ECCV 2012 List of accepted papers

图像处理和计算机视觉中的经典论文(部分) 自己视野狭小,不敢说全部,只是把自己熟悉的方向中的部分经典文章列出来了。经典的论文,读得怎么透都不过分。有人说关于配准的文章太多了,其实我也不太关注这方面,不过由于它们引用率都比较高,就都列出来了,不过在zip包里一篇都没有。不关注这方面的可以无视之。 文档和论文下载地址: http://iask.sina.com.cn/u/2252291285/ish?folderid=775855 阅读详情

Oral presentation

 oral出来了,只有40篇文章,录取率只有大概2.3%。先Mark一下,等出来后选感兴趣的看几篇

Paper id Paper title Author names
13 Diverse M-Best Solutions in Markov Random Fields Dhruv Batra*, Toyota Technological Institute at Chicago (TTIC) ; Payman Yadollahpour, TTIC; Abner Guzman-Rivera, UIUC; Greg Shakhnarovich, TTIC
17 Attributes for classifier feedback Amar Prakash, IIIT-D; Devi Parikh*, TTIC
85 Reconstructing the World’s Museums Jianxiong Xiao*, MIT; Yasutaka Furukawa, Google
100 Frequency-Space Decomposition and Acquisition of Light Transport under Spatially Varying Illumination Dikpal Reddy*, UC Berkeley; Ravi Ramamoorthi, ; Brian Curless,
127 Metric Learning for Large Scale Image Classification: Generalizing to New Classes at Near-Zero Cost Thomas Mensink*, INRIA Rhone Alpes; Jakob Verbeek, ; Gabriela Csurka, XRCE; Florent Perronnin, XRCE
150 Segmentation Propagation in ImageNet Daniel Kuettel*, ETH Zurich; Matthieu Guillaumin, ETH Zürich; Vittorio Ferrari,
152 A Unified Framework for Multi-Target Tracking and Collective Activity Recognition Wongun Choi*, The University of Michigan; Silvio Savarese, The University of Michigan, Ann Arbor
175 Exact Acceleration of Linear Object Detectors Charles Dubout*, Idiap; François Fleuret, Idiap
214 Shape Sharing for Object Segmentation Jaechul Kim*, University of Texas at Austin; Kristen Grauman,
236 Activity Forecasting Kris Kitani*, Carnegie Mellon University; James Bagnell, ; Martial Hebert,
276 Action Recognition with Exemplar Based 2.5D Graph Matching Bangpeng Yao*, Stanford University; Li Fei-fei,
331 People Watching: Human Actions as a Cue for Single View Geometry David Fouhey*, Carnegie Mellon University; Vincent Delaitre, ; Alyosha Efros, CMU; Abhinav Gupta, ; Ivan Laptev, ; Josef Sivic, INRIA / Ecole Normale Superieure
354 Depth Extraction from Video Using Non-parametric Sampling Kevin Karsch*, UIUC; Ce Liu, Microsoft Research New England; Sing Bing Kang, Microsoft Research
405 Constrained Bootstrapping for Image Classification via Attributes and Comparative Attributes Abhinav Shrivastava*, Carnegie Mellon University; Saurabh Singh, Carnegie Mellon University; Abhinav Gupta, Carnegie Mellon University
440 “Clustering by Composition” for Unsupervised Discovery of Image Categories Michal Irani; Alon Faktor
708 Detecting and Localizing Activities at Different Scales under Budget Mohamed Amer*, Oregon State University; Dan Xie, UCLA; Mingtian Zhao , UCLA; Yaofei Feng, OREGON STATE UNIVERSITY; Behrooz Mahasseni, OREGON STATE UNIVERSITY; Sinisa Todorovic, Oregon State University; Song-Chun Zhu, UCLA
811 Latent Hough Transform for Object Detection Nima Razavi*, ETH Zurich; Juergen Gall, ETH Zurich; Pushmeet Kohli, ; Luc Van Gool,
848 A QCQP Approach to Triangulation Chris Aholt*, University of Washington; Sameer Agarwal, Google; Rekha Thomas, University of Washington
