1. Learning Complex Functional Manipulations by Human Demonstration and Fluent Discovery
    F. Gao, M. Edmonds, X. Xie, H. Liu, Y. Zhu, S. QI, B. Rothrock, S.C. Zhu
    Int'l Conf. on Intelligent Robots and Systems (IROS), 2017.

  2. A Glove-based System for Studying Hand-Object Manipulation via Pose and Force Sensing
    H. Liu, X. Xie, M. Millar, M. Edmonds, F. Gao, Y. Zhu, V.J. Santos, B. Rothrock, S.C. Zhu
    Int'l Conf. on Intelligent Robots and Systems (IROS), 2017.

  3. Unified Single-Image 3D Scene Parsing Using Geometric Commonsense
    C. Yu, X. B. Liu and S.C. Zhu
    26th Int'l joint Conf. on Artificial Intelligence (IJCAI), 2017.

  4. Inferring Human Attention by Learning Latent Intentions
    P. Wei, X. Dan, N.N. Zheng and S.C. Zhu
    26th Int'l joint Conf. on Artificial Intelligence (IJCAI), 2017.

  5. Inferring Hidden Statuses and Actions in Video by Causal Reasoning [pdf][web]
    A. Fire and S.-C. Zhu
    Int'l Workshop on Vision Meets Cognition Workshop: Functionality, Physics, Intentionality and Causality (FPIC), with CVPR, 2017.

  6. CERN: Confidence-Energy Recurrent Network for Group Activity Recognition [pdf][web]
    T. Shu, S. Todorovic, and S.-C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2017

  7. Mining Object Parts from CNNs via Active Question-Answering [pdf][web]
    Q. Zhang, R. Cao, Y. N. Wu, and S.-C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2017

  8. Synthesizing Dynamic Patterns by Spatial-Temporal Generative ConvNet [pdf][web]
    J. Xie, S.-C. Zhu, Y.N. Wu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2017

  9. Generative Hierarchical Learning of Sparse FRAME Models [pdf][web]
    J. Xie, Y. Xu, E. Nijkamp, Y.N. Wu, S.-C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2017

  10. Inferring Human Interaction from Motion Trajectories in Aerial Videos [pdf][web]
    T. Shu, Y. Peng, L. Fan, H. Lu, and S.-C. Zhu
    39th Annual Meeting of the Cognitive Science Society (CogSci), 2017.

  11. Consistent Probabilistic Simulation Underlying Human Judgment in Substance Dynamics [pdf][web]
    J. Kubricht, C. Jiang, Y.X. Zhu, S.-C. Zhu, D. Terzopoulos, H.J. Lu
    39th Annual Meeting of the Cognitive Science Society (CogSci), 2017.

  12. Visuomotor Adaptation and Sensory Recalibration in Reversed Hand Movement Task [pdf][web]
    J. Lin, Y.X. Zhu, J. Kubricht, S.-C. Zhu, and H.J. Lu
    39th Annual Meeting of the Cognitive Science Society (CogSci), 2017.

  13. Learning Social Affordance Grammar from Videos : Transferring Human Interactions to Human-Robot Interactions [pdf][web]
    T. Shu, X. Gao, M. S. Ryoo, S.-C. Zhu
    Int'l Conference on Robotics and Automation (ICRA), 2017.

  14. The Martian: Examining Human Physical Judgments Across Virtual Gravity Fields [pdf][web]
    T. Ye*, S. Qi*, J. Kubricht, Y. Zhu, H. Lu, and S.C. Zhu
    IEEE Virtual Reality, March, 2017

  15. Alternating Back-Propagation for Generator Network [pdf][web]
    T. Han, Y. Lu S.C. Zhu, and Y.N. Wu
    31th AAAI Conference on Artificial Intelligence (AAAI), San Francisco, Feb, 2017

  16. Cross-view People Tracking by Scene-Centered Spatio-Temporal Parsing [pdf][web]
    Y. Xu, X. B.Liu, L. Qin, and S.C. Zhu
    31th AAAI Conference on Artificial Intelligence (AAAI), San Francisco, Feb, 2017

  17. Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning [pdf][web]
    Q. Zhang, R. Cao, Y. N. Wu, and S.C. Zhu
    31th AAAI Conference on Artificial Intelligence (AAAI), San Francisco, Feb, 2017

  18. Inferring Context through Scene Understanding [pdf]
    M. Walton, D. Lange and S.C. Zhu
    31th AAAI Conference on Artificial Intelligence (AAAI) Symposium on Computational Context, San Francisco, Feb, 2017

  19. A Virtual Reality Platform for Dynamic Human-Scene Interaction [pdf][web]
    J. Lin*, X. Guo*, J. Shao*, C. Jiang, Y. Zhu, and S.C. Zhu
    Siggraph Asia, Virtual reality meets physical reality workshop, Dec. 2016.

