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Gortler, Todd Zickler", "aff": "Harvard University", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Heal_A_Lighting-Invariant_Point_Processor_for_Shading_CVPR_2020_paper.html", "arxiv": "" }, { "title": "A Local-to-Global Approach to Multi-Modal Movie Scene Segmentation", "status": "Poster", "site": "", "track": "main", "project": "https://anyirao.com/projects/SceneSeg.html", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Rao_A_Local-to-Global_Approach_to_Multi-Modal_Movie_Scene_Segmentation_CVPR_2020_paper.pdf", "youtube": "", "author": "Anyi Rao, Linning Xu, Yu Xiong, Guodong Xu, Qingqiu Huang, Bolei Zhou, Dahua Lin", "aff": "The Chinese University of Hong Kong, Shenzhen; CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Rao_A_Local-to-Global_Approach_to_Multi-Modal_Movie_Scene_Segmentation_CVPR_2020_paper.html", "arxiv": "2004.02678" }, { "title": "A Model-Driven Deep Neural Network for Single Image Rain Removal", "status": "Poster", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_A_Model-Driven_Deep_Neural_Network_for_Single_Image_Rain_Removal_CVPR_2020_paper.pdf", "youtube": "", "author": "Hong Wang, Qi Xie, Qian Zhao, Deyu Meng", "aff": "Xi\u2019an Jiaotong University; Macau University of Science and Technology", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Wang_A_Model-Driven_Deep_Neural_Network_for_Single_Image_Rain_Removal_CVPR_2020_paper.html", "arxiv": "2005.01333" }, { "title": "A Morphable Face Albedo Model", "status": "Oral", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Smith_A_Morphable_Face_Albedo_Model_CVPR_2020_paper.pdf", "youtube": "", "author": "William A. 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National University of Singapore; Huawei Noah\u2019s Ark Lab", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Yuan_Central_Similarity_Quantization_for_Efficient_Image_and_Video_Retrieval_CVPR_2020_paper.html", "arxiv": "1908.00347" }, { "title": "CentripetalNet: Pursuing High-Quality Keypoint Pairs for Object Detection", "status": "Poster", "site": "", "track": "main", "project": "", "github": "https://github.com/KiveeDong/CentripetalNet", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Dong_CentripetalNet_Pursuing_High-Quality_Keypoint_Pairs_for_Object_Detection_CVPR_2020_paper.pdf", "youtube": "", "author": "Zhiwei Dong, Guoxuan Li, Yue Liao, Fei Wang, Pengju Ren, Chen Qian", "aff": "SenseTime Research; University of Chinese Academy of Sciences; Beihang University; Institute of Arti\ufb01cial Intelligence and Robotics, Xi\u2019an Jiaotong University", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Dong_CentripetalNet_Pursuing_High-Quality_Keypoint_Pairs_for_Object_Detection_CVPR_2020_paper.html", "arxiv": "2003.09119" }, { "title": "Channel Attention Based Iterative Residual Learning for Depth Map Super-Resolution", "status": "Poster", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Song_Channel_Attention_Based_Iterative_Residual_Learning_for_Depth_Map_Super-Resolution_CVPR_2020_paper.pdf", "youtube": "", "author": "Xibin Song, Yuchao Dai, Dingfu Zhou, Liu Liu, Wei Li, Hongdong Li, Ruigang Yang", "aff": "Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, China; Shandong University, China; Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, China, University of Kentucky, Kentucky, USA; Australian National University, Australia, Australian Centre for Robotic Vision, Australia; Northwestern Polytechnical University, China", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Song_Channel_Attention_Based_Iterative_Residual_Learning_for_Depth_Map_Super-Resolution_CVPR_2020_paper.html", "arxiv": "2006.01469" }, { "title": "Circle Loss: A Unified Perspective of Pair Similarity Optimization", "status": "Oral", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Sun_Circle_Loss_A_Unified_Perspective_of_Pair_Similarity_Optimization_CVPR_2020_paper.pdf", "youtube": "", "author": "Yifan Sun, Changmao Cheng, Yuhan Zhang, Chi Zhang, Liang Zheng, Zhongdao Wang, Yichen Wei", "aff": "Australian National University; Beihang University; MEGVII Technology; 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Info. Process., Inst. of Comput. Tech., CAS, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; Kingsoft Cloud, Beijing, China; Key Lab of Intell. Info. Process., Inst. of Comput. 