The information you're looking for cannot be found, it may be temporarily unavailable or permanently removed. Try refreshing the page, or returning to ourIf the problem continues, please let us know.M. Pawan Kumar, P. Torr and A. Zisserman An Object Category Specific MRF for Segmentation Towards Category-Level Object Recognition M. Pawan Kumar, V. Kolmogorov and P. Torr Analyzing Convex Relaxations for MAP Estimation Advances in Markov Random Fields for Vision and Image Processing N. Komodakis, M. Pawan Kumar and N. Paragios (Hyper)-Graphs Inference through Convex Relaxations and Move Making Algorithms Foundations and Trends in Computer Graphics and Vision M. Pawan Kumar, P.H.S. Torr and A. Zisserman Learning Layered Motion Segmentations of Video In International Journal of Computer Vision (IJCV), 2008 P. Kohli, M. Pawan Kumar and P. Torr P^3 and Beyond: Move Making Algorithms for Solving Higher Order Functions In Pattern Analysis and Machine Intelligence (PAMI), 2009
An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs In Journal of Machine Learning Research (JMLR), 2009 M. Pawan Kumar, P. Torr and A. Zisserman OBJCUT: Efficient Segmentation using Top-Down and Bottom-Up Cues In Pattern Analysis and Machine Intelligence (PAMI), 2010 M. Pawan Kumar, O. Veksler and P. Torr Improved Moves for Truncated Convex Models In Journal of Machine Learning Research (JMLR), 2011 M. Pawan Kumar, H. Turki, D. Preston and D. Koller Parameter Estimation and Energy Minimization for Region-based Semantic Segmentation In Pattern Analysis and Machine Ingelligence (PAMI), 2015 A. Behl, P. Mohapatra, C.V. Jawahar and M. Pawan Kumar Optimizing Average Precision using Weakly Supervised Data M. Pawan Kumar and P. Dokania Rounding-based Moves for Semi-Metric Labeling In Journal of Machine Learning Research (JMLR), 2016 R. Bunel, A. Desmaison, P. Kohli, P. Torr and M. Pawan Kumar
In Proceedings of Advances in Neural Information Processing Systems (NIPS), 2016 D. Bouchacourt, M. Pawan Kumar and S. Nowozin DISCO Nets: DISsimilarity COefficient Networks Efficient Continuous Relaxations for Dense CRF In Proceedings of European Conference on Computer Vision (ECCV), 2016 P. Mohapatra, P. Dokania, C.V. Jawahar and M. Pawan Kumar Partial Linearization based Optimization for Multi-Class SVM J. Pritts, D. Rozumnyi, M. Pawan Kumar and O. Chum Coplanar Repeats by Energy Minimization In Proceedings of British Machine Vision Conference (BMVC), 2016 D. Bouchacourt, S. Nowozin and M. Pawan Kumar Entropy-based Latent Structured Prediction In Proceedings of International Conference on Computer Vision (ICCV), 2015 P. Dokania and M. Pawan Kumar P. Mohapatra, C. V. Jawahar and M. Pawan Kumar Efficient Optimization for Average Precision SVM In Proceedings of Advances in Neural Information Processing Systems (NIPS), 2014
Rounding-based Moves for Metric Labeling P. Dokania, A. Behl, C.V. Jawahar and M. Pawan Kumar Learning to Rank using High-Order Information In Proceedings of European Conference on Computer Vision (ECCV), 2014 A. Behl, C.V. Jawahar and M. Pawan Kumar In Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), 2014 P.-Y. Baudin, D. Goodman, P. Kumar, N. Azzabou, P.G. Carlier, N. Paragios and M. Pawan Kumar Discriminative Parameter Estimation for Random Walks Segmentation In Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013 W. Zaremba, M. Pawan Kumar, A. Gramfort and M. Blaschko Learning from M/EEG Data with Variable Brain Activation Delays In Proceedings of International Conference on Information Processing in Medical Imaging (IPMI), 2013 M. Pawan Kumar, B. Packer and D. Koller Modeling Latent Variable Uncertainty for Loss-based Learning
In Proceedings of International Conference on Machine Learning (ICML), 2012 K. Miller, M. Pawan Kumar, B. Packer, D. Goodman and D. Koller In Proceedings of Conference on Artificial Intelligence and Statistics (AISTATS), 2012 Learning Specific-Class Segmentation from Diverse Data In Proceedings of International Conference on Computer Vision (ICCV), 2011 Self-Paced Learning for Latent Variable Models In Proceedings of Advances in Neural Information Processing Systems (NIPS), 2010 M. Pawan Kumar and D. Koller Efficiently Selecting Regions for Scene Understanding In Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), 2010 P. Kohli and M. Pawan Kumar Energy Minimization for Linear Envelope MRFs Learning a Small Mixture of Trees In Proceedings of Advances in Neural Information Processing Systems (NIPS), 2009 M. Pawan Kumar, A. Zisserman and P. Torr Efficient Discriminative Learning of Parts-based Models
In Proceedings of International Conference on Computer Vision (ICCV), 2009 MAP Estimation of Semi-Metric MRFs via Hierarchical Graph Cuts In Proceedings of Conference on Uncertainity in Artificial Intelligence (UAI), 2009 M. Pawan Kumar and P. Torr In Proceedings of Advances in Neural Information Processing Systems (NIPS), 2008 Efficiently Solving Convex Relaxations for MAP Estimation In Proceedings of International Conference on Machine Learning (ICML), 2008 An Analysis of Convex Relaxations for MAP Estimation In Proceedings of Advances in Neural Information Processing Systems (NIPS), 2007 Honourable mention, best student paper award An Invariant Large Margin Nearest Neighbour Classifier In Proceedings of International Conference on Computer Vision (ICCV), 2007 P^3 and Beyond: Solving Energies with Higher Order Cliques In Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), 2007 Solving Markov Random Fields using Second Order Cone Programming Relaxations
In Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), 2006 Note: The algorithm presented in the above paper is dominated by the LP relaxation. Please see our NIPS 2007 paper for more details. Fast Memory-Efficient Generalized Belief Propagation In Proceedings of European Conference on Computer Vision (ECCV), 2006 Note: This is a new version with corrected claims. The algorithm is exact for the special case of hard constraints, and approximate otherwise. In Proceedings of International Conference on Computer Vision (ICCV), 2005 In Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), 2005 Learning Layered Pictorial Structures from Video In Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2004 IAPR best paper award at conference Extending Pictorial Structures for Object Recognition In Proceedings of British Machine Vision Conference (BMVC), 2004