  20. What is Where: Inferring Containment Relations from Videos [pdf][web]
    W. Liang, Y. Zhao, Y.X. Zhu, and S.C. Zhu
    25th Int'l joint Conf. on Artificial Intelligence (IJCAI), p.3418-3424, 2016.

  21. Learning Social Affordance for Human-Robot Interactions [pdf][web]
    T.M. Shu, M. Ryoo, and S.C. Zhu
    25th Int'l joint Conf. on Artificial Intelligence (IJCAI), p3454-3461, 2016.

  22. Jointly Learning Grounded Task Structures from Language Instruction and Visual Demonstration [pdf]
    C. Liu, S. Yang, S. Saba-Sadiya, N. Shukla, Y. He, S.-C. Zhu, and J. Chai
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016.

  23. Inferring Human Intent from Video by Sampling Hierarchical Plans [pdf]
    S. Holtzen, Y.B. Zhao, T. Gao, J. B. Tenenbaum, S.C. Zhu
    Int'l Conf. on Intelligent Robots and Systems (IROS), Deajeon, Oct., 2016.

  24. A Theory of Generative ConvNet [pdf][web]
    J. Xie, Y. Lu, S.C. Zhu, and Y.N. Wu
    Int'l Conf. on Machine Learning (ICML), p2635-2644, 2016.

  25. Grounded Semantic Role Labeling [pdf][web]
    S. Yang, Q. Gao, C. Liu, C. Xiong, S.C. Zhu, and J. Y. Chai
    15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NA-ACL), p149-159, San Diego, 2016

  26. Probabilistic Simulation Predicts Human Performance on Viscous Fluid-Pouring Problem [pdf][web]
    J. Kubricht, C. Jiang, Y.X. Zhu, S.C. Zhu, D. Terzopoulos, and H.J. Lu
    38th Annual Meeting of the Cognitive Science Society (CogSci), 2016.

  27. Critical Features of Joint Actions that Signal Human Interaction [pdf][web]
    T. Shu, S. Thurman, D. Chen, S.C. Zhu, and H.J. Lu
    38th Annual Meeting of the Cognitive Science Society (CogSci), 2016.

  28. Multi-view People Tracking via Hierarchical Trajectory Composition [pdf][web]
    Y. Xu, X.Liu, Y. Liu and S.-C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2016.

  29. Recognizing Car Fluents from Video [pdf][web]
    B. Li, T.F. Wu, C. Xiong, and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2016.

  30. Inferring Forces and Learning Human Utilities from Video [pdf][web]
    Y.X. Zhu, C. Jiang, Y. Zhao, D. terzopoulos and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2016.

  31. Robot Learning with a Spatial, Temporal, and Causal And-Or Graph [pdf][web]
    C.M. Xiong, N. Shukla, W. Xiong and S.C. Zhu
    Int'l Conference on Robotics and Automation (ICRA), p2144-2151, 2016.

  32. Learning FRAME Models Using CNN Filters [pdf][web]
    Y. Lu, S.C. Zhu and Y.N. Wu
    30th AAAI Conference on Artificial Intelligence (AAAI), p1902-1910, Phoenix, Arizona, 2016.

  33. Task Learning through Visual Demonstration and Situated Dialogue [pdf]
    C.S. Liu, J. Y. Chai, N. Shukla and S.C.Zhu
    AAAI Workshop on Symbiotic Cognitive Systems, Phoenix, Arizona, 2016.

  34. Attributed Grammars for Joint Estimation of Human Attributes, Parts and Poses [pdf][web]
    S. Park and S.C. Zhu
    Proc. of International Conference on Computer vision (ICCV), 2015.

  35. Mining And-Or Graphs for Graph Matching and Object Discovery [pdf][web]
    Q.S. Zhang, Y.N. Wu and S.C. Zhu
    Proc. of International Conference on Computer vision (ICCV), 2015.

  36. Automated Facial Trait Judgment and Election Outcome Prediction: Social Dimensions of Face [pdf][web]
    J. Joo, F. Steen and S.C. Zhu
    Proc. of International Conference on Computer vision (ICCV), 2015.

  37. A Unified Framework for Human-Robot Knowledge Transfer
    N. Shukla, C.M. Xiong and S.C. Zhu
    AAAI Symposium on Artificial Intelligence and Human-Robot Interactions (AI-HRI), 2015.

  38. Represent and Infer Human Theory of Minds for Human-Robot Interaction.
    Y.B. Zhao, S. Holtzen, T. Gao and S.C. Zhu
    AAAI Symposium on Artificial Intelligence and Human-Robot Interactions (AI-HRI), 2015.

  39. Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition [pdf][web]
    Y. Zhu, Y.B. Zhao and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2015.

