverse_Conditional_Image_ECCV_2018_paper.html,ECCV,2018,https://github.com/SSAW14/Image_Generation_with_Latent_Code,4,1/2/2019 +Subspace Clustering for Sequential Data,http://openaccess.thecvf.com/content_cvpr_2014/html/Tierney_Subspace_Clustering_for_2014_CVPR_paper.html,CVPR,2014,https://github.com/sjtrny/OSC,2,1/2/2019 +Structural Sparse Tracking,http://openaccess.thecvf.com/content_cvpr_2015/html/Zhang_Structural_Sparse_Tracking_2015_CVPR_paper.html,CVPR,2015,https://github.com/shenjianbing/Visual-tracking-using-strong-classifier-and-structural-local-sparse-descriptors-,2,1/2/2019 +Extreme Clicking for Efficient Object Annotation,http://openaccess.thecvf.com/content_iccv_2017/html/Papadopoulos_Extreme_Clicking_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/serycjon/extreme_clicking,2,1/2/2019 +Less Is More: Zero-Shot Learning From Online Textual Documents With Noise Suppression,http://openaccess.thecvf.com/content_cvpr_2016/html/Qiao_Less_Is_More_CVPR_2016_paper.html,CVPR,2016,https://github.com/rqiao/zsl_noise_suppression,2,1/2/2019 +Information Constraints on Auto-Encoding Variational Bayes,http://arxiv.org/abs/1805.08672v2,NIPS,2018,https://github.com/romain-lopez/HCV,3,1/2/2019 +Composite Functional Gradient Learning of Generative Adversarial Models,http://proceedings.mlr.press/v80/johnson18a.html,ICML,2018,https://github.com/riejohnson/cfg-gan,2,1/2/2019 +Learning for Active 3D Mapping,http://openaccess.thecvf.com/content_iccv_2017/html/Zimmermann_Learning_for_Active_ICCV_2017_paper.html,ICCV,2017,https://github.com/RheoDesign/AAVS-Beijing,2,1/2/2019 +Efficient Algorithms for Moral Lineage Tracing,http://openaccess.thecvf.com/content_iccv_2017/html/Rempfler_Efficient_Algorithms_for_ICCV_2017_paper.html,ICCV,2017,https://github.com/rempfler/efficient-mlt,2,1/2/2019 +AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms,http://papers.nips.cc/paper/6893-aide-an-algorithm-for-measuring-the-accuracy-of-probabilistic-inference-algorithms.pdf,NIPS,2017,https://github.com/probcomp/nips2017-aide-experiments,2,1/2/2019 +Scalable Levy Process Priors for Spectral Kernel Learning,http://papers.nips.cc/paper/6983-scalable-levy-process-priors-for-spectral-kernel-learning.pdf,NIPS,2017,https://github.com/pjang23/levy-spectral-kernel-learning,2,1/2/2019 +DeLS-3D: Deep Localization and Segmentation With a 3D Semantic Map,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_DeLS-3D_Deep_Localization_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/pengwangucla/DeLS-3D,4,1/2/2019 +Simultaneous Stereo Video Deblurring and Scene Flow Estimation,http://openaccess.thecvf.com/content_cvpr_2017/html/Pan_Simultaneous_Stereo_Video_CVPR_2017_paper.html,CVPR,2017,https://github.com/panpanfei/data-Simultaneous-Stereo-Video-Deblurring-and-Scene-Flow-Estimation,2,1/2/2019 +A Simple yet Effective Baseline for 3D Human Pose Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Martinez_A_Simple_yet_ICCV_2017_paper.html,ICCV,2017,https://github.com/nulledge/bilinear,4,1/2/2019 +Towards Effective Low-Bitwidth Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhuang_Towards_Effective_Low-Bitwidth_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nowgood/QuantizeCNNModel,5,1/2/2019 +Recognizing Human Actions as the Evolution of Pose Estimation Maps,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Recognizing_Human_Actions_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nkliuyifang/Skeleton-based-Human-Action-Recognition,4,1/2/2019 +Moral Lineage Tracing,http://openaccess.thecvf.com/content_cvpr_2016/html/Jug_Moral_Lineage_Tracing_CVPR_2016_paper.html,CVPR,2016,https://github.com/mpi-inf-cia/moral-lineage-tracing,2,1/2/2019 +Interpolation on the Manifold of K Component GMMs,http://openaccess.thecvf.com/content_iccv_2015/html/Kim_Interpolation_on_the_ICCV_2015_paper.html,ICCV,2015,https://github.com/MLman/kgmm_interpolation,2,1/2/2019 +Teaching Categories to Human Learners With Visual Explanations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Aodha_Teaching_Categories_to_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/macaodha/explain_teach,3,1/2/2019 +A Framework for Evaluating 6-DOF Object Trackers,http://openaccess.thecvf.com/content_ECCV_2018/html/Mathieu_Garon_A_Framework_for_ECCV_2018_paper.html,ECCV,2018,https://github.com/lvsn/6DOF_tracking_evaluation,4,1/2/2019 +Contour Knowledge Transfer for Salient Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Xin_Li_Contour_Knowledge_Transfer_ECCV_2018_paper.html,ECCV,2018,https://github.com/lixin666/C2SNet,5,1/2/2019 +Multi-Layered Gradient Boosting Decision Trees,,NIPS,2018,https://github.com/limberc/ML-GBDT,2,1/2/2019 +Learning Background-Aware Correlation Filters for Visual Tracking,http://openaccess.thecvf.com/content_iccv_2017/html/Galoogahi_Learning_Background-Aware_Correlation_ICCV_2017_paper.html,ICCV,2017,https://github.com/LCAR979/BACF,2,1/2/2019 +Count-Based Exploration with Neural Density Models,http://proceedings.mlr.press/v70/ostrovski17a.html,ICML,2017,https://github.com/kristychoi/pixel_exploration,2,1/2/2019 +Using Locally Corresponding CAD Models for Dense 3D Reconstructions From a Single Image,http://openaccess.thecvf.com/content_cvpr_2017/html/Kong_Using_Locally_Corresponding_CVPR_2017_paper.html,CVPR,2017,https://github.com/kongchen1992/LDCgraph,2,1/2/2019 +Compositional Learning for Human Object Interaction,http://openaccess.thecvf.com/content_ECCV_2018/html/Keizo_Kato_Compositional_Learning_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/kkatocmu/Compositional_Learning,2,1/2/2019 +CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions,http://proceedings.mlr.press/v80/tian18a.html,ICML,2018,https://github.com/kjtian/CoVeR,2,1/2/2019 +Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition,http://openaccess.thecvf.com/content_cvpr_2018/papers/Sun_Optical_Flow_Guided_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/kitsune999/Optical-Flow-Guided-Feature,6,1/2/2019 +Adaptive As-Natural-As-Possible Image Stitching,http://openaccess.thecvf.com/content_cvpr_2015/html/Lin_Adaptive_As-Natural-As-Possible_Image_2015_CVPR_paper.html,CVPR,2015,https://github.com/KANU51/ANAP,2,1/2/2019 +"Look, Listen and Learn",http://openaccess.thecvf.com/content_iccv_2017/html/Arandjelovic_Look_Listen_and_ICCV_2017_paper.html,ICCV,2017,https://github.com/Kajiyu/LLLNet,8,1/2/2019 +Learning and Memorization,http://proceedings.mlr.press/v80/chatterjee18a.html,ICML,2018,https://github.com/jre2/AnkiRPG,2,1/2/2019 +Convex Global 3D Registration With Lagrangian Duality,http://openaccess.thecvf.com/content_cvpr_2017/html/Briales_Convex_Global_3D_CVPR_2017_paper.html,CVPR,2017,https://github.com/jbriales/CVPR17,6,1/2/2019 +Device Placement Optimization with Reinforcement Learning,http://proceedings.mlr.press/v70/mirhoseini17a.html,ICML,2017,https://github.com/indrajeet95/Device-Placement-Optimization-with-Reinforcement-Learning,4,1/2/2019 +Lifelong Learning via Progressive Distillation and Retrospection,http://openaccess.thecvf.com/content_ECCV_2018/html/Saihui_Hou_Progressive_Lifelong_Learning_ECCV_2018_paper.html,ECCV,2018,https://github.com/hshustc/ECCV18_Lifelong_Learning,3,1/2/2019 +Fitting Low-Rank Tensors in Constant Time,http://papers.nips.cc/paper/6841-fitting-low-rank-tensors-in-constant-time.pdf,NIPS,2017,https://github.com/hayasick/CTFT,2,1/2/2019 +Asynchronous Distributed Variational Gaussian Processes for Regression,,ICML,2017,https://github.com/hao-peng/ADVGP,3,1/2/2019 +Hide-And-Seek: Forcing a Network to Be Meticulous for Weakly-Supervised Object and Action Localization,http://openaccess.thecvf.com/content_iccv_2017/html/Singh_Hide-And-Seek_Forcing_a_ICCV_2017_paper.html,ICCV,2017,https://github.com/goddoe/hide-and-seek,2,1/2/2019 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Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhu_Learning_Spatial_Regularization_CVPR_2017_paper.html,CVPR,2017,https://github.com/Enjia/Spatial-Regularization-Network-in-Tensorflow,6,1/2/2019 +Generative Hierarchical Learning of Sparse FRAME Models,http://openaccess.thecvf.com/content_cvpr_2017/html/Xie_Generative_Hierarchical_Learning_CVPR_2017_paper.html,CVPR,2017,https://github.com/enijkamp/HS-FRAME,2,1/2/2019 +Low-Dimensionality Calibration Through Local Anisotropic Scaling for Robust Hand Model Personalization,http://openaccess.thecvf.com/content_iccv_2017/html/Remelli_Low-Dimensionality_Calibration_Through_ICCV_2017_paper.html,ICCV,2017,https://github.com/edoRemelli/hadjust,2,1/2/2019 +Image Retrieval Using Scene Graphs,http://openaccess.thecvf.com/content_cvpr_2015/html/Johnson_Image_Retrieval_Using_2015_CVPR_paper.html,CVPR,2015,https://github.com/econser/py_irsg_orig,2,1/2/2019 +Stochastic Gradient Monomial Gamma Sampler,http://proceedings.mlr.press/v70/zhang17a.html,ICML,2017,https://github.com/dreasysnail/SGMGT,2,1/2/2019 +Generalized