François Fleuret

Picture of Francois Fleuret, March 20th, 2014.

E-mail
francois.fleuret@idiap.ch (pgp key)
Offices
Idiap 309 / EPFL ELE131
Phone
+41 27 721 7739
Address
Idiap Research Institute
Centre du Parc
Rue Marconi, 19
1920 Martigny
Switzerland

I am the head of the Machine Learning group at the Idiap research institute, and adjunct faculty at the École Polytechnique Fédérale de Lausanne.

My research is supported by the Swiss National Science Foundation, the Hasler Foundation, the Swiss Commission for Technology and Innovation, the Ark foundation, the European Commission, and through direct industrial collaborations.

News

Selected papers

S. Tulyakov, A. Ivanov, and F. Fleuret. Weakly Supervised Learning of Deep Metrics for Stereo Reconstruction. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017. (To appear). bib · pdf

P. Baqué, F. Fleuret, and P. Fua. Deep Occlusion Reasoning for Multi-Camera Multi-Target Detection. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017. (To appear). bib · pdf

J. Newling and F. Fleuret. A Sub-Quadratic Exact Medoid Algorithm. In Proceedings of the international conference on Artificial Intelligence and Statistics (AISTATS), pages 185–193, 2017. (Best paper award). bib · pdf

T. Bagautdinov, A. Alahi, F. Fleuret, P. Fua, and S. Savarese. Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), 2017. (To appear). bib · pdf

L. Lefakis and F. Fleuret. Jointly Informative Feature Selection Made Tractable by Gaussian Modeling. Journal of Machine Learning Research (JMLR), 17(182):1–39, 2016. bib · pdf

F. Fleuret. Predicting the dynamics of 2d objects with a deep residual network. CoRR, abs/1610.04032, 2016. bib · pdf

C. Jose and F. Fleuret. Scalable Metric Learning via Weighted Approximate Rank Component Analysis. In Proceedings of the European Conference on Computer Vision (ECCV), pages 875–890, 2016. bib · pdf

O. Canévet, C. Jose, and F. Fleuret. Importance Sampling Tree for Large-scale Empirical Expectation. In Proceedings of the International Conference on Machine Learning (ICML), pages 1454–1462, 2016. bib · pdf

O. Canévet and F. Fleuret. Large Scale Hard Sample Mining with Monte Carlo Tree Search. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 5128–5137, 2016. bib · pdf

F. Fleuret, T. Li, C. Dubout, E. K. Wampler, S. Yantis, and D. Geman. Comparing machines and humans on a visual categorization test. Proceedings of the National Academy of Sciences (PNAS), 108(43):17621–17625, 2011. bib · pdf

F. Fleuret and D. Geman. Stationary Features and Cat Detection. Journal of Machine Learning Research (JMLR), 9:2549–2578, 2008. bib · pdf

F. Fleuret. Fast Binary Feature Selection with Conditional Mutual Information. Journal of Machine Learning Research (JMLR), 5:1531–1555, 2004. bib · pdf

F. Fleuret and D. Geman. Coarse-to-fine Face Detection. International Journal of Computer Vision (IJCV), 41(1/2):85–107, 2001. bib · ps · pdf