  40. Joint Inference of Groups, Events and Human Roles in Aerial Videos [pdf][web]
    T. Shu, D. Xie, B. Rothrock, S. Todorovic and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2015.

  41. Joint Action Recognition and Pose Estimation From Video [pdf][web]
    B. X. Nie, C. Xiong and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2015.

  42. Evaluating Human Cognition of Containing Relations with Physical Simulation [pdf][web]
    W. Liang, Y. B. Zhao, Y.X. Zhu and S.C. Zhu
    37th Annual Cognitive Science Conference (CogSci), Los Angeles, 2015.

  43. Mapping Energy Landscapes of Non-Convex Learning Problems [pdf]
    M. Pavlovskaia, K.W. Tu and S.C. Zhu
    Proc. of Energy Minimization Method for Computer Vision and Pattern Recognition (EMMCVPR), Hong Kong, Jan. 2015.

  44. Integrating Context and Occlusion for Car Detection by Hierarchical And-Or Model. [pdf]
    B. Li, T.F. Wu and S.C. Zhu
    Proc. of European Conf. on Computer Vision (ECCV), 2014.

  45. Visual Persuasion: Inferring Communicative Intents of Images [pdf][web]
    J. Joo, W.X. Li, F. Steen and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014.

  46. Cross-View Action Modeling, Learning and Recognition [pdf][web]
    J. Wang, B. Nie, Y. Xia, Y. Wu and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014.

  47. Single-View 3D Scene Parsing by Attributed Grammar [pdf][web]
    X.B. Liu, Y.B. Zhao and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014.

  48. Online Object Tracking, Learning and Parsing with And-Or Graphs [pdf][web]
    Y. Lu, T.F. Wu and S.C. Zhu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014.

  49. Learning Inhomogeneous FRAME Models for Object Patterns [pdf][web]
    J. Xie. W. Hu, S.C. Zhu and Y. Wu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014.

  50. Unsupervised Learning of Dictionaries of Hierarchical Compositional Models [pdf][web]
    J. Dai, Y. Hong, W. Hu, S.C. Zhu and Y. Wu
    Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014.

  51. Detecting Potential Falling Objects by Inferring Human Action and Natural Disturbance [pdf] [web]
    B. Zheng, Y.B. Zhao, J. C. Yu, K. Ikeuchi and S.C. Zhu
    Proc. Int'l Conf. on Robotics and Automations (ICRA), 2014.

  52. Unsupervised Structure Learning of Stochastic And-Or Grammars [pdf][web]
    K.W Tu, M. Pavlovskaia and S.C. Zhu
    Proc. Neural Information Processing Systems (NIPS), 2013.

  53. Inferring ‘Dark Matter’ and ‘Dark Energy’ from Videos [pdf][web]
    D. Xie, S. Todorovic and S.C. Zhu
    Proc. Int’l Conference on Computer Vision (ICCV), 2013.

  54. Learning Near-Optimal Cost-Sensitive Decision Policy for Object Detection [pdf][web]
    T.F. Wu and S.C. Zhu
    Proc. Int’l Conference on Computer Vision (ICCV), 2013.

  55. Monte Carlo Tree Search for Scheduling Activity Recognition [pdf][web]
    M. Amer, S. Todorovic, A. Fern and S.C. Zhu
    Proc. Int’l Conference on Computer Vision (ICCV), 2013.

  56. Human Attribute Recognition by Rich Appearance Dictionary [pdf][web]
    J. Joo, S. Wang and S.C. Zhu
    Proc. Int’l Conference on Computer Vision (ICCV), 2013.

  57. Cosegmentation and Cosketch by Unsupervised Learning [pdf][web]
    J. Dai, Y. Wu, J. Zhou and S.C. Zhu
    Proc. Int’l Conference on Computer Vision (ICCV), 2013.

  58. Concurrent Action Detection with Structural Prediction [pdf][web]
    P. Wei, N.N. Zheng, Y.B. Zhao and S.C. Zhu
    Proc. Int’l Conference on Computer Vision (ICCV), 2013.

  59. Modeling Occlusion by Discriminative AND-OR Structures [pdf][web]
    B. Li, W. Hu, T.F. Wu and S.C. Zhu
    Proc. Int’l Conference on Computer Vision (ICCV), 2013.

  60. Modeling 4D Human-Object Interactions for Event and Object Recognition [pdf][web]
    P. Wei, Y. B. Zhao, N.N. Zheng and S.C. Zhu
    Proc. Int’l Conference on Computer Vision (ICCV), 2013.

  61. Using Causal Induction in Humans to Learn and Infer Causality from Video [pdf] [web]
    A. Fire and S.C. Zhu
    35th Annual Cognitive Science Conference (CogSci), Berlin, Germany, 2013

  62. Scene Parsing by Integrating Function, Geometry and Appearance Models [pdf] [web with data]
    Y. B. Zhao and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2013.