866 Recognizing Actions, Poses, and Objects with Relational Phraselets Chaitanya Desai*, University of California Irvine; Deva Ramanan,
880 Generic Cuts: An Efficient Optimal Algorithm for Submodular MRF-MAP Problems with Higher Order Cliques Chetan Arora*, IIT Delhi; Subhashis Banerjee, IIT Delhi; Prem Kalra, IIT Delhi; S.N. Maheshwari, IIT Delhi
959 A Three-Layered Approach to Facade Parsing Andelo Martinovic*, KU Leuven; Markus Mathias, KU Leuven; Julien Weissenberg, ETHZ; Luc Van Gool, KU Leuven
981 Multiple View Object Cosegmentation using Appearance and Stereo Cues Adarsh Kowdle*, Cornell University; Sudipta Sinha, ; Rick Szeliski,
1024 Using linking features in learning non-parametric part models Leonid Karlinsky*, Weizmann Institute of Science; Shimon Ullman, Weizmann Institute of Science
1035 Patch Complexity, Finite Pixel Correlations and Optimal Denoising Anat Levin*, Weizmann Institute; Boaz Nadler, Weizmann Inst; Fredo Durand, MIT; William Freeman, Massachusetts Institute of Technology
1051 Filter-based Mean-Field Inference for Random Fields with Higher Order Terms and Product Label-Spaces Jonathan Warrell*, Oxford Brookes University; Phil Torr, ; Vibhav Vineet, Oxford Brookes University
1071 Good Regions to Deblur Zhe Hu*, UC Merced; Ming-Hsuan Yang, University of California at Merced
1079 Indoor Segmentation and Support Inference from RGBD Images Nathan Silberman*, NYU; Rob Fergus, ; Derek Hoiem, UIUC; Pushmeet Kohli,
1110 Reflectance and Natural Illumination from a Single Image Stephen Lombardi*, Drexel University; Ko Nishino, Drexel University
1171 Diagnosing Error in Object Detectors Derek Hoiem*, University of Illinois; Yodsawalai Chodpathumwan, University of Illinois; Qieyun Dai, University of Illinois
1181 A Naturalistic Open Source Movie for Optical Flow Evaluation Daniel Butler*, University of Washington; Jonas Wulff, Max Planck Institute for Intelligent Systems; Garrett Stanley, Department of Biomedical Engineering, Georgia Institute of Technology; Michael Black, Max Planck Institute for Intelligent Systems
1243 Efficient Optimization For Low-Rank Integrated Bilinear Classifiers Takumi Kobayashi*, National Institute of AIST; Nobuyuki Otsu,
1258 PlantID: A Computer Vision System for Automatic Plant Species Identification Neeraj Kumar*, University of Washington; David Jacobs, ; Peter Belhumeur, Columbia University; Arijit Biswas, University of Maryland; Joao Soares, University of Maryland
1330 Semantic Segmentation with Second-Order Pooling Joao Carreira*, University of Coimbra; Rui Caseiro, Institute Systems Robotics; Jorge Batista, Institute Systems Robotics – University Coimbra – Portugal; Cristian Sminchisescu, University of Bonn
1383 Photo-Sequencing Tali Basha*, Tel Aviv University; Shai Avidan, ; Yael Moses, IDC
1422 Continuous Markov Random Fields for Robust Stereo Estimation Koichiro Yamaguchi, TTI Chicago; Tamir Hazan, TTI Chicago; David McAllester, TTI Chicago; Raquel Urtasun*, TTIC
1429 Fourier Kernel Learning Eduard-Gabriel Bazavan*, IMAR; Fuxin Li, Georgia Inst. of Tech.; Cristian Sminchisescu, University of Bonn