Semantic Preserving Hashing for N-Label Cross-Modal Retrieval,http://openaccess.thecvf.com/content_cvpr_2017/html/Mandal_Generalized_Semantic_Preserving_CVPR_2017_paper.html,CVPR,2017,https://github.com/devraj89/Generalized-Semantic-Preserving-Hashing-for-N-Label-Cross-Modal-Retrieval,4,1/2/2019 +AdaNet: Adaptive Structural Learning of Artificial Neural Networks,http://proceedings.mlr.press/v70/cortes17a.html,ICML,2017,https://github.com/davidabek1/adanet,3,1/2/2019 +Sub-sampled Cubic Regularization for Non-convex Optimization,http://proceedings.mlr.press/v70/kohler17a.html,ICML,2017,https://github.com/dalab/subsampled_cubic_regularization,4,1/2/2019 +HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning,http://openaccess.thecvf.com/content_ECCV_2018/html/Thomas_Robert_HybridNet_Classification_and_ECCV_2018_paper.html,ECCV,2018,https://github.com/dakshitagrawal97/HybridNet,5,1/2/2019 +Online Sketching Hashing,http://openaccess.thecvf.com/content_cvpr_2015/html/Leng_Online_Sketching_Hashing_2015_CVPR_paper.html,CVPR,2015,https://github.com/cvpr2015-submission/online-sketching-hashing,2,1/2/2019 +Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising,http://openaccess.thecvf.com/content_iccv_2015/html/Xu_Patch_Group_Based_ICCV_2015_paper.html,ICCV,2015,https://github.com/csjunxu/PGPD-ICCV2015,2,1/2/2019 +Single Image Water Hazard Detection using FCN with Reflection Attention Units,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiaofeng_Han_Single_Image_Water_ECCV_2018_paper.html,ECCV,2018,https://github.com/Cow911/SingleImageWaterHazardDetectionWithRAU,4,1/2/2019 +Dropout Inference in Bayesian Neural Networks with Alpha-divergences,http://proceedings.mlr.press/v70/li17a.html,ICML,2017,https://github.com/cosmozhang/BBalpha_pytorch,2,1/2/2019 +LaVAN: Localized and Visible Adversarial Noise,http://proceedings.mlr.press/v80/karmon18a.html,ICML,2018,https://github.com/ChesterAiGo/LaVAN_python-tf-,2,1/2/2019 +Generalized Max Pooling,http://openaccess.thecvf.com/content_cvpr_2014/html/Murray_Generalized_Max_Pooling_2014_CVPR_paper.html,CVPR,2014,https://github.com/celisun/Generalized-pooling-functions-CNN,2,1/2/2019 +Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization,http://openaccess.thecvf.com/content_cvpr_2016/html/Lu_Tensor_Robust_Principal_CVPR_2016_paper.html,CVPR,2016,https://github.com/canyilu/Tensor-Robust-Principal-Component-Analysis-TRPCA,4,1/2/2019 +A Wavefront Marching Method for Solving the Eikonal Equation on Cartesian Grids,http://openaccess.thecvf.com/content_iccv_2015/html/Cancela_A_Wavefront_Marching_ICCV_2015_paper.html,ICCV,2015,https://github.com/braisCB/WMM,2,1/2/2019 +From Patches to Images: A Nonparametric Generative Model,http://proceedings.mlr.press/v70/ji17a.html,ICML,2017,https://github.com/bnpy/hdp-grid-image-restoration,2,1/2/2019 +Learning Longer-term Dependencies in RNNs with Auxiliary Losses,http://proceedings.mlr.press/v80/trinh18a.html,ICML,2018,https://github.com/belepi93/rnn-auxiliary-loss,5,1/2/2019 +Learning to Localize Sound Source in Visual Scenes,http://openaccess.thecvf.com/content_cvpr_2018/papers/Senocak_Learning_to_Localize_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ardasnck/learning_to_localize_sound,5,1/2/2019 +Multi-Task Learning for Contextual Bandits,http://papers.nips.cc/paper/7070-multi-task-learning-for-contextual-bandits.pdf,NIPS,2017,https://github.com/aniketde/MultiTaskLearningContextualBandits,2,1/2/2019 +Importance Weighted Transfer of Samples in Reinforcement Learning,http://proceedings.mlr.press/v80/tirinzoni18a.html,ICML,2018,https://github.com/AndreaTirinzoni/iw-transfer-rl,3,1/2/2019 +Configurable Markov Decision Processes,http://proceedings.mlr.press/v80/metelli18a.html,ICML,2018,https://github.com/albertometelli/Configurable-Markov-Decision-Processes-ICML-2018,4,1/2/2019 +Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design,http://proceedings.mlr.press/v80/lyu18a.html,ICML,2018,https://github.com/Alaya-in-Matrix/MACE,6,1/2/2019 +High Order Tensor Formulation for Convolutional Sparse Coding,http://openaccess.thecvf.com/content_iccv_2017/html/Bibi_High_Order_Tensor_ICCV_2017_paper.html,ICCV,2017,https://github.com/adelbibi/Tensor_CSC,2,1/2/2019 +Beyond Filters: Compact Feature Map for Portable Deep Model,http://proceedings.mlr.press/v70/wang17m.html,ICML,2017,https://github.com/a4338324/ICML-2017,2,1/2/2019 +Minimum Delay Moving Object Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Lao_Minimum_Delay_Moving_CVPR_2017_paper.html,CVPR,2017,https://github.com/zsameem/realtime-mdmod,1,1/2/2019 +Saliency Pattern Detection by Ranking Structured Trees,http://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Saliency_Pattern_Detection_ICCV_2017_paper.html,ICCV,2017,https://github.com/zhulei2016/RST-saliency,3,1/2/2019 +A Modulation Module for Multi-task Learning with Applications in Image Retrieval,http://openaccess.thecvf.com/content_ECCV_2018/html/Xiangyun_Zhao_A_Modulation_Module_ECCV_2018_paper.html,ECCV,2018,https://github.com/Zhaoxiangyun/Multi-Task-Modulation-Module,6,1/2/2019 +Unrolling the Shutter: CNN to Correct Motion Distortions,http://openaccess.thecvf.com/content_cvpr_2017/html/Rengarajan_Unrolling_the_Shutter_CVPR_2017_paper.html,CVPR,2017,https://github.com/yogeshbalaji/CVPR17_Unrolling_the_shutter,2,1/2/2019 +Self-Occlusions and Disocclusions in Causal Video Object Segmentation,http://openaccess.thecvf.com/content_iccv_2015/html/Yang_Self-Occlusions_and_Disocclusions_ICCV_2015_paper.html,ICCV,2015,https://github.com/ycyang12/SODVS,1,1/2/2019 +Stochastic Video Generation with a Learned Prior,http://proceedings.mlr.press/v80/denton18a.html,ICML,2018,https://github.com/yamata2/stochastic-video-generation,2,1/2/2019 +DSLR-Quality Photos on Mobile Devices With Deep Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Ignatov_DSLR-Quality_Photos_on_ICCV_2017_paper.html,ICCV,2017,https://github.com/wuyx/CNN---DSLR-Quality-Photos-on-Mobile-Devices-with-Deep-Convolutional-Networks,1,1/2/2019 +Discovering Potential Correlations via Hypercontractivity,http://papers.nips.cc/paper/7044-discovering-potential-correlations-via-hypercontractivity.pdf,NIPS,2017,https://github.com/wgao9/hypercontractivity,1,1/2/2019 +Primary Object Segmentation in Videos via Alternate Convex Optimization of Foreground and Background Distributions,http://openaccess.thecvf.com/content_cvpr_2016/html/Jang_Primary_Object_Segmentation_CVPR_2016_paper.html,CVPR,2016,https://github.com/wdjang/ACO,1,1/2/2019 +Contour Box: Rejecting Object Proposals Without Explicit Closed Contours,http://openaccess.thecvf.com/content_iccv_2015/html/Lu_Contour_Box_Rejecting_ICCV_2015_paper.html,ICCV,2015,https://github.com/WangHong-yang/contour-box,1,1/2/2019 +Learning Object Interactions and Descriptions for Semantic Image Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Wang_Learning_Object_Interactions_CVPR_2017_paper.html,CVPR,2017,https://github.com/wanggrun/IDW-CNN-V2,2,1/2/2019 +Gradient Descent for Spiking Neural Networks,http://arxiv.org/abs/1706.04698v2,NIPS,2018,https://github.com/vikram-mm/Spiking-Neural-Network---Theano-Framework,2,1/2/2019 +DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding,http://proceedings.mlr.press/v80/moreau18a.html,ICML,2018,https://github.com/tomMoral/Dicod,3,1/2/2019 +Adaptive Batch Size for Safe Policy Gradients,http://papers.nips.cc/paper/6950-adaptive-batch-size-for-safe-policy-gradients.pdf,NIPS,2017,https://github.com/T3p/adaptive-batch-size,1,1/2/2019 +Deep Affordance-Grounded Sensorimotor Object Recognition,http://openaccess.thecvf.com/content_cvpr_2017/html/Thermos_Deep_Affordance-Grounded_Sensorimotor_CVPR_2017_paper.html,CVPR,2017,https://github.com/spthermo/Sensorimotor,1,1/2/2019 +On clustering network-valued data,http://papers.nips.cc/paper/7282-on-clustering-network-valued-data.pdf,NIPS,2017,https://github.com/soumendu041/clustering-network-valued-data,1,1/2/2019 +Computing the Stereo Matching Cost With a Convolutional Neural Network,http://openaccess.thecvf.com/content_cvpr_2015/html/Zbontar_Computing_the_Stereo_2015_CVPR_paper.html,CVPR,2015,https://github.com/soonyk/mc-cnn,1,1/2/2019 +A Projection Free Method for Generalized Eigenvalue Problem With a Nonsmooth Regularizer,http://openaccess.thecvf.com/content_iccv_2015/html/Hwang_A_Projection_Free_ICCV_2015_paper.html,ICCV,2015,https://github.com/shwang54/iccv2015_sjh,1,1/2/2019 +Stochastic Wasserstein Barycenters,http://proceedings.mlr.press/v80/claici18a.html,ICML,2018,https://github.com/sebastian-claici/StochasticWassersteinBarycenters,1,1/2/2019 +Collaborative Deep Learning in Fixed Topology Networks,http://papers.nips.cc/paper/7172-collaborative-deep-learning-in-fixed-topology-networks.pdf,NIPS,2017,https://github.com/SCSLabISU/CDSGD,1,1/2/2019 +Weakly Supervised Dense Video