  63. Beyond Point Clouds: Scene Understanding by Reasoning Geometry and Physics [pdf] [web with data]
    B. Zheng, Y.B. Zhao, J.C. Yu, K. Ikeuchi, and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2013.

  64. Integrating Grammar and Segmentation for Human Pose Estimation [pdf] [web with data]
    B. Rothrock, S. Park, and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2013.

  65. Discriminatively Trained And-Or Tree Models for Object Detection [pdf] [web with data]
    X. Song, T.F. Wu, Y. Jia, and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2013.

  66. Weakly Supervised Learning for Attribute Localization in Outdoor Scenes [pdf] [web with data]
    S. Wang, J. Joo, Y.Z. Wang, and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2013.

  67. Rates for Inductive Learning of Compositional Models [pdf]
    A. Barbu, M. Pavlovskaia and S.C. Zhu
    AAAI Workshop on Learning Rich Representations from Low-Level Sensors (RepLearning), Bellvue, WA, 2013

  68. Learning Perceptual Causality from Video
    A. Fire and S.C. Zhu
    AAAI Workshop on Learning Rich Representations from Low-Level Sensors (RepLearning), Bellvue, WA, 2013

  69. Cost-Sensitive Top-down/Bottom-up Inference for Multiscale Activity Recognition [pdf][web with dataset ]
    M. R. Amer, D. Xie, M. Zhao, S. Todorovic, and S.C. Zhu
    European Conf. on Computer Vision (ECCV), 2012.

  70. Hierarchical Space Tiling for Scene Modelling [pdf] [web]
    S. Wang, Y.Z Wang, and S.C. Zhu
    Proc. of Asia Conf. on Computer Vision (ACCV), 2012.

  71. Reconfigurable Templates for Robust Vehicle Detection and Classification [pdf][web]
    Y. Lu, B. Yao, Y. Wang and S.C. Zhu
    Workshop on Application of Computer Vision (WACV), Colorado, 2012

  72. Learning Reconfigurable Scene Representation by Tangram Model [pdf][web]
    J. Zhu, T.F. Wu, S.C. Zhu, X.K. Yang, W. Zhang
    Workshop on Application of Computer Vision (WACV), Colorado, 2012

  73. Artistic Rendering of Portraits [pdf][web]
    M.T. Zhao and S.C. Zhu
    Book chapter in Image and Video based Artistic Stylization, Eds. J. Collomosse and P. Rossin, Springer, 2012

  74. Hierarchical Organization by And-Or Tree [pdf][web]
    J. Joo, S. Wang and S.C. Zhu
    Book chapter in Handbook of Perceptual Organization, eds.J. Wagemans, Springer, 2012

  75. Structure v.s. Appearance and 3D v.s. 2D? A Numeric Answer [pdf][web]
    W.Z. Hu, Z. Si, and S.C. Zhu
    Book chapter in Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective Eds.S. Dickinson and Z. Pizlo Cambridge Univ. Press, 2012

  76. Learning 3D Object Templates by Hierarchical Quantization of Geometry and Appearance Spaces [pdf][web with data and code ]
    W.Z. Hu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Providence, RI 2012.

  77. Image Parsing via Stochastic Scene Grammar [pdf] [web]
    Y.B. Zhao and S.C. Zhu
    Neural Information Processing Systems (NIPS), 2011.

  78. Unsupervised Learning of Stochastic And-Or Templates for Object modeling [pdf] [web]
    Z.Z. Si and S.C. Zhu
    Int'l Workshop on Stochastic Image Grammar (SIG), Barcelona, Spain, 2011

  79. Human Parsing using Stochastic And-Or grammar and Rich Appearance [pdf] [web]
    B. Rothrock and S.C. Zhu
    Int'l Workshop on Stochastic Image Grammar (SIG), Barcelona, Spain, 2011

  80. Parsing Video Events with Goal inference and Intent Prediction [pdf] [web]
    M. Pei, Y. Jia, and S.-C. Zhu
    Int'l Conf. on Computer Vision (ICCV), Barcelona, Spain, 2011.

  81. Unsupervised Learning of Event And-Or Grammar and Semantics from Video [pdf] [web]
    Z. Si, M. Pei, Z.Y. Yao, and S.-C. Zhu
    Int'l Conf. on Computer Vision (ICCV), Barcelona, Spain, 2011.

  82. Image Representation by Active Curves [pdf] [web]
    W.Z. Hu, Y.N. Wu and S.-C. Zhu
    Int'l Conf. on Computer Vision (ICCV), Barcelona, Spain, 2011.

  83. Video Primal Sketch: A Generic Middle-Level Representation of Video [pdf] [web]
    Z. Han, Z.B. Xu, and S.-C. Zhu
    Int'l Conf. on Computer Vision (ICCV), Barcelona, Spain, 2011.