1436 Large Scale Visual Geo-Localization of Images in Mountainous Terrain Georges Baatz*, ETHZ; Olivier Saurer, ETHZ; Kevin Koeser, ETHZ; Marc Pollefeys,
1543 Streaming Hierarchical Video Segmentation Chenliang Xu, SUNY at Buffalo; Caiming Xiong, SUNY at Buffalo; Jason Corso*, SUNY at Buffalo
1619 Motion Capture of Hands in Action using Discriminative Salient Points Luca Ballan*, ETH Zurich; Aparna Taneja, ETH Zurich; Juergen Gall, ETH Zurich; Luc Van Gool, ; Marc Pollefeys,
1707 Beyond the line of sight: labeling the underlying surfaces

还看不出谁是oral,谁是poster,也没有查到oral录取率和总录取率。粗略数了数,录取率大概是410/1712=23.9%(总篇数用最后一篇的序号来估算)。无聊统计了一下,录取的前100篇对应的录取率是100/376=26.6%,前200篇对应的录取率是200/816=24.5%,前300篇对应的录取率是300/1176=25.5%。这也说明,投稿先后对录取没什么影响^_^



Paper ID Paper Title Author Names
1 Semi-Intrinsic Mean shift on Riemannian Manifolds Rui Caseiro*, Institute Systems Robotics; Jo„o F Henriques, ISR; PedroMartins, ISR; Jorge Batista, Institute Systems Robotics – University Coimbra- Portugal
5 Online Learning of Linear Predictors for Real-Time Tracking Stefan Holzer*, Technische Universität München; Marc Pollefeys;Slobodan Ilic, TUM; David Joseph Tan, Technische Universität München; NassirNavab, Technische Universität München
6 Learning to Efficiently Detect Repeatable Interest Points in Depth Data Stefan Holzer*, Technische Universität München; Jamie Shotton, MicrosoftResearch Cambridge; Pushmeet Kohli 
10 Effective Use of Frequent Itemset Mining for Image Classification Basura Fernando*, K.U. Leuven; Elisa Fromont, University Jean MonnetSaint Etienne France; Tinne Tuytelaars 
13 M-Best Modes Payman Yadollahpour, TTIC; Dhruv Batra*, Toyota Technological Instituteat Chicago (TTIC) ; Abner Guzman-Rivera, UIUC; Greg Shakhnarovich, TTIC
17 Attributes for classifier feedback Amar Prakash, IIIT-D; Devi Parikh*, TTIC
21 Lie Bodies: A Manifold Representation of 3D Human Shape Oren Freifeld*, Brown University; Michael Black, Max Planck Institute forIntelligent Systems
25 Modeling Complex Temporal Composition of Actionlets for ActivityPrediction Kang Li; Jie Hu, State University of New York (SUNY) at Buffalo; YunFu*, SUNY at Buffalo
35 Object Co-detection Yinzge Bao*, U of Michigan at Ann Arbor; Yu Xiang, University ofMichigan; Silvio Savarese, The University of Michigan, Ann Arbor
41 What Do You Do: Occupation Recognition in a Photo Ming Shao*; Liangyue Li, SUNY at Buffalo; Yun Fu, SUNY at Buffalo
46 Shape and Material Under Natural Illumination Geoffrey Oxholm*, Drexel University; Ko Nishino, Drexel University
47 Efficient Discriminative Projections for Compact Binary Descriptors Tomasz Trzcinski*, EPFL; Vincent Lepetit 
57 Efficient Nonlocal Regularization for Optical Flow Philipp Krähenb¸hl*, Stanford University; Vladlen Koltun, StanfordUniversity
64 Morphable Displacement Field based Image Matching for Face RecognitionAcross Pose shaoxin Li*, ICT, CAS; xin Liu, Institute of Computing Chinese Academy ofScience; Xiujuan Chai, ICT,CAS; Haihong Zhang, Omron; Shihong Lao, Omron;Shiguang Shan, ICT, CAS