Captioning,http://openaccess.thecvf.com/content_cvpr_2017/html/Shen_Weakly_Supervised_Dense_CVPR_2017_paper.html,CVPR,2017,https://github.com/SCLinDennis/Weakly-Supervised-Dense-Video-Captioning,2,1/2/2019 +Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation,,NIPS,2018,https://github.com/rwenqi/NBD-GLRA,7,1/2/2019 +Deep Visual-Semantic Alignments for Generating Image Descriptions,http://openaccess.thecvf.com/content_cvpr_2015/html/Karpathy_Deep_Visual-Semantic_Alignments_2015_CVPR_paper.html,CVPR,2015,https://github.com/rszeto/eecs-692-replication-project,1,1/2/2019 +Efficient and Consistent Adversarial Bipartite Matching,http://proceedings.mlr.press/v80/fathony18a.html,ICML,2018,https://github.com/rizalzaf/bipartite-mat,1,1/2/2019 +Gated Feedback Refinement Network for Dense Image Labeling,http://openaccess.thecvf.com/content_cvpr_2017/html/Islam_Gated_Feedback_Refinement_CVPR_2017_paper.html,CVPR,2017,https://github.com/rezaulnkarim/RefinementTest,1,1/2/2019 +Coupled End-to-End Transfer Learning With Generalized Fisher Information,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Coupled_End-to-End_Transfer_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/RankingCNN/Coupled-End-to-End-Transfer-Learning-With-Generalized-Fisher-Information,1,1/2/2019 +Expert Gate: Lifelong Learning With a Network of Experts,http://openaccess.thecvf.com/content_cvpr_2017/html/Aljundi_Expert_Gate_Lifelong_CVPR_2017_paper.html,CVPR,2017,https://github.com/rahafaljundi/Expert-Gate,4,1/2/2019 +Task-driven Webpage Saliency,http://openaccess.thecvf.com/content_ECCV_2018/html/Quanlong_Zheng_Task-driven_Webpage_Saliency_ECCV_2018_paper.html,ECCV,2018,https://github.com/quanlzheng/Task-driven-Webpage-Saliency,2,1/2/2019 +A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks,,NIPS,2018,https://github.com/pokaxpoka/deep_Mahalanobis_detector,32,1/2/2019 +Follow the Moving Leader in Deep Learning,http://proceedings.mlr.press/v70/zheng17a.html,ICML,2017,https://github.com/patniharshit/Follow-the-Moving-Leader-in-Deep-Learning,1,1/2/2019 +Unsupervised Semantic Parsing of Video Collections,http://openaccess.thecvf.com/content_iccv_2015/html/Sener_Unsupervised_Semantic_Parsing_ICCV_2015_paper.html,ICCV,2015,https://github.com/ozansener/ICCV2015,1,1/2/2019 +Feature Selective Networks for Object Detection,http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhai_Feature_Selective_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/noido/feature_selective_networks,1,1/2/2019 +Generative Local Metric Learning for Kernel Regression,http://papers.nips.cc/paper/6839-generative-local-metric-learning-for-kernel-regression.pdf,NIPS,2017,https://github.com/nohyung/Nadaraya-Watson-Regression-Metric,1,1/2/2019 +Functional Map of the World,http://openaccess.thecvf.com/content_cvpr_2018/papers/Christie_Functional_Map_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/nichochar/zapmap,1,1/2/2019 +Distributionally Robust Graphical Models,,NIPS,2018,https://github.com/Narendhar123/Linear-Regression-Algoritham-,1,10/14/2018 +Robust Budget Allocation via Continuous Submodular Functions,http://proceedings.mlr.press/v70/staib17a.html,ICML,2017,https://github.com/mstaib/robust-budget-allocation-code,1,1/2/2019 +Differentially Private Clustering in High-Dimensional Euclidean Spaces,http://proceedings.mlr.press/v70/balcan17a.html,ICML,2017,https://github.com/mouwenlong/dp-clustering-icml17,1,1/2/2019 +Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Minjun_Li_Unsupervised_Image-to-Image_Translation_ECCV_2018_paper.html,ECCV,2018,https://github.com/minjunli/SCAN,1,10/14/2018 +CartoonGAN: Generative Adversarial Networks for Photo Cartoonization,http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_CartoonGAN_Generative_Adversarial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/MingtaoGuo/CartoonGAN-tensorflow,2,1/2/2019 +Model evidence from nonequilibrium simulations,http://papers.nips.cc/paper/6772-model-evidence-from-nonequilibrium-simulations.pdf,NIPS,2017,https://github.com/michaelhabeck/paths,1,1/2/2019 +On Calibration of Modern Neural Networks,http://proceedings.mlr.press/v70/guo17a.html,ICML,2017,https://github.com/markdtw/temperature-scaling-tensorflow,1,1/2/2019 +CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces,,NIPS,2018,https://github.com/maple-research-lab/CapProNet,3,1/2/2019 +Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees,http://papers.nips.cc/paper/6679-greedy-algorithms-for-cone-constrained-optimization-with-convergence-guarantees.pdf,NIPS,2017,https://github.com/locatelf/cone-greedy,1,1/2/2019 +Defense Against Universal Adversarial Perturbations,http://openaccess.thecvf.com/content_cvpr_2018/papers/Akhtar_Defense_Against_Universal_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/liujianee/Pertrubation_Rectifying_Network,1,1/2/2019 +Inhomogeneous Hypergraph Clustering with Applications,http://papers.nips.cc/paper/6825-inhomogeneous-hypergraph-clustering-with-applications.pdf,NIPS,2017,https://github.com/lipan00123/InHclustering,2,1/2/2019 +SPFTN: A Self-Paced Fine-Tuning Network for Segmenting Objects in Weakly Labelled Videos,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_SPFTN_A_Self-Paced_CVPR_2017_paper.html,CVPR,2017,https://github.com/LeYangNwpu/SPFTN,1,1/2/2019 +Maximum Causal Tsallis Entropy Imitation Learning,http://arxiv.org/abs/1805.08336v2,NIPS,2018,https://github.com/kyungjaelee/MCTEIL,1,10/14/2018 +Matrix Norm Estimation from a Few Entries,http://papers.nips.cc/paper/7221-matrix-norm-estimation-from-a-few-entries.pdf,NIPS,2017,https://github.com/khetan2/Schatten_norm_estimation,1,1/2/2019 +Learning to Group Objects,http://openaccess.thecvf.com/content_cvpr_2014/html/Yanulevskaya_Learning_to_Group_2014_CVPR_paper.html,CVPR,2014,https://github.com/KamilWo/PHP_OOP,1,1/2/2019 +Latent Trees for Estimating Intensity of Facial Action Units,http://openaccess.thecvf.com/content_cvpr_2015/html/Kaltwang_Latent_Trees_for_2015_CVPR_paper.html,CVPR,2015,https://github.com/kaltwang/2015latent,1,1/2/2019 +Laplacian Patch-Based Image Synthesis,http://openaccess.thecvf.com/content_cvpr_2016/html/Lee_Laplacian_Patch-Based_Image_CVPR_2016_paper.html,CVPR,2016,https://github.com/KAIST-VCLAB/laplacianinpainting,1,1/2/2019 +Bidirectional Retrieval Made Simple,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wehrmann_Bidirectional_Retrieval_Made_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/jwehrmann/chain-vse,3,1/2/2019 +"Online Detection of Action Start in Untrimmed, Streaming Videos",http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Shou_Online_Detection_of_ECCV_2018_paper.html,ECCV,2018,https://github.com/junting/odas,2,1/2/2019 +MarioQA: Answering Questions by Watching Gameplay Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Mun_MarioQA_Answering_Questions_ICCV_2017_paper.html,ICCV,2017,https://github.com/JonghwanMun/MarioQA,5,1/2/2019 +ScaleNet: Guiding Object Proposal Generation in Supermarkets and Beyond,http://openaccess.thecvf.com/content_iccv_2017/html/Qiao_ScaleNet_Guiding_Object_ICCV_2017_paper.html,ICCV,2017,https://github.com/joe-siyuan-qiao/ScaleNet,1,1/2/2019 +Video-Story Composition via Plot Analysis,http://openaccess.thecvf.com/content_cvpr_2016/html/Choi_Video-Story_Composition_via_CVPR_2016_paper.html,CVPR,2016,https://github.com/jinsc37/Video-Story-CVPR16,1,1/2/2019 +Objects2action: Classifying and Localizing Actions Without Any Video Example,http://openaccess.thecvf.com/content_iccv_2015/html/Jain_Objects2action_Classifying_and_ICCV_2015_paper.html,ICCV,2015,https://github.com/JingPG2014/objects2action,1,1/2/2019 +Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy,http://proceedings.mlr.press/v80/yang18c.html,ICML,2018,https://github.com/jiaseny/kdsd,1,9/16/2018 +Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Yu_Video_Paragraph_Captioning_CVPR_2016_paper.html,CVPR,2016,https://github.com/JaywongWang/Video-Paragraph-Captioning,1,1/2/2019 +Fast Algorithms for Convolutional Neural Networks,http://openaccess.thecvf.com/content_cvpr_2016/html/Lavin_Fast_Algorithms_for_CVPR_2016_paper.html,CVPR,2016,https://github.com/istoony/winograd-convolutional-nn,3,1/2/2019 +Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models,http://openaccess.thecvf.com/content_ECCV_2018/html/Dong_Su_Is_Robustness_the_ECCV_2018_paper.html,ECCV,2018,https://github.com/IBM/ImageNet-Robustness,1,1/2/2019 +Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives,,NIPS,2018,https://github.com/IBM/Contrastive-Explanation-Method,3,1/2/2019 +DRACO: Byzantine-resilient Distributed Training via Redundant Gradients,http://proceedings.mlr.press/v80/chen18l.html,ICML,2018,https://github.com/hwang595/Draco,5,1/2/2019 +Learning Spatiotemporal Features With 3D Convolutional Networks,http://openaccess.thecvf.com/content_iccv_2015/html/Tran_Learning_Spatiotemporal_Features_ICCV_2015_paper.html,ICCV,2015,https://github.com/hunter-87/read-c3d-features-numpy,1,1/2/2019 +Priv’IT: Private and Sample Efficient Identity Testing,http://proceedings.mlr.press/v70/cai17a.html,ICML,2017,https://github.com/hoonose/privit,1,1/2/2019 +Deep Adaptive Image Clustering,http://openaccess.thecvf.com/content_iccv_2017/html/Chang_Deep_Adaptive_Image_ICCV_2017_paper.html,ICCV,2017,https://github.com/HongtaoYang/DAC-tensorflow,6,1/2/2019 +Directionally Convolutional Networks for 3D Shape Segmentation,http://openaccess.thecvf.com/content_iccv_2017/html/Xu_Directionally_Convolutional_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/HaotianMXu/3D-Shape-Segmentation-with-Deep-Neural-Networks,1,1/2/2019 +Fast and Effective L0 Gradient Minimization by Region Fusion,http://openaccess.thecvf.com/content_iccv_2015/html/Nguyen_Fast_and_Effective_ICCV_2015_paper.html,ICCV,2015,https://github.com/guqifeng/L0_norm,2,1/2/2019 +Context-Aware Synthesis for Video Frame Interpolation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Niklaus_Context-Aware_Synthesis_for_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/GeorgeBohw/interpolation,1,1/2/2019 +Geodesic Distance Descriptors,http://openaccess.thecvf.com/content_cvpr_2017/html/Shamai_Geodesic_Distance_Descriptors_CVPR_2017_paper.html,CVPR,2017,https://github.com/fuyangliu/3D-Model-Descriptor,1,1/2/2019 +Generative Modeling of Audible Shapes for Object Perception,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Generative_Modeling_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/FredHuangBia/Sound_ICCV,1,1/2/2019 +Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages,,NIPS,2018,https://github.com/forest-snow/mtanchor_demo,3,1/2/2019 +Online control of the false discovery rate with decaying memory,http://papers.nips.cc/paper/7148-online-control-of-the-false-discovery-rate-with-decaying-memory.pdf,NIPS,2017,https://github.com/fanny-yang/OnlineFDRCode,1,1/2/2019 +COLA: Decentralized Linear Learning,,NIPS,2018,https://github.com/epfml/cola,5,1/2/2019 +Structured Uncertainty Prediction Networks,http://openaccess.thecvf.com/content_cvpr_2018/papers/Dorta_Structured_Uncertainty_Prediction_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/EhtashamBillah/Acute-Lymphoblastic-Leukemia-cell-classification-using-Bayesian-Convolutional-Neural-Networks,1,1/2/2019 +S3Pool: Pooling With Stochastic Spatial Sampling,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhai_S3Pool_Pooling_With_CVPR_2017_paper.html,CVPR,2017,https://github.com/edgarmedina1801/S3Pool,1,1/2/2019 +Playing hard exploration games by watching YouTube,http://arxiv.org/abs/1805.11592v1,NIPS,2018,https://github.com/dnddnjs/learning-from-youtube,1,10/14/2018 +Highly-Economized Multi-View Binary Compression for Scalable Image Clustering,http://openaccess.thecvf.com/content_ECCV_2018/html/Zheng_Zhang_Highly-Economized_Multi-View_Binary_ECCV_2018_paper.html,ECCV,2018,https://github.com/DarrenZhangZ/HSIC,1,10/1/2018 +Adversarial PoseNet: A Structure-Aware Convolutional Network for Human Pose Estimation,http://openaccess.thecvf.com/content_iccv_2017/html/Chen_Adversarial_PoseNet_A_ICCV_2017_paper.html,ICCV,2017,https://github.com/danache/Adversarial-PoseNet,1,1/2/2019 +Fast Zero-Shot Image Tagging,http://openaccess.thecvf.com/content_cvpr_2016/html/Zhang_Fast_Zero-Shot_Image_CVPR_2016_paper.html,CVPR,2016,https://github.com/csueb-research/fast-zero-shot-image-tagging,1,1/2/2019 +MEC: Memory-efficient Convolution for Deep Neural Network,http://proceedings.mlr.press/v70/cho17a.html,ICML,2017,https://github.com/CSshengxy/MEC,4,1/2/2019 +A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping,http://openaccess.thecvf.com/content_cvpr_2018/papers/Liang_A_Hybrid_l1-l0_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/csjunxu/L1L0_TM-CVPR2018,3,1/2/2019 +Multispectral Image Intrinsic Decomposition via Subspace Constraint,http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Multispectral_Image_Intrinsic_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cianhwang/MIID,2,1/2/2019 +Chi-square Generative Adversarial Network,http://proceedings.mlr.press/v80/tao18b.html,ICML,2018,https://github.com/chenyang-tao/chi2gan,2,1/2/2019 +Co-teaching: Robust Training Deep Neural Networks with Extremely Noisy Labels,,NIPS,2018,https://github.com/char256/co-teaching_bohan_et.al,1,1/2/2019 +Linearly constrained Gaussian processes,http://papers.nips.cc/paper/6721-linearly-constrained-gaussian-processes.pdf,NIPS,2017,https://github.com/carji475/linearly-constrained-gaussian-processes,1,1/2/2019 +A Joint Intrinsic-Extrinsic Prior Model for Retinex,http://openaccess.thecvf.com/content_iccv_2017/html/Cai_A_Joint_Intrinsic-Extrinsic_ICCV_2017_paper.html,ICCV,2017,https://github.com/caibolun/JieP,2,1/2/2019 +Learning unknown ODE models with Gaussian processes,http://proceedings.mlr.press/v80/heinonen18a.html,ICML,2018,https://github.com/cagatayyildiz/npode,1,1/2/2019 +The committee machine: Computational to statistical gaps in learning a two-layers neural network,,NIPS,2018,https://github.com/benjaminaubin/TheCommitteeMachine,1,1/2/2019 +The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities,http://papers.nips.cc/paper/7031-the-expxorcist-nonparametric-graphical-models-via-conditional-exponential-densities.pdf,NIPS,2017,https://github.com/arunsais/Expxorcist,1,1/2/2019 +Found Graph Data and Planted Vertex Covers,http://arxiv.org/abs/1805.01209v1,NIPS,2018,https://github.com/arbenson/FGDnPVC,1,1/2/2019 +Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization,http://proceedings.mlr.press/v80/filstroff18a.html,ICML,2018,https://github.com/alumbreras/MMLE-GaP,1,1/2/2019 +Robust Optimization for Deep Regression,http://openaccess.thecvf.com/content_iccv_2015/html/Belagiannis_Robust_Optimization_for_ICCV_2015_paper.html,ICCV,2015,https://github.com/AIHGF/matconvnet-deepReg,1,1/2/2019 +Unsupervised Hard Example Mining from Videos for Improved Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/SouYoung_Jin_Unsupervised_Hard-Negative_Mining_ECCV_2018_paper.html,ECCV,2018,https://github.com/adiprasad/unsup-hard-negative-mining-mscoco,1,1/2/2019 +3D Part-Based Sparse Tracker With Automatic Synchronization and Registration,http://openaccess.thecvf.com/content_cvpr_2016/html/Bibi_3D_Part-Based_Sparse_CVPR_2016_paper.html,CVPR,2016,https://github.com/adelbibi/3D-Part-Based-Sparse-Tracker-with-Automatic-Synchronization-and-Registration,1,1/2/2019 +Video Acceleration Magnification,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Video_Acceleration_Magnification_CVPR_2017_paper.html,CVPR,2017,https://github.com/acceleration-magnification/acceleration-magnification.github.io,1,1/2/2019 +Video Representation Learning Using Discriminative Pooling,http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Video_Representation_Learning_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/3xWangDot/SVMP,2,1/2/2019 +Learning Discriminative Video Representations Using Adversarial Perturbations,http://openaccess.thecvf.com/content_ECCV_2018/html/Jue_Wang_Learning_Discriminative_Video_ECCV_2018_paper.html,ECCV,2018,https://github.com/3xWangDot/DSP,2,1/2/2019 +"Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning",http://openaccess.thecvf.com/content_cvpr_2018/papers/Ge_Multi-Evidence_Filtering_and_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/ZYYSzj/Multi-Evidence-Filtering-and-Fusion-WSL,0,1/2/2019 +Stein Points,http://proceedings.mlr.press/v80/chen18f.html,ICML,2018,https://github.com/ZloyChert/Romash.ISO.SteinerPoints,0,1/2/2019 +Deep Defense: Training DNNs with Improved Adversarial Robustness,http://arxiv.org/abs/1803.00404v2,NIPS,2018,https://github.com/ZiangYan/deepdefense.pytorch,8,1/2/2019 +Supervision by Fusion: Towards Unsupervised Learning of Deep Salient Object Detector,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Supervision_by_Fusion_ICCV_2017_paper.html,ICCV,2017,https://github.com/zhangyuygss/caffe-modified,0,1/2/2019 +Active Learning with Logged Data,http://proceedings.mlr.press/v80/yan18a.html,ICML,2018,https://github.com/yyysbysb/al_log_icml18,0,1/2/2019 +Long-Term Recurrent Convolutional Networks for Visual Recognition and Description,http://openaccess.thecvf.com/content_cvpr_2015/html/Donahue_Long-Term_Recurrent_Convolutional_2015_CVPR_paper.html,CVPR,2015,https://github.com/yurisan/Long-term-Recurrent-Convolutional-Networks-for-Visual-Recognition-and-Description,0,1/2/2019 +The Weighted Kendall and High-order Kernels for Permutations,http://proceedings.mlr.press/v80/jiao18a.html,ICML,2018,https://github.com/YunlongJiao/weightedkendall,0,1/2/2019 +On Word Embedding Dimensionality,,NIPS,2018,https://github.com/yukubo/sample_word2vec_skipgram,0,1/2/2019 +DeepPINK: reproducible feature selection in deep neural networks,http://arxiv.org/abs/1809.01185v2,NIPS,2018,https://github.com/younglululu/DeepPINK,0,1/2/2019 +Ego-Surfing First-Person