  84. Inferring Social Roles in Long Timespan Video Sequence [pdf] [web]
    J. Zhang, W. Hu, B. Yao, Y. Wang and S.C. Zhu
    Int'l Workshop on Video Event Categorization, Tagging and Retrieval for Real World Applications, Barcelona, Spain, 2011.

  85. Customizing Painterly Rendering Styles Using Stroke Processes [pdf] [web]
    M.T. Zhao and S.-C. Zhu
    Int'l Symposium on Non-Photorealistic Animation and Rendering (NPAR), Vancouver, Canada, 2011.

  86. Portrait Painting Using Active Templates [pdf] [web]
    M.T. Zhao and S.-C. Zhu
    Int'l Symposium on Non-Photorealistic Animation and Rendering (NPAR), Vancouver, Canada, 2011.

  87. CO3 for Ultra-fast and Accurate Interactive Segmentation [pdf] [web]
    Y.B. Zhao, S.C. Zhu, and S.W. Luo,
    ACM conference on Multi-media (MM'10, Long paper), Firenze, Italy, October, 2010.

  88. Artistic Paper-cut of Human Portraints [pdf] [web]
    M. Meng, M.T. Zhao, S.C. Zhu,
    ACM conference on Multi-media (MM'10, short paper), October, 2010, Firenze, Italy.

  89. Sisley the Abstract Painter [pdf] [web]
    M.T. Zhao and S.C. Zhu
    Int'l Symposium on Non-Photorealistic Animation and Rendering (NPAR) Annecy, France, 2010.

  90. Painterly Animation Using Video Semantics and Feature Correspondence [pdf] [web]
    L. Lin K. Zeng H. Lv Y.Z. Wang, Y. Xu, and S. C. Zhu
    Int'l Symposium on Non-Photorealistic Animation and Rendering (NPAR) Annecy, France, 2010.

  91. Learning Artistic Lighting Template from Portrait Photographs [pdf] [web]
    X. Jin, M.T. Zhao, X.W Chen,Q.P. Zhao, S.C. Zhu
    Proc. of European Conf. on Computer Vision (ECCV), 2010.

  92. Learning a Probabilistic Model Mixing 3D and 2D Primitives for View Invariant Object Recognition [pdf] [web]
    W.Z. Hu and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , San Francisco, 2010.

  93. Discovering Scene Categories by Information Projection and Cluster Sampling [pdf]
    D.X. Dai, T.F. Wu and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , San Francisco, 2010

  94. Learning Deformable Action Templates from Cluttered Videos [pdf]
    B. Yao and S.C. Zhu
    Proc. Int'l Conf. on Computer Vision (ICCV) , Kyoto, Japan, 2009

  95. Evaluating Information Contributions of Bottom-up and Top-down Processes [pdf]
    X. Yang, T.F. Wu, and S.C. Zhu
    Proc. Int'l Conf. on Computer Vision (ICCV) , Kyoto, Japan, 2009

  96. Learning Mixed Templates for Object Recognition [pdf]
    Z.Z. Si, H.F. Gong, Y.N. Wu, and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , Miami, Florida, June, 2009

  97. Flow Mosaicking: Real-time Pedestrian Counting without Scene-Specific Learning [pdf]
    Y. Cong, H.F. Gong, and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , Miami, Florida, June, 2009

  98. Trajectory Parsing by Cluster Sampling in Spatio-Temporal Graph [pdf]
    X.B. Liu, L. Lin, and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , Miami, Florida, June, 2009

  99. Layered Graph Matching by Composite Clustering with Collaborative and Competitive Interactions [pdf]
    L. Lin, K. Zeng, X. B. Liu and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , Miami, Florida, June, 2009

  100. Learning compositional models for object categories from small sample sets [pdf]
    J. Porway, B. Yao, and S.C. Zhu
    Book Chapter in Sven Dickinson et al (eds.) Object Categorization: Computer and Human Vision Perspectives, Cambridge University Press. 2009

  101. A Hierarchical and Contextual Model for Aerial Image Understanding
    J. Porway, K. Wang, and S.C. Zhu,
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , Anchorage, Alaska, June, 2008. [pdf]

  102. An Integrated Background Model for Video Surveillance Based on Primal Sketch and 3D Scene Geometry
    W. HU, H.F. Gong, S.C. Zhu, and Y. Wang,
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , Anchorage, Alaska, June, 2008.[pdf]

  103. Learning a Scene Contextual Model for Tracking and Abnormality Detection
    B. Yao, L. Wang and S.C. Zhu
    Proc. 3rd Int'l Workshop on Semantic Learning and Applications in Multimedia, Anchorage, Alaska, June, 2008. [pdf]

