Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
暂无分享,去创建一个
[1] Nikos Komodakis,et al. Beyond pairwise energies: Efficient optimization for higher-order MRFs , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[2] Egon Balas,et al. Projection, Lifting and Extended Formulation in Integer and Combinatorial Optimization , 2005, Ann. Oper. Res..
[3] Alexander Schrijver,et al. Theory of linear and integer programming , 1986, Wiley-Interscience series in discrete mathematics and optimization.
[4] Pushmeet Kohli,et al. Robust Higher Order Potentials for Enforcing Label Consistency , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[5] Dimitris Samaras,et al. Topology cuts: A novel min-cut/max-flow algorithm for topology preserving segmentation in N-D images , 2008, Comput. Vis. Image Underst..
[6] Vladimir Kolmogorov,et al. An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision , 2001, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Martin J. Wainwright,et al. MAP estimation via agreement on (hyper)trees: Message-passing and linear programming , 2005, ArXiv.
[8] Yair Weiss,et al. Linear Programming Relaxations and Belief Propagation - An Empirical Study , 2006, J. Mach. Learn. Res..
[9] Dorin Comaniciu,et al. Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[10] Yair Weiss,et al. MAP Estimation, Linear Programming and Belief Propagation with Convex Free Energies , 2007, UAI.
[11] Vladimir Kolmogorov,et al. Graph cut based image segmentation with connectivity priors , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[12] Vladimir Kolmogorov,et al. An Analysis of Convex Relaxations for MAP Estimation , 2007, NIPS.
[13] Amir Globerson,et al. Convergent message passing algorithms - a unifying view , 2009, UAI.
[14] Thomas Hofmann,et al. Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..
[15] Olga Veksler,et al. Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[16] Sebastian Nowozin,et al. Global connectivity potentials for random field models , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[17] Tomás Werner,et al. A Linear Programming Approach to Max-Sum Problem: A Review , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[19] Greg Mori,et al. Guiding model search using segmentation , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[20] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[21] Olga Veksler,et al. Semiautomatic segmentation with compact shape prior , 2009, Image Vis. Comput..
[22] Thorsten Joachims,et al. Cutting-plane training of structural SVMs , 2009, Machine Learning.
[23] Pushmeet Kohli,et al. Exact inference in multi-label CRFs with higher order cliques , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[24] Vladimir Kolmogorov,et al. On partial optimality in multi-label MRFs , 2008, ICML '08.
[25] Pushmeet Kohli,et al. Minimizing sparse higher order energy functions of discrete variables , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[26] Vladimir Kolmogorov,et al. Convergent Tree-Reweighted Message Passing for Energy Minimization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Dimitri P. Bertsekas,et al. Nonlinear Programming , 1997 .
[28] Daniel P. Huttenlocher,et al. Learning for stereo vision using the structured support vector machine , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[29] Tommi S. Jaakkola,et al. New Outer Bounds on the Marginal Polytope , 2007, NIPS.
[30] Tommi S. Jaakkola,et al. Tightening LP Relaxations for MAP using Message Passing , 2008, UAI.
[31] Jitendra Malik,et al. Learning a classification model for segmentation , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[32] Benno Schwikowski,et al. Discovering regulatory and signalling circuits in molecular interaction networks , 2002, ISMB.
[33] Martin J. Wainwright,et al. MAP estimation via agreement on trees: message-passing and linear programming , 2005, IEEE Transactions on Information Theory.
[34] Stan Z. Li,et al. Markov Random Field Models in Computer Vision , 1994, ECCV.
[35] Chih-Jen Lin,et al. A dual coordinate descent method for large-scale linear SVM , 2008, ICML '08.
[36] Vladimir Kolmogorov,et al. What energy functions can be minimized via graph cuts? , 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[37] Tommi S. Jaakkola,et al. Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations , 2007, NIPS.
[38] Ben Taskar,et al. An Introduction to Conditional Random Fields for Relational Learning , 2007 .
[39] Nir Friedman,et al. Probabilistic Graphical Models - Principles and Techniques , 2009 .
[40] G. Nemhauser,et al. Integer Programming , 2020 .
[41] John N. Tsitsiklis,et al. Introduction to linear optimization , 1997, Athena scientific optimization and computation series.
[42] Thorsten Joachims,et al. Training structural SVMs when exact inference is intractable , 2008, ICML '08.
[43] Christoph H. Lampert,et al. Learning to Localize Objects with Structured Output Regression , 2008, ECCV.
[44] Philip H. S. Torr,et al. Efficiently solving convex relaxations for MAP estimation , 2008, ICML '08.
[45] Pushmeet Kohli,et al. P3 & Beyond: Solving Energies with Higher Order Cliques , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[46] Nikos Komodakis,et al. Beyond Loose LP-Relaxations: Optimizing MRFs by Repairing Cycles , 2008, ECCV.
[47] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[48] Jianguo Zhang,et al. The PASCAL Visual Object Classes Challenge , 2006 .
[49] Derek Hoiem,et al. Learning CRFs Using Graph Cuts , 2008, ECCV.
[50] Luc Van Gool,et al. Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..
[51] Tomás Werner,et al. High-arity interactions, polyhedral relaxations, and cutting plane algorithm for soft constraint optimisation (MAP-MRF) , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[52] Nikos Komodakis,et al. MRF Optimization via Dual Decomposition: Message-Passing Revisited , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[53] Binoy Pinto,et al. Speeded Up Robust Features , 2011 .