Principled Parallel Mean-Field Inference for Discrete Random Fields
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Pascal Fua | François Fleuret | Pierre Baqué | Timur M. Bagautdinov | P. Fua | F. Fleuret | P. Baqué
[1] Iasonas Kokkinos,et al. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs , 2014, ICLR.
[2] Lena Gorelick,et al. Submodularization for Binary Pairwise Energies , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[3] Sebastian Nowozin,et al. Decision tree fields , 2011, 2011 International Conference on Computer Vision.
[4] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[5] Vladlen Koltun,et al. Parameter Learning and Convergent Inference for Dense Random Fields , 2013, ICML.
[6] Tiziana D'Orazio,et al. A Semi-automatic System for Ground Truth Generation of Soccer Video Sequences , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.
[7] Tom Minka,et al. Expectation Propagation for approximate Bayesian inference , 2001, UAI.
[8] Chong Wang,et al. Stochastic variational inference , 2012, J. Mach. Learn. Res..
[9] P. Cochat,et al. Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[10] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[11] Jan Kautz,et al. Fully-Connected CRFs with Non-Parametric Pairwise Potential , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[12] Rainer Stiefelhagen,et al. Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics , 2008, EURASIP J. Image Video Process..
[13] Sebastian Nowozin,et al. A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems , 2014, International Journal of Computer Vision.
[14] Takayuki Okatani,et al. Application of the mean field methods to MRF optimization in computer vision , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Boris Polyak. Some methods of speeding up the convergence of iteration methods , 1964 .
[16] Pascal Fua,et al. Multi-Commodity Network Flow for Tracking Multiple People , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[17] Michael I. Jordan,et al. Loopy Belief Propagation for Approximate Inference: An Empirical Study , 1999, UAI.
[18] Vladimir Kolmogorov,et al. A New Look at Reweighted Message Passing , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[19] Pascal Fua,et al. Kullback-Leibler Proximal Variational Inference , 2015, NIPS.
[20] Ambuj Tewari,et al. Composite objective mirror descent , 2010, COLT 2010.
[21] VekslerOlga,et al. Fast Approximate Energy Minimization via Graph Cuts , 2001 .
[22] Vibhav Vineet,et al. Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces , 2012, International Journal of Computer Vision.
[23] Charles M. Bishop,et al. Variational Message Passing , 2005, J. Mach. Learn. Res..
[24] Pascal Fua,et al. Probability occupancy maps for occluded depth images , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Shun-ichi Amari,et al. Natural Gradient Works Efficiently in Learning , 1998, Neural Computation.
[26] Jianguo Zhang,et al. The PASCAL Visual Object Classes Challenge , 2006 .
[27] Michael I. Jordan,et al. Graphical Models, Exponential Families, and Variational Inference , 2008, Found. Trends Mach. Learn..
[28] Vibhav Vineet,et al. Conditional Random Fields as Recurrent Neural Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[29] Christopher D. Manning,et al. Simple MAP Inference via Low-Rank Relaxations , 2014, NIPS.
[30] Marc Teboulle,et al. Entropic Proximal Mappings with Applications to Nonlinear Programming , 1992, Math. Oper. Res..
[31] Vladlen Koltun,et al. Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials , 2011, NIPS.
[32] Olga Veksler,et al. Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[33] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[34] Adrian F. M. Smith,et al. Sampling-Based Approaches to Calculating Marginal Densities , 1990 .
[35] ZissermanAndrew,et al. The Pascal Visual Object Classes Challenge , 2015 .
[36] FuaPascal,et al. Multicamera People Tracking with a Probabilistic Occupancy Map , 2008 .
[37] Vincent Lepetit,et al. Real-time landing place assessment in man-made environments , 2013, Machine Vision and Applications.