  104. SAVE: A Framework for Semantic Annotation of Visual Events
    M.W. lee, A. Hakeem, N. Haering, and S.C. Zhu,
    Proc. 1st Int'l Workshop on Internet Vision, Anchorage, Alaska, June, 2008. [pdf]

  105. Deformable Template As Active Basis
    Y.N. Wu, Z.Z. Si, C. Fleming, and S.C. Zhu
    Proc. Int'l Conf. on Computer Vision (ICCV), Rio. Brazil, Oct, 2007. [pdf]

  106. An Empirical Study of Object Category Recognition: Sequential Testing with Generalized Samples
    L. Lin, S.W Peng, J. Porway, S.C. Zhu, and Y.T. Wang
    Proc. Int'l Conf. on Computer Vision (ICCV), Rio. Brazil, Oct, 2007. [pdf]

  107. Introduction to a large scale general purpose groundtruth dataset: methodology, annotation tool, and benchmarks
    Z.Y. Yao, X. Yang, and S.C. Zhu
    Proc. 6th Int'l Conf on Energy Minimization Methods in CVPR (EMMCVPR), Springer LNCS 4679, Ezhou, China, Aug 2007. [pdf]

  108. Object category recognition using generative template boosting
    S.W. Peng, L. Lin, J. Porway, N. Sang, and S.C. Zhu
    Proc. 6th Int'l Conf on Energy Minimization Methods in CVPR (EMMCVPR), Springer LNCS 4679, Ezhou, China, Aug 2007. [pdf]

  109. An Automatic Portrait System Based on And-Or Graph Representation
    F Min, J.L. Suo, S.C. Zhu, and N. Sang
    Proc. 6th Int'l Conf on Energy Minimization Methods in CVPR (EMMCVPR), Springer LNCS 4679, Ezhou, China, Aug 2007. [pdf]

  110. Dynamic Feature Cascade for Multiple Object Tracking with Trackability Analysis
    Z. Li, H.F. Gong, S.C. Zhu, and N. Sang
    Proc. 6th Int'l Conf on Energy Minimization Methods in CVPR (EMMCVPR), Springer LNCS 4679, Ezhou, China, Aug 2007. [pdf]

  111. Bayesian Inference for Layer Representation with Mixed Markov Random Field
    R.X. Gao, T.F Wu, N. Sang, and S.C. Zhu
    Proc. 6th Int'l Conf on Energy Minimization Methods in CVPR (EMMCVPR), Springer LNCS 4679, Ezhou, China, Aug 2007. [pdf]

  112. Mapping the Ensemble of Natural Image Patches by Emplicit and Implicit Manifolds
    K, Shi and S.C. Zhu
    Proc. IEEE. Conf. on Computer Vision and Pattern Recognition (CVPR), June, 2007. [pdf]

  113. Compositional Boosting for Computing Hierarchical Image Structures
    T.F. Wu, G.S. Xia, and S.C. Zhu
    Proc. IEEE. Conf. on Computer Vision and Pattern Recognition (CVPR) , June, 2007. [pdf]

  114. Layered Graph Matching with Graph Editing
    L. Lin, S.C. Zhu and Y.T. Wang
    Proc. IEEE. Conf. on Computer Vision and Pattern Recognition (CVPR), June, 2007. [pdf]

  115. A Multi-Resolution Dynamic Model for Face Aging Simulation
    Jl. Suo, F. Min, S.C. Zhu, S.G. Shan, and X. L. Chen
    Proc. IEEE. Conf. on Computer Vision and Pattern Recognition (CVPR) , June, 2007. [pdf]

  116. Composite Templates for Cloth Modeling and Sketching
    H. Chen, Z.J. Xu, Z.Q. Liu, and S.C. Zhu
    Proc. IEEE Conf. on Pattern Recognition and Computer Vision (CVPR), June, 2006. [pdf]

  117. Incorporating Visual Knowledge Representation in Stereo Reconstruction
    A. Barbu and S.C. Zhu
    Proc. Int'l Conf. on Computer Vision (ICCV), Beijing, China, Oct. 2005. [pdf]

  118. Perceptual Scale Space and It Applications
    Y. Z. Wang, S. Bahrami, and S.C. Zhu
    Proc. Int'l Conf. on Computer Vision (ICCV), Beijing, China, Oct. 2005. [pdf]

  119. Bottom-up/Top-Down Image Parsing by Attribute Graph Grammar
    F. Han and S.C. Zhu
    Proc. Int'l Conf. on Computer Vision (ICCV), Beijing, China, Oct. 2005. [pdf]

  120. A generative model of human hair for hair sketching
    H. Chen and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), San Diego, June 2005.[pdf]

  121. A high resolution grammatical model for face representation and sketching
    Z.J. Xu, H. Chen and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), San Diego, June 2005.[pdf]

  122. Cloth representation by shape from shading with shading primitives
    F. Han and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), San Diego, June 2005.[pdf]

