| Fast binary feature selection with conditional mutual information. F Fleuret Journal of Machine learning research 5 (9), 2004 | 1201 | 2004 |
| Multiple object tracking using k-shortest paths optimization J Berclaz, F Fleuret, E Turetken, P Fua IEEE transactions on pattern analysis and machine intelligence 33 (9), 1806-1819, 2011 | 1182 | 2011 |
| Multicamera people tracking with a probabilistic occupancy map F Fleuret, J Berclaz, R Lengagne, P Fua IEEE transactions on pattern analysis and machine intelligence 30 (2), 267-282, 2007 | 988 | 2007 |
| Transformers are rnns: Fast autoregressive transformers with linear attention A Katharopoulos, A Vyas, N Pappas, F Fleuret International Conference on Machine Learning, 5156-5165, 2020 | 389 | 2020 |
| Coarse-to-fine face detection F Fleuret, D Geman International Journal of computer vision 41 (1), 85-107, 2001 | 380 | 2001 |
| Tracking multiple people under global appearance constraints HB Shitrit, J Berclaz, F Fleuret, P Fua 2011 International conference on computer vision, 137-144, 2011 | 307 | 2011 |
| Robust people tracking with global trajectory optimization J Berclaz, F Fleuret, P Fua 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006 | 279 | 2006 |
| Not all samples are created equal: Deep learning with importance sampling A Katharopoulos, F Fleuret International conference on machine learning, 2525-2534, 2018 | 268 | 2018 |
| Multi-commodity network flow for tracking multiple people HB Shitrit, J Berclaz, F Fleuret, P Fua IEEE transactions on pattern analysis and machine intelligence 36 (8), 1614-1627, 2013 | 197 | 2013 |
| Exact acceleration of linear object detectors C Dubout, F Fleuret European Conference on Computer Vision, 301-311, 2012 | 188 | 2012 |
| Social scene understanding: End-to-end multi-person action localization and collective activity recognition T Bagautdinov, A Alahi, F Fleuret, P Fua, S Savarese Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 180 | 2017 |
| Multiple object tracking using flow linear programming J Berclaz, F Fleuret, P Fua Performance Evaluation of Tracking and Surveillance (PETS-Winter), 2009 …, 2009 | 175 | 2009 |
| Scalable metric learning via weighted approximate rank component analysis C Jose, F Fleuret European conference on computer vision, 875-890, 2016 | 154 | 2016 |
| Comparing machines and humans on a visual categorization test F Fleuret, T Li, C Dubout, EK Wampler, S Yantis, D Geman Proceedings of the National Academy of Sciences 108 (43), 17621-17625, 2011 | 128 | 2011 |
| Feature harvesting for tracking-by-detection M Özuysal, V Lepetit, F Fleuret, P Fua European conference on computer vision, 592-605, 2006 | 127 | 2006 |
| Tracking interacting objects using intertwined flows X Wang, E Türetken, F Fleuret, P Fua IEEE transactions on pattern analysis and machine intelligence 38 (11), 2312 …, 2015 | 121 | 2015 |
| Tracking interacting objects optimally using integer programming X Wang, E Türetken, F Fleuret, P Fua European Conference on Computer Vision, 17-32, 2014 | 121 | 2014 |
| Full-gradient representation for neural network visualization S Srinivas, F Fleuret Advances in neural information processing systems 32, 2019 | 107 | 2019 |
| Non-Mercer Kernels for SVM Object Recognition. S Boughorbel, JP Tarel, F Fleuret BMVC, 1-10, 2004 | 106 | 2004 |
| Knowledge transfer with jacobian matching S Srinivas, F Fleuret International Conference on Machine Learning, 4723-4731, 2018 | 104 | 2018 |
Pascal FuaProfessor Computer Science, EPFLVerified email at epfl.ch