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Tang was at MPI-IS and University of T\u00fcbingen); Max Planck Institute for Informatics, Saarland Informatics Campus, Germany; Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany and University of T\u00fcbingen, Germany", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Ma_Learning_to_Dress_3D_People_in_Generative_Clothing_CVPR_2020_paper.html", "arxiv": "1907.13615" }, { "title": "Learning to Evaluate Perception Models Using Planner-Centric Metrics", "status": "Poster", "site": "", "track": "main", "project": "https://nv-tlabs.github.io/detection-relevance", "github": "https://github.com/nv-tlabs/detection-relevance", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Philion_Learning_to_Evaluate_Perception_Models_Using_Planner-Centric_Metrics_CVPR_2020_paper.pdf", "youtube": "", "author": "Jonah Philion, Amlan Kar, Sanja Fidler", "aff": "University of Toronto Vector Institute; NVIDIA", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Philion_Learning_to_Evaluate_Perception_Models_Using_Planner-Centric_Metrics_CVPR_2020_paper.html", "arxiv": "2004.08745" }, { "title": "Learning to Forget for Meta-Learning", "status": "Poster", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Baik_Learning_to_Forget_for_Meta-Learning_CVPR_2020_paper.pdf", "youtube": "", "author": "Sungyong Baik, Seokil Hong, Kyoung Mu Lee", "aff": "ASRI, Department of ECE, Seoul National University", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Baik_Learning_to_Forget_for_Meta-Learning_CVPR_2020_paper.html", "arxiv": "1906.05895" }, { "title": "Learning to Generate 3D Training Data Through Hybrid Gradient", "status": "Poster", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Yang_Learning_to_Generate_3D_Training_Data_Through_Hybrid_Gradient_CVPR_2020_paper.pdf", "youtube": "", "author": "Dawei Yang, Jia Deng", "aff": "Princeton University; 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Grenoble Alpes, CNRS, Grenoble INP, LJK; ETH Z \u00a8urich, Microsoft; Microsoft; Inria, D\u00b4epartement d\u2019informatique de l\u2019ENS, CNRS, PSL Research University", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Hasson_Leveraging_Photometric_Consistency_Over_Time_for_Sparsely_Supervised_Hand-Object_Reconstruction_CVPR_2020_paper.html", "arxiv": "2004.13449" }, { "title": "LiDAR-Based Online 3D Video Object Detection With Graph-Based Message Passing and Spatiotemporal Transformer Attention", "status": "Poster", "site": "", "track": "main", "project": "", "github": "https://github.com/yinjunbo/3DVID", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Yin_LiDAR-Based_Online_3D_Video_Object_Detection_With_Graph-Based_Message_Passing_CVPR_2020_paper.pdf", "youtube": "", "author": "Junbo Yin, Jianbing Shen, Chenye Guan, Dingfu Zhou, Ruigang Yang", "aff": "Inception Institute of Arti\ufb01cial Intelligence, UAE; Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, China; Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, China; Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, University of Kentucky, Kentucky, USA", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Yin_LiDAR-Based_Online_3D_Video_Object_Detection_With_Graph-Based_Message_Passing_CVPR_2020_paper.html", "arxiv": "2004.01389" }, { "title": "LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World", "status": "Oral", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Manivasagam_LiDARsim_Realistic_LiDAR_Simulation_by_Leveraging_the_Real_World_CVPR_2020_paper.pdf", "youtube": "", "author": "Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Shuhan