  123. Modeling complex motion by tracking and editing hidden Markov graphs
    Y.Z. Wang and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Washington, DC, June 2004. [pdf]

  124. Information scaling laws in natural scenes
    C.E. Guo, Y.N. Wu, and S.C. Zhu
    Prod. 2nd Workshop on Generative Model Based Vision Washington, DC, June 2004. [pdf]

  125. Multigrid and multi-level Swendsen-Wang cuts for hierarchic graph partition
    A. Barbu and S.C. Zhu
    Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Washington, DC, June 2004. [pdf]

  126. On the relationship between image and motion segmentation
    A. Barbu and S.C. Zhu
    Proc. Workshop on Spatial Coherence for Visual Motion Analysis , Prague, Czech, May, 2004. [pdf]

  127. Automatic single view building reconstruction by integrating segmentation
    F. Han and S.C. Zhu
    Proc. IEEE Workshop on Perceptual Organization in Computer Vision Washington, DC, June 2004.

  128. A mathematical theory of primal sketch and sketchability.
    C.E. Guo, S.C. Zhu and Y.N. Wu.
    Proc. of Int'l Conf. on Computer Vision (ICCV), Nice, France, October, 2003. [demo][pdf]

  129. Image parsing: segmentation, detection, and recognition.
    Z.W. Tu, X.R. Chen, A.L Yuille, and S.C. Zhu.
    Proc. of Int'l Conf. on Computer Vision (ICCV), Nice, France, October, 2003.[demo][pdf]

  130. Modeling textured motion: particles, waves, and cartoon sketch.
    Y.Z. Wang and S.C. Zhu.
    Proc. of Int'l Conf. on Computer Vision (ICCV), Nice, France, October, 2003.[demo][pdf]

  131. Graph partition by Swendsen-Wang cut.
    A. Barbu and S.C. Zhu.
    Proc. of Int'l Conf. on Computer Vision (ICCV), Nice, France, October, 2003.[demo][pdf]

  132. A multiscale generative model for animate shape and parts.
    A. Dubinskiy and S.C. Zhu.
    Proc. of Int'l Conf. on Computer Vision (ICCV), Nice, France, October, 2003.[demo][pdf]

  133. How do heuristics expedite Markov chain search? .
    R. Maciuca and S.C. Zhu.
    Proc. of Int'l workshop on Statistical and Computational Theories of Vision. (SCTV) , Nice, France, October, 2003 .[demo] [pdf]

  134. Bayesian reconstruction of 3D shapes and scenes from a single image .
    F. Han and S.C. Zhu.
    Proc. of Int'l workshop on High Level Knowledge in 3D Modeling and Motion. (HLK) , Nice, France, October, 2003.[demo] [pdf]

  135. A generative model for textured motion: analysis and synthesis.
    Y.Z. Wang and S.C. Zhu.
    Proc. of European Conf. on Computer Vision (ECCV), Copenhagen, June,2002.[pdf]

  136. Parsing images into region and curve processes
    Z.W. Tu and S.C. Zhu
    Proc. of European Conf. on Computer Vision (ECCV), Copenhagen, June, 2002.[pdf]

  137. What are textons?
    S.C. Zhu, C.E. Guo, Y.N. Wu, and Y.Z. Wang
    Proc. of European Conf. on Computer Vision (ECCV), Copenhagen, June, 2002.[pdf]

  138. Statistical modeling of texture sketch
    Y.N. Wu, S.C. Zhu, and C.E. Guo
    Proc. of European Conf. on Computer Vision (ECCV), Copenhagen, June, 2002.[pdf]

  139. A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction
    F. Han, Z.W. Tu, and S.C. Zhu
    Proc. of European Conf. on Computer Vision (ECCV), Copenhagen, June, 2002.[pdf]

  140. Image segmentation by data driven Markov chain Monte Carlo.
    Z. W. Tu, S. C. Zhu and H. Y. Shum.
    Proc. of Int'l Conference on Computer Vision (ICCV), Vancouver, Canada, July, 2001. [pdf]

  141. Visual learning by integrating descriptive and generative methods.
    C. E. Guo, S. C. Zhu and Y. N. Wu
    Proc. of Int'l Conference on Computer Vision (ICCV), Vancouver, Canada, July, 2001. [pdf]

  142. Learning inhomogeneous Gibbs models of faces by minimax entropy.
    C. Liu, S. C. Zhu, and H. Y. Shum.
    Proc Int'l Conference on Computer Vision (ICCV), Vancouver, Canada, July, 2001.[pdf]

  143. Example-based facial sketch generation with non-parametric sampling.
    H. Chen, Y. Q. Xu, H. Y. Shum, S. C. Zhu, and N. N. Zhen.
    Proc. Int'l Conference on Computer Vision (ICCV), Vancouver, Canada, July, 2001.[pdf]

  144. Conceptualization and Modeling of Visual Patterns
    S.C. Zhu and C.E. Guo
    Proc. of IEEE Workshop on Perceptual Organization in Computer Vision (POCV), Vancouver, Canada, July 2001.