70 Frequency Analysis of Transient Light Transport with Applications in BareSensor Imaging Di Wu, MIT Media Lab; GordonWetzstein*, MIT Media Lab; Christopher Barsi, MIT Media Lab; ThomasWillwacher, Harvard University; Matthew O’Toole, University of Toronto;Nikhil Naik, MIT Media Lab; Qionghai Dai, Tsinghua University; KyrosKutulakos; Ramesh Raskar, MIT Media Lab
82 Descriptor Learning Revisited Karen Simonyan*, University of Oxford; Andrea Vedaldi, Oxford U; AndrewZisserman 
85 Reconstructing the World’s Museums Jianxiong Xiao*, MIT; Yasutaka Furukawa, Google
86 Online Learned Discriminative Part-Based Appearance Models forMulti-Human Tracking Bo Yang*, USC; Ram Nevatia 
87 A New Combinatorial Algorithm with Applications in Multi-Model Estimation Andrew Delong*, University of Western Ontario; Olga Veksler, Universityof Western Ontario; Yuri Boykov, University of Western Ontario
88 Segmentation with non-linear regional constraints via line-search cuts Lena Gorelick*, UWO; Frank Schmidt, ESIEE; Yuri Boykov, University ofWestern Ontario; Andrew Delong, University of Western Ontario; Aaron Ward,UWO
97 Hausdorff Distance Constraint for Multi-Surface Segmentation Frank Schmidt*, ESIEE; Yuri Boykov, University of Western Ontario
98 Background Subtraction using Group Sparsity and Low Rank constraint Xinyi Cui*, Rutgers University; Junzhou Huang; shaoting Zhang, RutgersUniversity; Dimitris Metaxas, Rutgers University
99 Exposure Stacks of Live Scenes with Hand-held Cameras Jun Hu, Duke University; Orazio Gallo*, NVIDIA, Corp.; Kari Pulli, NVIDIAResearch
100 Frequency-Space Decomposition and Acquisition of Light Transport underSpatially Varying Illumination Dikpal Reddy*, UC Berkeley; Ravi Ramamoorthi; Brian Curless 
107 Worldwide Pose Estimation Using 3D Point Cloud Models Yunpeng Li*, EPFL; Noah Snavely, Cornell University; Daniel Huttenlocher,; Pascal Fua, EPFL
108 Combining Per-Frame and Per-Track Cues for Multi-Person ActionRecognition Sameh Khamis*, University of Maryland; Vlad Morariu, University ofMaryland; Larry Davis, University of Maryland
111 A graph cut algorithm based on approximating the signed bi-form graph Alex Fix, Cornell; Joyce Chen, Cornell; Endre Boros, Rutgers; RaminZabih* 
113 Recursive Bilateral Filtering Qingxiong Yang*, City University of Hong Kong
115 Accelerated Large-Scale Optimization by Concomitant Hashing Yadong Mu*, Columbia University; John Wright, Columbia University;Shih-Fu Chang, Columbia
118 Graph Degree Linkage: Agglomerative Clustering on a Directed Graph Wei Zhang*, CUHK; Xiaogang Wang, The Chinese University of HK; Deli Zhao,CUHK; Xiaoou Tang 
120 Joint Image and Word Sense Discrimination For Image Retrieval Aurelien Lucchi*, EPFL; Jason Weston, google
122 Supervised Earth Mover’s Distance Learning and Its Computer VisionApplications Fan Wang*, Stanford University; Leonidas Guibas, Stanford University
127 Metric Learning for Large Scale Image Classification: Generalizing to NewClasses at Near-Zero Cost Thomas Mensink*, INRIA Rhone Alpes; Jakob Verbeek; Gabriela Csurka,XRCE; Florent Perronnin, XRCE
128 Knowledge-Oriented Sketch Segmentation Zhenbang Sun*, Shanghai Jiao Tong University; Changhu Wang, MicrosoftResearch Asia; Liqing Zhang, Shanghai Jiao Tong University; Lei Zhang, MSRA