Tan, Bin Yang, Wei-Chiu Ma, Raquel Urtasun", "aff": "Uber Advanced Technologies Group, University of Toronto; Uber Advanced Technologies Group; Uber Advanced Technologies Group, Massachusetts Institute of Techonology", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Manivasagam_LiDARsim_Realistic_LiDAR_Simulation_by_Leveraging_the_Real_World_CVPR_2020_paper.html", "arxiv": "2006.09348" }, { "title": "Light Field Spatial Super-Resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization", "status": "Poster", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Jin_Light_Field_Spatial_Super-Resolution_via_Deep_Combinatorial_Geometry_Embedding_and_CVPR_2020_paper.pdf", "youtube": "", "author": "Jing Jin, Junhui Hou, Jie Chen, Sam Kwong", "aff": "Hong Kong Baptist University; City University of Hong Kong", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Jin_Light_Field_Spatial_Super-Resolution_via_Deep_Combinatorial_Geometry_Embedding_and_CVPR_2020_paper.html", "arxiv": "2004.02215" }, { "title": "Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation", "status": "Poster", "site": "", "track": "main", "project": "", "github": "https://github.com/yeshaokai/Calibrator-Domain-Adaptation", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Ye_Light-weight_Calibrator_A_Separable_Component_for_Unsupervised_Domain_Adaptation_CVPR_2020_paper.pdf", "youtube": "", "author": "Shaokai Ye, Kailu Wu, Mu Zhou, Yunfei Yang, Sia Huat Tan, Kaidi Xu, Jiebo Song, Chenglong Bao, Kaisheng Ma", "aff": "Institute for interdisciplinary information core technology(IIISCT), China; Tsinghua University, China; University of Tsukuba, Japan; Northeastern University, USA", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Ye_Light-weight_Calibrator_A_Separable_Component_for_Unsupervised_Domain_Adaptation_CVPR_2020_paper.html", "arxiv": "1911.12796" }, { "title": "Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination", "status": "Poster", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Srinivasan_Lighthouse_Predicting_Lighting_Volumes_for_Spatially-Coherent_Illumination_CVPR_2020_paper.pdf", "youtube": "", "author": "Pratul P. 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Carreira-Perpi\u00f1\u00e1n", "aff": "Dept. 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CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Zhan_Self-Supervised_Scene_De-Occlusion_CVPR_2020_paper.html", "arxiv": "2004.02788" }, { "title": "Self-Supervised Viewpoint Learning From Image Collections", "status": "Poster", "site": "", "track": "main", "project": "", "github": "https://github.com/NVlabs/SSV", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Mustikovela_Self-Supervised_Viewpoint_Learning_From_Image_Collections_CVPR_2020_paper.pdf", "youtube": "", "author": "Siva Karthik Mustikovela, Varun Jampani, Shalini De Mello, Sifei Liu, Umar Iqbal, Carsten Rother, Jan Kautz", "aff": "NVIDIA, Heidelberg University; Heidelberg University; NVIDIA", "oa": "https://openaccess.thecvf.com/content_CVPR_2020/html/Mustikovela_Self-Supervised_Viewpoint_Learning_From_Image_Collections_CVPR_2020_paper.html", "arxiv": "2004.01793" }, { "title": "Self-Trained Deep Ordinal Regression for End-to-End Video Anomaly Detection", "status": "Poster", "site": "", "track": "main", "project": "", "github": "", "pdf": "https://openaccess.thecvf.com/content_CVPR_2020/papers/Pang_Self-Trained_Deep_Ordinal_Regression_for_End-to-End_Video_Anomaly_Detection_CVPR_2020_paper.pdf", "youtube": "", "author": "Guansong Pang, Cheng Yan, Chunhua Shen, Anton van den Hengel, Xiao Bai", "aff": "Beihang University, China; 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