Conference, Workshops, and Chapters
  1. 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

  2. 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]

  3. 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]

  4. 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]

  5. 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]

  6. 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]

  7. 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]

  8. 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]

  9. 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]

  10. 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]

  11. 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]

  12. 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]

  13. 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]

  14. 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]

  15. 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]

  16. 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]

  17. 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]

  18. 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]

  19. 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]

  20. 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]

  21. 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]

  22. 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]

  23. 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]

  24. 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]


  25. 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]


  26. 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]


  27. 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]


  28. 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.


  29. 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]

  30. 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]

  31. 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]

  32. 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]

  33. 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]

  34. 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]

  35. 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]

  36. 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]

  37. 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]

  38. 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]

  39. 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]

  40. 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]

  41. 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]

  42. 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]

  43. 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]

  44. 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]

  45. 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.

  46. 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.

  47. 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]

  48. 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.

  49. 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.

  50. 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.

  51. 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.

  52. 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.

  53. 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.

  54. 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.

  55. 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.

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

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

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

  59. 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.

  60. The Geometric Interpretations for Minimax Entropy and Discrimination
    Alan Yuille and Song Chun Zhu
    Preprint of Smith-kettlewell Eye Research Institute, 1997.

  61. Stereo surface reconstruction using region competition.
    M. Weisman, S. C. Zhu, A. L. Yuille.
    Harvard Technical Report, 1996.

  62. Gibbs Reaction And Diffusion Equations.
    Song Chun Zhu, David Mumford
    Proc. 6th Int'l Conf. on Computer Vision (ICCV), 1998.

  63. Learning probability models and algorithms for vision.
    A. L. Yuille and S. C. Zhu
    Proc. Int'l. Conf. on Neural Networks, Hongkong, Sept. 1996.

  64. 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.

  65. A unified theory for statistical modeling of texture.
    S. C. Zhu, Y. N. Wu and D. B. Mumford.
    Proc. SPIE conf. on Human Vision and Electronic Imaging, San Jose, Feb. 1997.

  66. 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.

  67. 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.

  68. 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.

  69. The statistical and syntactical modeling and recognition of flexible objects.
    S. C. Zhu and A. L. Yuille.
    Proc. Workshop on Geometrical Modeling and Invariants for Computer Vision.\ Xi'an, April, 1995.

  70. A framework for shape representation and recognition.
    S. C. Zhu and A. L. Yuille.
    Proc. 1st Int'l conf. on Image Processing (ICIP), Austin, Nov., 1994.

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