Videos,http://openaccess.thecvf.com/content_cvpr_2015/html/Yonetani_Ego-Surfing_First-Person_Videos_2015_CVPR_paper.html,CVPR,2015,https://github.com/yonetaniryo/corrsearch,0,1/2/2019 +Multiresolution Kernel Approximation for Gaussian Process Regression,http://papers.nips.cc/paper/6964-multiresolution-kernel-approximation-for-gaussian-process-regression.pdf,NIPS,2017,https://github.com/yiding2012/MKA,0,1/2/2019 +Accurate Inference for Adaptive Linear Models,http://proceedings.mlr.press/v80/deshpande18a.html,ICML,2018,https://github.com/yash-deshpande/decorrelating-linear-models,1,1/2/2019 +Modular Generative Adversarial Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Bo_Zhao_Modular_Generative_Adversarial_ECCV_2018_paper.html,ECCV,2018,https://github.com/xjdeng/EasyGAN,0,1/2/2019 +Weighted-Entropy-Based Quantization for Deep Neural Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Park_Weighted-Entropy-Based_Quantization_for_CVPR_2017_paper.html,CVPR,2017,https://github.com/xiaoweiChen/Weighted-Entropy-based-Quantization-for-Deep-Neural-Networks,0,1/2/2019 +End-To-End People Detection in Crowded Scenes,http://openaccess.thecvf.com/content_cvpr_2016/html/Stewart_End-To-End_People_Detection_CVPR_2016_paper.html,CVPR,2016,https://github.com/wuyx/End-to-end-people-detection-in-crowded-scenes,0,1/2/2019 +Towards End-To-End Text Spotting With Convolutional Recurrent Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Li_Towards_End-To-End_Text_ICCV_2017_paper.html,ICCV,2017,https://github.com/wuyenan/-Towards-End-to-end-Text-Spotting-with-Convolutional-Recurrent-Neural-Networks,0,1/2/2019 +A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations,http://proceedings.mlr.press/v80/nie18a.html,ICML,2018,https://github.com/weilinie/BackpropVis,1,1/2/2019 +What If We Do Not Have Multiple Videos of the Same Action? -- Video Action Localization Using Web Images,http://openaccess.thecvf.com/content_cvpr_2016/html/Sultani_What_If_We_CVPR_2016_paper.html,CVPR,2016,https://github.com/WaqasSultani/ActionLocalization_CVPR16,0,1/2/2019 +"Cross-view Action Modeling, Learning and Recognition",http://openaccess.thecvf.com/content_cvpr_2014/html/Wang_Cross-view_Action_Modeling_2014_CVPR_paper.html,CVPR,2014,https://github.com/wangjiangb/crossviewActionRecognition,0,1/2/2019 +Deep Neural Networks with Box Convolutions,,NIPS,2018,https://github.com/vvoluom/Neural-Networks,0,10/1/2018 +ResNet with one-neuron hidden layers is a Universal Approximator,http://arxiv.org/abs/1806.10909v2,NIPS,2018,https://github.com/vinsis/points-in-2d,0,1/2/2019 +Guided Proofreading of Automatic Segmentations for Connectomics,http://openaccess.thecvf.com/content_cvpr_2018/papers/Haehn_Guided_Proofreading_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/VCG/guidedproofreading,0,1/2/2019 +Reducing Network Agnostophobia,,NIPS,2018,https://github.com/Vastlab/Reducing-Network-Agnostophobia,2,1/2/2019 +Gray-box Adversarial Training,http://openaccess.thecvf.com/content_ECCV_2018/html/Vivek_B_S_Gray_box_adversarial_ECCV_2018_paper.html,ECCV,2018,https://github.com/val-iisc/gat,0,1/2/2019 +What Value Do Explicit High Level Concepts Have in Vision to Language Problems?,http://openaccess.thecvf.com/content_cvpr_2016/html/Wu_What_Value_Do_CVPR_2016_paper.html,CVPR,2016,https://github.com/upccpu/-,0,1/2/2019 +Motion-Depth: RGB-D Depth Map Enhancement with Motion and Depth in Complement,http://openaccess.thecvf.com/content_cvpr_2014/html/Hui_Motion-Depth_RGB-D_Depth_2014_CVPR_paper.html,CVPR,2014,https://github.com/twhui/Motion-Depth,0,1/2/2019 +Efficient Point Process Inference for Large-Scale Object Detection,http://openaccess.thecvf.com/content_cvpr_2016/html/Pham_Efficient_Point_Process_CVPR_2016_paper.html,CVPR,2016,https://github.com/trungtpham/point_process_optimisation,0,1/2/2019 +"Real-World Repetition Estimation by Div, Grad and Curl",http://openaccess.thecvf.com/content_cvpr_2018/papers/Runia_Real-World_Repetition_Estimation_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/tomrunia/RepetitionEstimation,1,1/2/2019 +Efficient Intersection of Three Quadrics and Applications in Computer Vision,http://openaccess.thecvf.com/content_cvpr_2016/html/Kukelova_Efficient_Intersection_of_CVPR_2016_paper.html,CVPR,2016,https://github.com/tolgabirdal/e3q3,0,1/2/2019 +Adaptive Neural Networks for Efficient Inference,http://proceedings.mlr.press/v70/bolukbasi17a.html,ICML,2017,https://github.com/tolga-b/ann,0,1/2/2019 +A Laplacian Framework for Option Discovery in Reinforcement Learning,http://proceedings.mlr.press/v70/machado17a.html,ICML,2017,https://github.com/timguoqk/option_discovery,0,1/2/2019 +SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate,http://proceedings.mlr.press/v80/ramdas18a.html,ICML,2018,https://github.com/tijana-zrnic/SAFFRONcode,0,1/2/2019 +Product Split Trees,http://openaccess.thecvf.com/content_cvpr_2017/html/Babenko_Product_Split_Trees_CVPR_2017_paper.html,CVPR,2017,https://github.com/theherobrinehunter/Mod,1,1/2/2019 +Emotion Recognition in Context,http://openaccess.thecvf.com/content_cvpr_2017/html/Kosti_Emotion_Recognition_in_CVPR_2017_paper.html,CVPR,2017,https://github.com/Thanuja2812/Deep-Neural-Network,0,1/2/2019 +Hybrid Camera Pose Estimation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Camposeco_Hybrid_Camera_Pose_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/TeaganLi/A-Hybrid-3DoF-Pose-Estimation-Method-based-on-Camera-and-Lidar-Data,0,1/2/2019 +Multi-View Subspace Clustering,http://openaccess.thecvf.com/content_iccv_2015/html/Gao_Multi-View_Subspace_Clustering_ICCV_2015_paper.html,ICCV,2015,https://github.com/TaoZhou19/Dual-Shared-Specific-Multi-view-Subspace-Clustering,0,1/2/2019 +Comparison-Based Random Forests,http://proceedings.mlr.press/v80/haghiri18a.html,ICML,2018,https://github.com/SylwiaOliwia2/Decision-tree-random-forest-xgboost-comparison,0,1/2/2019 +Guided Perturbations: Self-Corrective Behavior in Convolutional Neural Networks,http://openaccess.thecvf.com/content_iccv_2017/html/Sankaranarayanan_Guided_Perturbations_Self-Corrective_ICCV_2017_paper.html,ICCV,2017,https://github.com/swamiviv/guided_perturbations,1,1/2/2019 +Non-Blind Deblurring: Handling Kernel Uncertainty With CNNs,http://openaccess.thecvf.com/content_cvpr_2018/papers/Vasu_Non-Blind_Deblurring_Handling_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/subeeshvasu/2018_subeesh_nbd_cvpr,0,1/2/2019 +Object-centered image stitching,http://openaccess.thecvf.com/content_ECCV_2018/html/Charles_Herrmann_Object-centered_image_stitching_ECCV_2018_paper.html,ECCV,2018,https://github.com/StewartNash/img_proc_7,0,1/2/2019 +Topological mixture estimation,http://proceedings.mlr.press/v80/huntsman18a.html,ICML,2018,https://github.com/SteveHuntsmanBAESystems/TopologicalMixtureEstimation,0,1/2/2019 +Non-metric Similarity Graphs for Maximum Inner Product Search,,NIPS,2018,https://github.com/stanis-morozov/ip-nsw,7,1/2/2019 +Gradient Boosted Decision Trees for High Dimensional Sparse Output,http://proceedings.mlr.press/v70/si17a.html,ICML,2017,https://github.com/springdaisy/GBDT,0,1/2/2019 +What Do Deep Networks Like to See?,http://openaccess.thecvf.com/content_cvpr_2018/papers/Palacio_What_Do_Deep_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/spalaciob/normnets,0,1/2/2019 +Analysis by Synthesis: 3D Object Recognition by Object Reconstruction,http://openaccess.thecvf.com/content_cvpr_2014/html/Hejrati_Analysis_by_Synthesis_2014_CVPR_paper.html,CVPR,2014,https://github.com/siqihao95/Musical-Analysis-by-Synthesis,0,1/2/2019 +Neural Network Encapsulation,http://openaccess.thecvf.com/content_ECCV_2018/html/Hongyang_Li_Neural_Network_Encapsulation_ECCV_2018_paper.html,ECCV,2018,https://github.com/sio2boss/k5-spec,0,1/2/2019 +From Source to Target and Back: Symmetric Bi-Directional Adaptive GAN,http://openaccess.thecvf.com/content_cvpr_2018/papers/Russo_From_Source_to_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/shubhampachori12110095/GAN,0,1/2/2019 +Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation,,NIPS,2018,https://github.com/shivapratap/AlgorithmicAssurance_NIPS2018,0,1/2/2019 +Estimating Sparse Signals With Smooth Support via Convex Programming and Block Sparsity,http://openaccess.thecvf.com/content_cvpr_2016/html/Shah_Estimating_Sparse_Signals_CVPR_2016_paper.html,CVPR,2016,https://github.com/shahsohil/CoLaMP,0,1/2/2019 +Learning with Abandonment,http://proceedings.mlr.press/v80/schmit18a.html,ICML,2018,https://github.com/schmit/learning-abandonment,0,1/2/2019 +Infinite Feature Selection,http://openaccess.thecvf.com/content_iccv_2015/html/Roffo_Infinite_Feature_Selection_ICCV_2015_paper.html,ICCV,2015,https://github.com/Sadegh28/SINF,0,1/2/2019 +Gaussian Process Conditional Density Estimation,,NIPS,2018,https://github.com/richardbayes/bayes-treed-cde,0,1/2/2019 +Learning SMaLL