| Self-paced learning for latent variable models M Kumar, B Packer, D Koller Advances in neural information processing systems 23, 2010 | 1364 | 2010 |
| Objcut: Efficient segmentation using top-down and bottom-up cues MP Kumar, PHS Torr, A Zisserman Pattern Analysis and Machine Intelligence, IEEE Transactions on 32 (3), 530-545, 2010 | 654* | 2010 |
| P³ & Beyond: Move Making Algorithms for Solving Higher Order Functions P Kohli, MP Kumar, PHS Torr Pattern Analysis and Machine Intelligence, IEEE Transactions on 31 (9), 1645 …, 2009 | 458* | 2009 |
| A unified view of piecewise linear neural network verification RR Bunel, I Turkaslan, P Torr, P Kohli, PK Mudigonda Advances in Neural Information Processing Systems 31, 2018 | 352* | 2018 |
| Learning layered motion segmentations of video MP Kumar, PHS Torr, A Zisserman Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 1 …, 2005 | 240 | 2005 |
| Efficiently selecting regions for scene understanding MP Kumar, D Koller 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 181 | 2010 |
| Parameter estimation and energy minimization for region-based semantic segmentation MP Kumar, H Turki, D Preston, D Koller IEEE transactions on pattern analysis and machine intelligence 37 (7), 1373-1386, 2014 | 120* | 2014 |
| An analysis of convex relaxations for MAP estimation of discrete MRFs MP Kumar, V Kolmogorov, PHS Torr The Journal of Machine Learning Research 10, 71-106, 2009 | 119* | 2009 |
| Branch and bound for piecewise linear neural network verification R Bunel, P Mudigonda, I Turkaslan, P Torr, J Lu, P Kohli Journal of Machine Learning Research 21 (2020), 2020 | 118 | 2020 |
| Efficient discriminative learning of parts-based models MP Kumar, A Zisserman, PHS Torr 2009 IEEE 12th International Conference on Computer Vision, 552-559, 2009 | 117 | 2009 |
| Extending pictorial structures for object recognition MP Kumar, PHS Torr, A Zisserman Proc. BMVC, 81.1-81.10, 2004 | 103 | 2004 |
| Smooth loss functions for deep top-k classification L Berrada, A Zisserman, MP Kumar arXiv preprint arXiv:1802.07595, 2018 | 97 | 2018 |
| Dissimilarity coefficient based weakly supervised object detection A Arun, CV Jawahar, MP Kumar Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 88 | 2019 |
| Improved moves for truncated convex models MP Kumar, O Veksler, PHS Torr The Journal of Machine Learning Research 12, 31-67, 2011 | 76 | 2011 |
| A statistical approach to assessing neural network robustness S Webb, T Rainforth, YW Teh, MP Kumar arXiv preprint arXiv:1811.07209, 2018 | 73 | 2018 |
| Energy minimization for linear envelope MRFs P Kohli, MP Kumar 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 72 | 2010 |
| Hybrid models for learning to branch P Gupta, M Gasse, E Khalil, P Mudigonda, A Lodi, Y Bengio Advances in neural information processing systems 33, 18087-18097, 2020 | 70 | 2020 |
| Solving Markov random fields using second order cone programming relaxations MP Kumar, PHS Torr, A Zisserman Computer Vision and Pattern Recognition, 2006 IEEE Computer Society …, 2006 | 64 | 2006 |
| Learning class-specific edges for object detection and segmentation M Prasad, A Zisserman, A Fitzgibbon, MP Kumar, PHS Torr Computer Vision, Graphics and Image Processing: 5th Indian Conference …, 2006 | 63 | 2006 |
| Disco nets: Dissimilarity coefficients networks D Bouchacourt, PK Mudigonda, S Nowozin Advances in Neural Information Processing Systems 29, 2016 | 61 | 2016 |
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