  145. Asymptotically admissible texture synthesis
    Y. Q. Xu, S. C. Zhu, B. N. Guo, and H. Y. Shum
    Proc. of Int'l Workshop on Statistical and Computational Theories of Vision (SCTV), Vancouver, Canada, 2001.

  146. Integrating Top-down/Bottom-up for Object Recognition by Data Driven Markov Chain Monte Carlo
    S. C. Zhu, R. Zhang, and Z. W. Tu.
    Proc. of Int'l Conf. on Computer Vision and Pattern Recognition (CVPR), 2000.[pdf]

  147. Order Parameter Theory for minimax entropy models: How Does High Level Knowledge Helps?
    A. L. Yuille, J. Coughlan, Y. N. Wu, and S. C. Zhu
    Proc. of Int'l Conf. on Computer Vision and Pattern Recognition (CVPR), 2000.

  148. Learning in Gibbsian Feilds: How Accurate and How Fast can It Be?
    S.C. Zhu and X.W. Liu,
    Proc. of Int'l Conf. on Computer Vision and Pattern Recognition (CVPR), 2000.

  149. Mathematical Modeling of Clutter: descriptive vs. generative models
    S. C. Zhu and C. E. Guo
    Proc. of SPIE AeroSense Conference on Automatic Target Recognition, Orlando, FL. 2000.

  150. A unified framework for performance analysis in Bayesian inference.
    A. L. Yuille, J. Coughlan, and S. C. Zhu
    Proc. of SPIE AeroSense conference on Automatic Target Recognition, Orlando, FL. 2000.

  151. Effective Bayesian Inference by Data-Driven Markov Chain Monte Carlo
    S.C. Zhu, Z. W. Tu, and R. Zhang
    Proc. of SPIE AeroSense conference on Automatic Target Recognition, Orlando, FL. 2000.

  152. Equivalance of Julesz and Gibbs Ensembles
    Y. N. Wu, S. C. Zhu, and X. W. Liu
    Proc. of Int'l Conf on Computer Vision, Greece (ICCV), September, 1999.

  153. Exploring Julesz Ensembles by Efficient MCMC
    S. C. Zhu, X. W. Liu, and Y.N. Wu
    Proc. of Workshop on Stat. and Comput. Theories of Vision (SCTV), Fort Collins, CO, June, 1999.

  154. Fundamental Bounds on Edge Detection
    S. M. Konishi, J. M. Coughlan, A. L. Yuille, and S. C. Zhu
    Proc. of Int'l Conf. on Computer Vision and Pattern recognition (CVPR), 1999.

  155. A theory for computing texture and shape
    S.C. Zhu
    Proc. of Int'l Conf. on Computational Neurosciences, Santa Barabra, 1998.

  156. Stochastic Computation of Medial Axis in Markov Random Fields
    S. C. Zhu
    Proc. of Int'l Conf. on Computer Vision and Pattern recognition (CVPR), 1998.

  157. A theory for shape modeling and perceptual organization
    S. C. Zhu
    IEEE Computer Society Workshop on Perceptual Organization in Computer Vision (POCV), 1998.

  158. Clutter modeling and Performance analysis in Automatic Target recognition
    S. Zhu, A.D. Lanterman, and M.I. Miller
    Workshop on Detection and Classification of Difficult Targets,
    Redstone Arsenal, Alabama, 1998.

  159. Gibbs Reaction And Diffusion Equations. [pdf]
    S.C. Zhu and D.B. Mumford
    Proc. 6th Int'l Conf. on Computer Vision (ICCV), 1998.

  160. Learning generic prior models for visual computation.
    S. C. Zhu and D. B. Mumford.
    Proc. of Int'l. Conf. on Computer Vision and Pattern Recognition (CVPR), 1997.

  161. Filters, Random Fields, and Maximum Entropy (FRAME): towards a unified theory for texture modeling.
    S. C. Zhu, Y. N. Wu and D. B. Mumford.
    Proc. Int'l. Conf. on Computer Vision and Pattern Recognition (CVPR), S.F. June, 1996.

  162. FORMS: a Flexible Object Recognition and Modeling System.
    S. C. Zhu and A. L. Yuille.
    Proc. 5th Int'l Conf. on Computer Vision (ICCV), Boston. June, 1995.

  163. Region Competition: unifying snakes, region growing, and Bayes/MDL for multi-band image segmentation.
    S. C. Zhu, T. S. Lee, and A. L. Yuille.
    Proc. 5th Int Conf. on Computer Vision (ICCV), Boston, June, 1995.


© S.-C. Zhu