Predictors,http://arxiv.org/abs/1803.02388v1,NIPS,2018,https://github.com/retropean/mspa-apps,0,1/2/2019 +Diversity-Enhanced Condensation Algorithm and Its Application for Robust and Accurate Endoscope Three-Dimensional Motion Tracking,http://openaccess.thecvf.com/content_cvpr_2014/html/Luo_Diversity-Enhanced_Condensation_Algorithm_2014_CVPR_paper.html,CVPR,2014,https://github.com/renzhe0009/Diversity-Enhanced-Condensation-Algorithm,0,1/2/2019 +Learning to Predict Saliency on Face Images,http://openaccess.thecvf.com/content_iccv_2015/html/Xu_Learning_to_Predict_ICCV_2015_paper.html,ICCV,2015,https://github.com/RenYun2016/Face,0,1/2/2019 +Clustering of Static-Adaptive Correspondences for Deformable Object Tracking,http://openaccess.thecvf.com/content_cvpr_2015/html/Nebehay_Clustering_of_Static-Adaptive_2015_CVPR_paper.html,CVPR,2015,https://github.com/rafaelvareto/CMT-Tracker,0,1/2/2019 +Streaming Principal Component Analysis in Noisy Setting,http://proceedings.mlr.press/v80/marinov18a.html,ICML,2018,https://github.com/r3831/NPCA,0,1/2/2019 +Local and Global Optimization Techniques in Graph-Based Clustering,http://openaccess.thecvf.com/content_cvpr_2018/papers/Ikami_Local_and_Global_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/qiao-/thesis_GPU_parallel_EuclideanMST_Multiple_2or3-opt_moves_for_graph_minimization-,0,1/2/2019 +Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees,http://proceedings.mlr.press/v80/taylor18a.html,ICML,2018,https://github.com/QCGroup/quad-lyap-first-order,0,1/2/2019 +Consistent Robust Regression,http://papers.nips.cc/paper/6806-consistent-robust-regression.pdf,NIPS,2017,https://github.com/purushottamkar/rreg,0,1/2/2019 +What Will Happen Next? Forecasting Player Moves in Sports Videos,http://openaccess.thecvf.com/content_iccv_2017/html/Felsen_What_Will_Happen_ICCV_2017_paper.html,ICCV,2017,https://github.com/pulkitag/sports-forecasting,0,1/2/2019 +Nearly Optimal Robust Subspace Tracking,http://proceedings.mlr.press/v80/narayanamurthy18a.html,ICML,2018,https://github.com/praneethmurthy/NORST,0,1/2/2019 +Laplacian Coordinates for Seeded Image Segmentation,http://openaccess.thecvf.com/content_cvpr_2014/html/Casaca_Laplacian_Coordinates_for_2014_CVPR_paper.html,CVPR,2014,https://github.com/pianoza/seproject,0,1/2/2019 +Unsupervised Correlation Analysis,http://openaccess.thecvf.com/content_cvpr_2018/papers/Hoshen_Unsupervised_Correlation_Analysis_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/pgyrya/customer_segments,0,1/2/2019 +Learning Abstract Options,,NIPS,2018,https://github.com/petterasla/IECCS,0,1/2/2019 +Smooth Representation Clustering,http://openaccess.thecvf.com/content_cvpr_2014/html/Hu_Smooth_Representation_Clustering_2014_CVPR_paper.html,CVPR,2014,https://github.com/PennStateStatGen/WaveletBasedFunctionalCluster,0,1/2/2019 +Complexity-Adaptive Distance Metric for Object Proposals Generation,http://openaccess.thecvf.com/content_cvpr_2015/html/Xiao_Complexity-Adaptive_Distance_Metric_2015_CVPR_paper.html,CVPR,2015,https://github.com/peacefulxy/CADM,0,1/2/2019 +Policy Optimization as Wasserstein Gradient Flows,http://proceedings.mlr.press/v80/zhang18a.html,ICML,2018,https://github.com/paper-review/ICML2018,0,1/2/2019 +Structured Set Matching Networks for One-Shot Part Labeling,http://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_Structured_Set_Matching_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Oushesh/Structured-Set-Matching-Networks-for-One-Shot-Part-Labeling-readme,0,1/2/2019 +Efficient First-Order Algorithms for Adaptive Signal Denoising,http://proceedings.mlr.press/v80/ostrovskii18a.html,ICML,2018,https://github.com/ostrodmit/AlgoRec,0,1/2/2019 +Best of Both Worlds: Human-Machine Collaboration for Object Annotation,http://openaccess.thecvf.com/content_cvpr_2015/html/Russakovsky_Best_of_Both_2015_CVPR_paper.html,CVPR,2015,https://github.com/orussakovsky/best-of-both-worlds,0,1/2/2019 +Best Response Regression,http://papers.nips.cc/paper/6748-best-response-regression.pdf,NIPS,2017,https://github.com/omerbp/Best-Response-Regression,0,1/2/2019 +Truncating Wide Networks Using Binary Tree Architectures,http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Truncating_Wide_Networks_ICCV_2017_paper.html,ICCV,2017,https://github.com/nutszebra/wide_networks_using_binary_tree,0,1/2/2019 +Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification,http://openaccess.thecvf.com/content_iccv_2015/html/He_Delving_Deep_into_ICCV_2015_paper.html,ICCV,2015,https://github.com/nutszebra/prelu_net,2,1/2/2019 +Unified Embedding and Metric Learning for Zero-Exemplar Event Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Hussein_Unified_Embedding_and_CVPR_2017_paper.html,CVPR,2017,https://github.com/noureldien/unified_embedding,0,1/2/2019 +Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction,,NIPS,2018,https://github.com/nips2018axiomatic/Mapping-Images-to-Scene-Graphs-master,2,1/2/2019 +Unsupervised Learning of Depth and Ego-Motion From Monocular Video Using 3D Geometric Constraints,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mahjourian_Unsupervised_Learning_of_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/Nick36/unsupervised-learning-depth-ego-motion,0,1/2/2019 +Unsupervised Learning of Depth and Ego-Motion From Video,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhou_Unsupervised_Learning_of_CVPR_2017_paper.html,CVPR,2017,https://github.com/Nick36/unsupervised-learning-depth-ego-motion,0,1/2/2019 +Dynamic Time-Of-Flight,http://openaccess.thecvf.com/content_cvpr_2017/html/Schober_Dynamic_Time-Of-Flight_CVPR_2017_paper.html,CVPR,2017,https://github.com/neiljones12/Whackathon2016,0,1/2/2019 +Predict and Constrain: Modeling Cardinality in Deep Structured Prediction,http://proceedings.mlr.press/v80/brukhim18a.html,ICML,2018,https://github.com/Natalybr/predict_and_constrain,1,1/2/2019 +Propagated Image Filtering,http://openaccess.thecvf.com/content_cvpr_2015/html/Chang_Propagated_Image_Filtering_2015_CVPR_paper.html,CVPR,2015,https://github.com/NASA-Planetary-Science/SALTAD,0,1/2/2019 +Processing of missing data by neural networks,http://arxiv.org/abs/1805.07405v2,NIPS,2018,https://github.com/mzkhan2000/TypeNeuralModel,0,1/2/2019 +Comparator Networks,http://openaccess.thecvf.com/content_ECCV_2018/html/Weidi_Xie_Comparator_Networks_ECCV_2018_paper.html,ECCV,2018,https://github.com/Morwenn/comparator-networks,0,1/2/2019 +Linear Ranking Analysis,http://openaccess.thecvf.com/content_cvpr_2014/html/Deng_Linear_Ranking_Analysis_2014_CVPR_paper.html,CVPR,2014,https://github.com/MickyDowns/mine_ncaa_rankings,0,1/2/2019 +Relationship Proposal Networks,http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_Relationship_Proposal_Networks_CVPR_2017_paper.html,CVPR,2017,https://github.com/mdxedia/Awsome-Cash,1,1/2/2019 +Semi-supervised Spectral Clustering for Image Set Classification,http://openaccess.thecvf.com/content_cvpr_2014/html/Mahmood_Semi-supervised_Spectral_Clustering_2014_CVPR_paper.html,CVPR,2014,https://github.com/Masoud-Fatemi/Pattern-Recognition,0,1/2/2019 +A Generative Model of People in Clothing,http://openaccess.thecvf.com/content_iccv_2017/html/Lassner_A_Generative_Model_ICCV_2017_paper.html,ICCV,2017,https://github.com/Masaokb/ClothesNet_PyTorch,0,1/2/2019 +SWIFT: Sparse Withdrawal of Inliers in a First Trial,http://openaccess.thecvf.com/content_cvpr_2015/html/Jaberi_SWIFT_Sparse_Withdrawal_2015_CVPR_paper.html,CVPR,2015,https://github.com/mary-jab/SWIFT,0,1/2/2019 +Adaptive Clustering through Semidefinite Programming,http://papers.nips.cc/paper/6776-adaptive-clustering-through-semidefinite-programming.pdf,NIPS,2017,https://github.com/martinroyer/pecok,0,1/2/2019 +Scalable Bayesian Rule Lists,http://proceedings.mlr.press/v70/yang17h.html,ICML,2017,https://github.com/margoseltzer/homebrew-sbrlmod,0,1/2/2019 +Efficient Multiple Instance Metric Learning Using Weakly Supervised Data,http://openaccess.thecvf.com/content_cvpr_2017/html/Law_Efficient_Multiple_Instance_CVPR_2017_paper.html,CVPR,2017,https://github.com/MarcTLaw/MIMLCA,0,1/2/2019 +Variational Bayesian Multiple Instance Learning With Gaussian Processes,http://openaccess.thecvf.com/content_cvpr_2017/html/Haussmann_Variational_Bayesian_Multiple_CVPR_2017_paper.html,CVPR,2017,https://github.com/manuelhaussmann/vgpmil,0,1/2/2019 +Learning Deep Representation for Imbalanced Classification,http://openaccess.thecvf.com/content_cvpr_2016/html/Huang_Learning_Deep_Representation_CVPR_2016_paper.html,CVPR,2016,https://github.com/Makundi/Machine-Learning-IPT-ParrotAI,1,1/2/2019 +Distributed Clustering via LSH Based Data Partitioning,http://proceedings.mlr.press/v80/bhaskara18a.html,ICML,2018,https://github.com/maheshakya/DistClust_via_LSH_L2,0,1/2/2019 +Delayed Impact of Fair Machine Learning,http://proceedings.mlr.press/v80/liu18c.html,ICML,2018,https://github.com/lydiatliu/delayedimpact,2,1/2/2019 +A High-Quality