Image Parsing: Unifying Segmentation, Detection, and Recognition
暂无分享,去创建一个
Zhuowen Tu | Alan L. Yuille | Song-Chun Zhu | Xiangrong Chen | A. Yuille | Song-Chun Zhu | Z. Tu | Xiangrong Chen
[1] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[2] W. K. Hastings,et al. Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .
[3] S. Ullman. Visual routines , 1984, Cognition.
[4] S. Geman,et al. Diffusions for global optimizations , 1986 .
[5] Wayne Niblack,et al. An introduction to digital image processing , 1986 .
[6] Anne Treisman,et al. Features and objects in visual processing , 1986 .
[7] John F. Canny,et al. A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] C. Hwang,et al. Diffusion for global optimization in R n , 1987 .
[9] Ulf Grenander,et al. Hands: A Pattern Theoretic Study of Biological Shapes , 1990 .
[10] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[11] M. Turk,et al. Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.
[12] Harris Drucker,et al. Boosting Performance in Neural Networks , 1993, Int. J. Pattern Recognit. Artif. Intell..
[13] Joel L. Davis,et al. Large-Scale Neuronal Theories of the Brain , 1994 .
[14] S Ullman,et al. Sequence seeking and counter streams: a computational model for bidirectional information flow in the visual cortex. , 1995, Cerebral cortex.
[15] Geoffrey E. Hinton,et al. The Helmholtz Machine , 1995, Neural Computation.
[16] P. Green. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination , 1995 .
[17] David Mumford,et al. Neuronal Architectures for Pattern-theoretic Problems , 1995 .
[18] Elie Bienenstock,et al. Compositionality, MDL Priors, and Object Recognition , 1996, NIPS.
[19] Geoffrey E. Hinton,et al. Using Generative Models for Handwritten Digit Recognition , 1996, IEEE Trans. Pattern Anal. Mach. Intell..
[20] Yoav Freund,et al. Experiments with a New Boosting Algorithm , 1996, ICML.
[21] Alan L. Yuille,et al. Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..
[22] Denis Fize,et al. Speed of processing in the human visual system , 1996, Nature.
[23] Alex Pentland,et al. Probabilistic Visual Learning for Object Representation , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[24] Takeo Kanade,et al. Neural Network-Based Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[25] Ellen K. Hughes,et al. Video OCR for digital news archive , 1998, Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database.
[26] Ellen K. Hughes,et al. Video OCR for Digital News Archives , 1998 .
[27] Anil K. Jain,et al. Automatic text location in images and video frames , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).
[28] Harry Wechsler,et al. The FERET database and evaluation procedure for face-recognition algorithms , 1998, Image Vis. Comput..
[29] Sean Dougherty,et al. Edge detector evaluation using empirical ROC curves , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).
[30] A. Yuille,et al. Two- and Three-Dimensional Patterns of the Face , 2001 .
[31] Dorin Comaniciu,et al. Mean shift analysis and applications , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[32] Narendra Ahuja,et al. Face detection using mixtures of linear subspaces , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).
[33] Takeo Kanade,et al. A statistical method for 3D object detection applied to faces and cars , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[34] Pietro Perona,et al. Towards automatic discovery of object categories , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[35] Pietro Perona,et al. Viewpoint-invariant learning and detection of human heads , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).
[36] J. Friedman. Special Invited Paper-Additive logistic regression: A statistical view of boosting , 2000 .
[37] John Odentrantz,et al. Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues , 2000, Technometrics.
[38] W. Freeman,et al. Generalized Belief Propagation , 2000, NIPS.
[39] Rong Zhang,et al. Integrating bottom-up/top-down for object recognition by data driven Markov chain Monte Carlo , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[40] Jitendra Malik,et al. Normalized Cuts and Image Segmentation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[41] Jitendra Malik,et al. Matching Shapes , 2001, ICCV.
[42] David A. Forsyth,et al. Learning the semantics of words and pictures , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[43] Harry Shum,et al. Image segmentation by data driven Markov chain Monte Carlo , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[44] Jitendra Malik,et al. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[45] Paul A. Viola,et al. Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade , 2001, NIPS.
[46] Jun S. Liu,et al. Monte Carlo strategies in scientific computing , 2001 .
[47] Timothy F. Cootes,et al. Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[48] Refractor. Vision , 2000, The Lancet.
[49] Sean Dougherty,et al. Edge Detector Evaluation Using Empirical ROC Curves , 2001, Comput. Vis. Image Underst..
[50] Hinrich Schütze,et al. Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.
[51] Zhuowen Tu,et al. Parsing Images into Region and Curve Processes , 2002, ECCV.
[52] Dan Klein,et al. A Generative Constituent-Context Model for Improved Grammar Induction , 2002, ACL.
[53] P. Perona,et al. Rapid natural scene categorization in the near absence of attention , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[54] 장윤희,et al. Y. , 2003, Industrial and Labor Relations Terms.
[55] James M. Rehg,et al. Learning a Rare Event Detection Cascade by Direct Feature Selection , 2003, NIPS.
[56] Alan L. Yuille,et al. Statistical Edge Detection: Learning and Evaluating Edge Cues , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[57] Song-Chun Zhu,et al. How Do Heuristics Expedite Markov Chain Search? Hitting-time Analysis of the Independence Metropolis Sampler , 2003 .
[58] Antonio Torralba,et al. Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes , 2003, NIPS.
[59] Adrian Barbu,et al. Graph partition by Swendsen-Wang cuts , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[60] Robert E. Schapire,et al. The Boosting Approach to Machine Learning An Overview , 2003 .
[61] Feng Han,et al. Bayesian reconstruction of 3D shapes and scenes from a single image , 2003, First IEEE International Workshop on Higher-Level Knowledge in 3D Modeling and Motion Analysis, 2003. HLK 2003..
[62] Martial Hebert,et al. Discriminative random fields: a discriminative framework for contextual interaction in classification , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[63] Jitendra Malik,et al. Contour and Texture Analysis for Image Segmentation , 2001, International Journal of Computer Vision.
[64] Alan L. Yuille,et al. Detecting and reading text in natural scenes , 2004, CVPR 2004.
[65] Alan L. Yuille,et al. AdaBoost Learning for Detecting and Reading Text in City Scenes , 2004, CVPR 2004.
[66] Multigrid and multi-level Swendsen-Wang cuts for hierarchic graph partition , 2004, CVPR 2004.
[67] Song-Chun Zhu,et al. Multigrid and multi-level Swendsen-Wang cuts for hierarchic graph partition , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[68] J. Ponce,et al. Towards true 3D object recognition , 2004 .
[69] David G. Lowe,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.
[70] Donald Geman,et al. Coarse-to-Fine Face Detection , 2004, International Journal of Computer Vision.
[71] Charless C. Fowlkes,et al. How Much Does Globalization Help Segmentation ? , 2004 .
[72] Zhuowen Tu,et al. Shape Matching and Recognition - Using Generative Models and Informative Features , 2004, ECCV.
[73] D. Geman,et al. Hierarchical testing designs for pattern recognition , 2005, math/0507421.
[74] Michael I. Jordan,et al. The DLR Hierarchy of Approximate Inference , 2005, UAI.
[75] Martial Hebert,et al. Discriminative Random Fields , 2006, International Journal of Computer Vision.
[76] Zhuowen Tu,et al. Parsing Images into Regions, Curves, and Curve Groups , 2006, International Journal of Computer Vision.
[77] A. Yuille,et al. Image Parsing: Unifying Segmentation, Detection, and Recognition , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.