| A comparative study of energy minimization methods for markov random fields with smoothness-based priors R Szeliski, R Zabih, D Scharstein, O Veksler, V Kolmogorov, A Agarwala, ... IEEE transactions on pattern analysis and machine intelligence 30 (6), 1068-1080, 2008 | 1229 | 2008 |
| Comparison of graph cuts with belief propagation for stereo, using identical MRF parameters MF Tappen, WT Freeman Computer Vision, IEEE International Conference on 3, 900-900, 2003 | 620 | 2003 |
| Sparse convolutional neural networks B Liu, M Wang, H Foroosh, M Tappen, M Pensky Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 588 | 2015 |
| A comparative study of energy minimization methods for markov random fields R Szeliski, R Zabih, D Scharstein, O Veksler, V Kolmogorov, A Agarwala, ... European conference on computer vision, 16-29, 2006 | 484 | 2006 |
| Recovering intrinsic images from a single image MF Tappen, WT Freeman, EH Adelson IEEE transactions on pattern analysis and machine intelligence 27 (9), 1459-1472, 2005 | 410 | 2005 |
| Markov random fields for vision and image processing A Blake, P Kohli, C Rother MIT press, 2011 | 311 | 2011 |
| Exploring the trade-off between accuracy and observational latency in action recognition C Ellis, SZ Masood, MF Tappen, JJ LaViola, R Sukthankar International Journal of Computer Vision 101 (3), 420-436, 2013 | 270 | 2013 |
| Learning to recognize shadows in monochromatic natural images J Zhu, KGG Samuel, SZ Masood, MF Tappen 2010 IEEE Computer Society conference on computer vision and pattern …, 2010 | 217 | 2010 |
| Exploiting the sparse derivative prior for super-resolution and image demosaicing MFTBC Russell, WT Freeman Proc. Third Int'l Workshop Statistical and Computational Theories of Vision, 2003 | 210 | 2003 |
| Learning gaussian conditional random fields for low-level vision MF Tappen, C Liu, EH Adelson, WT Freeman 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007 | 188 | 2007 |
| Learning pedestrian dynamics from the real world P Scovanner, MF Tappen 2009 IEEE 12th International Conference on Computer Vision, 381-388, 2009 | 155 | 2009 |
| Recovering intrinsic images from a single image MF Tappen, WT Freeman, EH Adelson | 147 | 2002 |
| Image processing and analysis with graphs: theory and practice O Lézoray, L Grady CRC Press, 2012 | 143 | 2012 |
| Context-constrained hallucination for image super-resolution J Sun, J Zhu, MF Tappen 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 127 | 2010 |
| Estimating intrinsic component images using non-linear regression MF Tappen, EH Adelson, WT Freeman 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006 | 122 | 2006 |
| Latent pyramidal regions for recognizing scenes F Sadeghi, MF Tappen European conference on computer vision, 228-241, 2012 | 96 | 2012 |
| Probabilistic label trees for efficient large scale image classification B Liu, F Sadeghi, M Tappen, O Shamir, C Liu Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 92 | 2013 |
| Learning optimized MAP estimates in continuously-valued MRF models KGG Samuel, MF Tappen 2009 IEEE Conference on Computer Vision and Pattern Recognition, 477-484, 2009 | 86 | 2009 |
| Utilizing variational optimization to learn markov random fields MF Tappen 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007 | 84 | 2007 |
| A Bayesian approach to alignment-based image hallucination MF Tappen, C Liu European conference on computer vision, 236-249, 2012 | 71 | 2012 |