135 Global Optimization of Object Pose and Motion from a Single RollingShutter Image with Automatic 2D-3D Matching Ludovic MAGERAND*, Clermont-UniversitÈ
136 Script Data for Attribute-based Recognition of Composite Activities Marcus Rohrbach*, MPI Informatics; Michaela Regneri, Saarland University;Mykhaylo Andriluka, MPI Informatik; Sikandar Amin, Max-Planck, TU Munich;Manfred Pinkal; Bernt Schiele 
141 Auto-grouped Sparse Representation for Visual Analysis Jiashi Feng*, NUS; Xiaotong Yuan; zilei Wang; Huan Xu; ShuichengYan 
145 Dual-force Metric Learning for Robust Distractor Resistant Tracker Zhibin Hong*, University of Technology, Sydn
149 Undoing the Damage of Dataset Bias Aditya Khosla*, MIT; Tinghui Zhou, CMU; Tomasz Malisiewicz, MIT; AlyoshaEfros, CMU; Antonio Torralba, MIT
150 Segmentation Propagation in ImageNet Daniel Kuettel*, ETH Zurich; Matthieu Guillaumin, ETH Z¸rich; VittorioFerrari 
151 Improved Reconstruction of Deforming Surfaces by Cancelling AmbientOcclusion Thabo Beeler, ETH; Derek Bradley*, Disney Research Zurich; HenningZimmer, ETH Zurich; Markus Gross, ETH Zurich
152 A Unified Framework for Multi-Target Tracking and Collective ActivityRecognition Wongun Choi*, The University of Michigan; Silvio Savarese, The Universityof Michigan, Ann Arbor
157 Dog Breed Classi?cation Using Part Localization Jiongxin Liu*, Columbia University; Angjoo Kanazawa; David Jacobs;Peter Belhumeur, Columbia University
158 On the statistical determination of optimal camera configurations inmulti-camera surveillance networks Junbin Liu*, QUT; Tim Wark, CSIRO; Sridha Sridharan, QueenslandUniversity of Technology
165 A Dictionary Learning Approach for Classification: Separating theParticularity and the Commonality Donghui Wang*, Zhejiang University; Shu Kong, Zhejiang University
175 Exact Acceleration of Linear Object Detectors Charles Dubout*, Idiap; François Fleuret, Idiap
180 Bottom-Up Perceptual Organization of Images into Object Part Hypotheses Maruthi Narayanan*, Brown University; Benjamin Kimia, Brown University
181 Learning Human Interaction by Interactive Phrases Yu Kong*, Beijing Institute of Technology; Yunde Jia, Beijing Inst. ofTech.; Yun Fu, SUNY at Buffalo
182 Structured Image Segmentation using Kernelized Features Aurelien Lucchi*, EPFL; Yunpeng Li, EPFL; Kevin Smith, EHTZ; Pascal Fua,EPFL
185 The Scale of Geometric Texture Geoffrey Oxholm*, Drexel University; Ko Nishino, Drexel University
187 Salient Object Detection: A Benchmark Ali Borji*, University of Southern Califor; Dicky Sihite, University ofSouthern California; Laurent Itti, University of Southern California
195 Multi-Task Orde
P2ORM:(ECCV 2020聚焦)像素对遮挡关系图(P2ORM) P2ORM:公式,推论和应用 该存储库包含我们论文的官方PyTorch实施:“像素对配对关系图(P2ORM):配方,推论和应用”(ECCV 2020聚焦)。 它包括两个部分:通过方向估计遮挡边界,以及使用估计的遮挡对深度图进行细化。 通过使用此存储库,您可以评估预训练的模型,训练自己的模型并使用建议的方法生成新的遮挡注释。 有关视频和简介幻灯片等更多详细信息,请参阅我们的项目网页。 新闻(2021-02-01):遮挡标签生成的代码已发布! 新闻(2020-08-28):培训和测试代码已发布! 如果我们的项目对您的研究有所帮助,请考虑引用: @inproceedings{qiu2020pixel, title = {Pixel-{P}air Occlusion Relationship Map ({P2ORM}): Formulation, Inference \& A 立即下载

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