Denoising Dataset for Smartphone Cameras,http://openaccess.thecvf.com/content_cvpr_2018/papers/Abdelhamed_A_High-Quality_Denoising_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/luhannan/mean-fusion-to-denoise-image,0,1/2/2019 +Structured Regression Gradient Boosting,http://openaccess.thecvf.com/content_cvpr_2016/html/Diego_Structured_Regression_Gradient_CVPR_2016_paper.html,CVPR,2016,https://github.com/LJohanna/Project_Python_SpeedDatingData,0,1/2/2019 +Data-Efficient Hierarchical Reinforcement Learning,,NIPS,2018,https://github.com/lizhuoru/aaai17,0,1/2/2019 +Open Category Detection with PAC Guarantees,http://proceedings.mlr.press/v80/liu18e.html,ICML,2018,https://github.com/liusi2019/ocd,1,1/2/2019 +Using Spatial Order to Boost the Elimination of Incorrect Feature Matches,http://openaccess.thecvf.com/content_cvpr_2016/html/Talker_Using_Spatial_Order_CVPR_2016_paper.html,CVPR,2016,https://github.com/liortalker/SpatialOrder,3,1/2/2019 +Efficient Sliding Window Computation for NN-Based Template Matching,http://openaccess.thecvf.com/content_ECCV_2018/html/Lior_Talker_Efficient_Sliding_Window_ECCV_2018_paper.html,ECCV,2018,https://github.com/liortalker/DIWU,2,1/2/2019 +"A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening",http://papers.nips.cc/paper/7264-a-sharp-error-analysis-for-the-fused-lasso-with-application-to-approximate-changepoint-screening.pdf,NIPS,2017,https://github.com/linnylin92/fused_lasso,0,1/2/2019 +Deep Learning Strong Parts for Pedestrian Detection,http://openaccess.thecvf.com/content_iccv_2015/html/Tian_Deep_Learning_Strong_ICCV_2015_paper.html,ICCV,2015,https://github.com/lijinxi1314/Deep_learning_strong_parts,0,1/2/2019 +Boosted Sparse and Low-Rank Tensor Regression,,NIPS,2018,https://github.com/LifangHe/SURF,1,1/2/2019 +Dual Supervised Learning,http://proceedings.mlr.press/v70/xia17a.html,ICML,2017,https://github.com/LifangHe/SDM14_DuSK,0,1/2/2019 +Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior,,NIPS,2018,https://github.com/Learning-and-Intelligent-Systems/meta-bo,0,1/2/2019 +Understanding Classifier Errors by Examining Influential Neighbors,http://openaccess.thecvf.com/content_cvpr_2015/html/Kabra_Understanding_Classifier_Errors_2015_CVPR_paper.html,CVPR,2015,https://github.com/kristinbranson/InfluentialNeighbors,0,1/2/2019 +Co-Occurrence Filter,http://openaccess.thecvf.com/content_cvpr_2017/html/Jevnisek_Co-Occurrence_Filter_CVPR_2017_paper.html,CVPR,2017,https://github.com/kobybibas/CoOccurrenceFilter,0,1/2/2019 +Learning to Assign Orientations to Feature Points,http://openaccess.thecvf.com/content_cvpr_2016/html/Yi_Learning_to_Assign_CVPR_2016_paper.html,CVPR,2016,https://github.com/kmyid/benchmark-orientation,0,1/2/2019 +Multi-Instance Object Segmentation With Occlusion Handling,http://openaccess.thecvf.com/content_cvpr_2015/html/Chen_Multi-Instance_Object_Segmentation_2015_CVPR_paper.html,CVPR,2015,https://github.com/kasertim/ObjectSegmentationOcclusionHandling,0,1/2/2019 +Leveraging Motion Priors in Videos for Improving Human Segmentation,http://openaccess.thecvf.com/content_ECCV_2018/html/Yu-Ting_Chen_Leveraging_Motion_Priors_ECCV_2018_paper.html,ECCV,2018,https://github.com/Jwy-Leo/Leveraging-Motion-Priors-in-Videos-for-Improving-Human-Segmentation,0,1/2/2019 +What Is Around the Camera?,http://openaccess.thecvf.com/content_iccv_2017/html/Georgoulis_What_Is_Around_ICCV_2017_paper.html,ICCV,2017,https://github.com/julianchow/LocationTesting,0,1/2/2019 +Local Convergence Properties of SAGA/Prox-SVRG and Acceleration,http://proceedings.mlr.press/v80/poon18a.html,ICML,2018,https://github.com/jliang993/Local-VRSGD,0,1/2/2019 +Generation and Comprehension of Unambiguous Object Descriptions,http://openaccess.thecvf.com/content_cvpr_2016/html/Mao_Generation_and_Comprehension_CVPR_2016_paper.html,CVPR,2016,https://github.com/jeetp465/Unambiguous-Object-Description,0,1/2/2019 +Large-Scale Stochastic Sampling from the Probability Simplex,http://arxiv.org/abs/1806.07137v1,NIPS,2018,https://github.com/jbaker92/SCIR,1,1/2/2019 +On the Solvability of Viewing Graphs,http://openaccess.thecvf.com/content_ECCV_2018/html/Matthew_Trager_On_the_Solvability_ECCV_2018_paper.html,ECCV,2018,https://github.com/ismummy/Train-Tracker,0,1/2/2019 +Learning Region Features for Object Detection,http://openaccess.thecvf.com/content_ECCV_2018/html/Jiayuan_Gu_Learning_Region_Features_ECCV_2018_paper.html,ECCV,2018,https://github.com/ironmanmark23/opencv_project1,0,1/2/2019 +RGB-Infrared Cross-Modality Person Re-Identification,http://openaccess.thecvf.com/content_iccv_2017/html/Wu_RGB-Infrared_Cross-Modality_Person_ICCV_2017_paper.html,ICCV,2017,https://github.com/InnovArul/rgb_IR_personreid,2,1/2/2019 +Composable Planning with Attributes,http://proceedings.mlr.press/v80/zhang18k.html,ICML,2018,https://github.com/infocampuspvtin/-Web-Designing-training-bangalore,0,1/2/2019 +Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning,http://arxiv.org/abs/1807.03146v1,NIPS,2018,https://github.com/ihankyang/keypoint-network,0,1/2/2019 +Single Image 3D Without a Single 3D Image,http://openaccess.thecvf.com/content_iccv_2015/html/Fouhey_Single_Image_3D_ICCV_2015_paper.html,ICCV,2015,https://github.com/ihankyang/keypoint-network,0,1/2/2019 +Neural Voice Cloning with a Few Samples,http://arxiv.org/abs/1802.06006v2,NIPS,2018,https://github.com/IEEE-NITK/Neural-Voice-Cloning,0,1/2/2019 +ATOMO: Communication-efficient Learning via Atomic Sparsification,http://arxiv.org/abs/1806.04090v2,NIPS,2018,https://github.com/hwang595/ATOMO,1,1/2/2019 +Designing Illuminant Spectral Power Distributions for Surface Classification,http://openaccess.thecvf.com/content_cvpr_2017/html/Blasinski_Designing_Illuminant_Spectral_CVPR_2017_paper.html,CVPR,2017,https://github.com/hblasins/optIll,0,1/2/2019 +Enhancing the Spatial Resolution of Stereo Images Using a Parallax Prior,http://openaccess.thecvf.com/content_cvpr_2018/papers/Jeon_Enhancing_the_Spatial_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/hassanisaadi/stereoSR_tf,0,1/2/2019 +Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization,http://proceedings.mlr.press/v80/wu18g.html,ICML,2018,https://github.com/hang-wu/VRCRM,0,1/2/2019 +Learning to Estimate 3D Hand Pose From Single RGB Images,http://openaccess.thecvf.com/content_iccv_2017/html/Zimmermann_Learning_to_Estimate_ICCV_2017_paper.html,ICCV,2017,https://github.com/hamaskhan/Hand3dRHD,0,1/2/2019 +CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images,http://openaccess.thecvf.com/content_ECCV_2018/html/Sheng_Guo_CurriculumNet_Learning_from_ECCV_2018_paper.html,ECCV,2018,https://github.com/guoshengcv/CurriculumNet,2,1/2/2019 +A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency,http://proceedings.mlr.press/v70/appel17a.html,ICML,2017,https://github.com/GuillaumeCollin/A-Simple-Multi-Class-Boosting-Framework-with-Theoretical-Guarantees-and-Empirical-Proficiency,0,1/2/2019 +Algebraic Variety Models for High-Rank Matrix Completion,http://proceedings.mlr.press/v70/ongie17a.html,ICML,2017,https://github.com/gregongie/vmc,0,1/2/2019 +Dynamic Few-Shot Visual Learning Without Forgetting,http://openaccess.thecvf.com/content_cvpr_2018/papers/Gidaris_Dynamic_Few-Shot_Visual_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/greentfrapp/few-shot-without-forgetting-tensorflow,1,1/2/2019 +Supervised Local Modeling for Interpretability,http://arxiv.org/abs/1807.02910v1,NIPS,2018,https://github.com/GDPlumb/SLIM,0,1/2/2019 +Multimodal Visual Concept Learning With Weakly Supervised Techniques,http://openaccess.thecvf.com/content_cvpr_2018/papers/Bouritsas_Multimodal_Visual_Concept_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/gbouritsas/cvpr18_multimodal_weakly_supervised_learning,0,1/2/2019 +Bayesian Adversarial Learning,,NIPS,2018,https://github.com/GaganNarula/BirdsongGAN_sequencelearning,0,1/2/2019 +Structured Indoor Modeling,http://openaccess.thecvf.com/content_iccv_2015/html/Ikehata_Structured_Indoor_Modeling_ICCV_2015_paper.html,ICCV,2015,https://github.com/furukawa00000/2015_structured_indoor_modeling,0,1/2/2019 +Actions and Attributes From Wholes and Parts,http://openaccess.thecvf.com/content_iccv_2015/html/Gkioxari_Actions_and_Attributes_ICCV_2015_paper.html,ICCV,2015,https://github.com/frankmalcolmkembery/GNU-GENERAL-PUBLIC-LICENSE-Version-3-29-June-2007-Copy,0,1/2/2019 +Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes,http://openaccess.thecvf.com/content_ECCV_2018/html/Fangneng_Zhan_Verisimilar_Image_Synthesis_ECCV_2018_paper.html,ECCV,2018,https://github.com/fnzhan/Verisimilar-Image-Synthesis-for-Accurate-Detection-and-Recognition-of-Texts-in-Scenes,24,1/2/2019 +Human Pose Estimation in Videos,http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Human_Pose_Estimation_ICCV_2015_paper.html,ICCV,2015,https://github.com/FJR-Nancy/TS-LSTM,0,1/2/2019 +Maximum Persistency via Iterative Relaxed Inference With Graphical Models,http://openaccess.thecvf.com/content_cvpr_2015/html/Shekhovtsov_Maximum_Persistency_via_2015_CVPR_paper.html,CVPR,2015,https://github.com/fgrsnau/part_opt,0,1/2/2019 +Density Adaptive Point Set Registration,http://openaccess.thecvf.com/content_cvpr_2018/papers/Lawin_Density_Adaptive_Point_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/felja633/DARE,9,1/2/2019 +Scale-Aware Face Detection,http://openaccess.thecvf.com/content_cvpr_2017/html/Hao_Scale-Aware_Face_Detection_CVPR_2017_paper.html,CVPR,2017,https://github.com/eugenelet/Scale-Aware-Face-Detection,0,1/2/2019 +Hamiltonian Variational Auto-Encoder,,NIPS,2018,https://github.com/ericZYZ/HVI-RMHVI-for-VAE,0,1/2/2019 +Adaptive Sampling Probabilities for Non-Smooth Optimization,http://proceedings.mlr.press/v70/namkoong17a.html,ICML,2017,https://github.com/duchi-lab/adaptive-sampling-descent,2,1/2/2019 +Extending Layered Models to 3D Motion,http://openaccess.thecvf.com/content_ECCV_2018/html/Dong_Lao_Extending_Layered_Models_ECCV_2018_paper.html,ECCV,2018,https://github.com/donglao/layers3Dmotion,0,1/2/2019 +Forest-type Regression with General Losses and Robust Forest,http://proceedings.mlr.press/v70/li17e.html,ICML,2017,https://github.com/dma092/Forest-type-Regression-with-General-Losses-and-Robust-Forest-an-implementation,0,1/2/2019 +Beyond the Pixel-Wise Loss for Topology-Aware Delineation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Mosinska_Beyond_the_Pixel-Wise_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/dingmyu/Pytorch-Topology-Aware-Delineation,0,1/2/2019 +The Stitched Puppet: A Graphical Model of 3D Human Shape and Pose,http://openaccess.thecvf.com/content_cvpr_2015/html/Zuffi_The_Stitched_Puppet_2015_CVPR_paper.html,CVPR,2015,https://github.com/despicableMinions/stitched-puppet,0,1/2/2019 +"Cut, Glue & Cut: A Fast, Approximate Solver for Multicut Partitioning",http://openaccess.thecvf.com/content_cvpr_2014/html/Beier_Cut_Glue__2014_CVPR_paper.html,CVPR,2014,https://github.com/danoan/GCCS,0,1/2/2019 +Effective Face Frontalization in Unconstrained Images,http://openaccess.thecvf.com/content_cvpr_2015/html/Hassner_Effective_Face_Frontalization_2015_CVPR_paper.html,CVPR,2015,https://github.com/daemonlair/face-frontalization,0,1/2/2019 +Light Field Intrinsics With a Deep Encoder-Decoder Network,http://openaccess.thecvf.com/content_cvpr_2018/papers/Alperovich_Light_Field_Intrinsics_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/cvia-kn/lf_autoencoder_cvpr2018_code,0,1/2/2019 +Reconfiguring the Imaging Pipeline for Computer Vision,http://openaccess.thecvf.com/content_iccv_2017/html/Buckler_Reconfiguring_the_Imaging_ICCV_2017_paper.html,ICCV,2017,https://github.com/cucapra/vision-plots,0,1/2/2019 +A Holistic Approach to Cross-Channel Image Noise Modeling and Its Application to Image Denoising,http://openaccess.thecvf.com/content_cvpr_2016/html/Nam_A_Holistic_Approach_CVPR_2016_paper.html,CVPR,2016,https://github.com/csjunxu/ccnoise_code_CVPR2016,0,1/2/2019 +A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models,http://proceedings.mlr.press/v80/wang18f.html,ICML,2018,https://github.com/cran/jeek,0,1/2/2019 +Latent Feature Lasso,http://proceedings.mlr.press/v70/yen17a.html,ICML,2017,https://github.com/cran/FLLat,0,1/2/2019 +Bayesian Nonparametric Spectral Estimation,,NIPS,2018,https://github.com/cran/bsplinePsd,0,1/2/2019 +A Linear Generalized Camera Calibration From Three Intersecting Reference Planes,http://openaccess.thecvf.com/content_iccv_2015/html/Nishimura_A_Linear_Generalized_ICCV_2015_paper.html,ICCV,2015,https://github.com/computer-vision/iccv2015,0,1/2/2019 +A Linear Extrinsic Calibration of Kaleidoscopic Imaging System From Single 3D Point,http://openaccess.thecvf.com/content_cvpr_2017/html/Takahashi_A_Linear_Extrinsic_CVPR_2017_paper.html,CVPR,2017,https://github.com/computer-vision/cvpr2017,0,1/2/2019 +ML-MG: Multi-Label Learning With Missing Labels Using a Mixed Graph,http://openaccess.thecvf.com/content_iccv_2015/html/Wu_ML-MG_Multi-Label_Learning_ICCV_2015_paper.html,ICCV,2015,https://github.com/CoderZWei/Multi-label,0,1/2/2019 +Extreme Learning to Rank via Low Rank Assumption,http://proceedings.mlr.press/v80/cheng18a.html,ICML,2018,https://github.com/cmhcbb/Extreme-learning-to-rank-via-low-rank-assumption,0,1/2/2019 +Hierarchical Recurrent Neural Network for Skeleton Based Action Recognition,http://openaccess.thecvf.com/content_cvpr_2015/html/Du_Hierarchical_Recurrent_Neural_2015_CVPR_paper.html,CVPR,2015,https://github.com/chrisjkim/hierarchical-recurrent-neural-network-for-skeleton-based-action-recognition,0,1/2/2019 +A Stable Multi-Scale Kernel for Topological Machine Learning,http://openaccess.thecvf.com/content_cvpr_2015/html/Reininghaus_A_Stable_Multi-Scale_2015_CVPR_paper.html,CVPR,2015,https://github.com/chocojoX/Kernel_for_TDAML,0,1/2/2019 +Fine-Grained Recognition Without Part Annotations,http://openaccess.thecvf.com/content_cvpr_2015/html/Krause_Fine-Grained_Recognition_Without_2015_CVPR_paper.html,CVPR,2015,https://github.com/chenlongcv/OVSNet,0,1/2/2019 +What are You Talking About? Text-to-Image Coreference,http://openaccess.thecvf.com/content_cvpr_2014/html/Kong_What_are_You_2014_CVPR_paper.html,CVPR,2014,https://github.com/chagge/sentences3D,0,1/2/2019 +Cross-View Image Matching for Geo-Localization in Urban Environments,http://openaccess.thecvf.com/content_cvpr_2017/html/Tian_Cross-View_Image_Matching_CVPR_2017_paper.html,CVPR,2017,https://github.com/cc1164/Cross-View-Image-Matching-for-Geo-localization-in-Urban-Environments,0,1/2/2019 +Deep Shape Matching,http://openaccess.thecvf.com/content_ECCV_2018/html/Filip_Radenovic_Deep_Shape_Matching_ECCV_2018_paper.html,ECCV,2018,https://github.com/CaramelYo/shape_matching_with_deep_learning,0,1/2/2019 +Seeing the Arrow of Time,http://openaccess.thecvf.com/content_cvpr_2014/html/Pickup_Seeing_the_Arrow_2014_CVPR_paper.html,CVPR,2014,https://github.com/BoeingX/seeing-the-arrow-of-time,0,1/2/2019 +Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification,http://papers.nips.cc/paper/7004-aggressive-sampling-for-multi-class-to-binary-reduction-with-applications-to-text-classification.pdf,NIPS,2017,https://github.com/bikash617/Aggressive-Sampling-for-Multi-class-to-BinaryReduction,0,1/2/2019 +An Analysis of Visual Question Answering Algorithms,http://openaccess.thecvf.com/content_iccv_2017/html/Kafle_An_Analysis_of_ICCV_2017_paper.html,ICCV,2017,https://github.com/bigman911/Project,0,1/2/2019 +A Boo(n) for Evaluating Architecture Performance,http://proceedings.mlr.press/v80/bajgar18a.html,ICML,2018,https://github.com/bajgar/Boon,0,1/2/2019 +Deep Reinforcement Learning-Based Image Captioning With Embedding Reward,http://openaccess.thecvf.com/content_cvpr_2017/html/Ren_Deep_Reinforcement_Learning-Based_CVPR_2017_paper.html,CVPR,2017,https://github.com/B3-348/DRL-based-Image-Captioning-with-Embedding-Reward,0,1/2/2019 +Interval Tracker: Tracking by Interval Analysis,http://openaccess.thecvf.com/content_cvpr_2014/html/Kwon_Interval_Tracker_Tracking_2014_CVPR_paper.html,CVPR,2014,https://github.com/atanu1982/Major-HIPAA-Survival-Guide,0,1/2/2019 +Webly Supervised Semantic Segmentation,http://openaccess.thecvf.com/content_cvpr_2017/html/Jin_Webly_Supervised_Semantic_CVPR_2017_paper.html,CVPR,2017,https://github.com/ascust/WSS,0,1/2/2019 +Image to Image Translation for Domain Adaptation,http://openaccess.thecvf.com/content_cvpr_2018/papers/Murez_Image_to_Image_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/artix41/ai-week-talk,0,1/2/2019 +Using Object Information for Spotting Text,http://openaccess.thecvf.com/content_ECCV_2018/html/Shitala_Prasad_Using_Object_Information_ECCV_2018_paper.html,ECCV,2018,https://github.com/arjun1237/Inheritance---Java,0,1/2/2019 +A Universal Analysis of Large-Scale Regularized Least Squares Solutions,http://papers.nips.cc/paper/6930-a-universal-analysis-of-large-scale-regularized-least-squares-solutions.pdf,NIPS,2017,https://github.com/apanahi/NIPS_Paper_1937,0,1/2/2019 +Fast Light Field Reconstruction With Deep Coarse-To-Fine Modeling of Spatial-Angular Clues,http://openaccess.thecvf.com/content_ECCV_2018/html/Henry_W._F._Yeung_Fast_Light_Field_ECCV_2018_paper.html,ECCV,2018,https://github.com/angularsr/LightFieldAngularSR,2,1/2/2019 +A Dataset for Movie Description,http://openaccess.thecvf.com/content_cvpr_2015/html/Rohrbach_A_Dataset_for_2015_CVPR_paper.html,CVPR,2015,https://github.com/aminanima/MovieProject,0,1/2/2019 +Feature Generating Networks for Zero-Shot Learning,http://openaccess.thecvf.com/content_cvpr_2018/papers/Xian_Feature_Generating_Networks_CVPR_2018_paper.pdf,CVPR,2018,https://github.com/akku1506/Feature-Generating-Networks-for-ZSL,3,1/2/2019 +AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel 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