You can download the complete bibtex file fleuret.bib, or check my Google Scholar and arXiv pages.
M. Pagliardini, A. Mohtashami, F. Fleuret, and M. Jaggi. DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), 2024. bib · pre
E. Alonso, A. Jelley, V. Micheli, A. Kanervisto, A. Storkey, T. Pearce, and F. Fleuret. Diffusion for World Modeling: Visual Details Matter in Atari. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), 2024. bib · pre
A. Sinha and F. Fleuret. DeepEMD: A Transformer-based Fast Estimation of the Earth Mover’s Distance. In Proceedings of the IEEE International Conference on Pattern Recognition (ICPR), 2024. bib · pdf
A. Pannatier, E. Courdier, and F. Fleuret. σ-GPTs: A New Approach to Autoregressive Models. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 2024. to appear. bib · pre
V. Micheli, E. Alonso, and F. Fleuret. Efficient World Models with Time-Aware and Context-Augmented Tokenization. In Proceedings of the International Conference on Machine Learning (ICML), 2024. to appear. bib · pre
K. Wang, N. Dimitriadis, G. Ortiz-Jimenez, F. Fleuret, and P. Frossard. Localizing Task Information for Improved Model Merging and Compression. In Proceedings of the International Conference on Machine Learning (ICML), 2024. to appear. bib · pre
A. Pannatier, K. Matoba, and F. Fleuret. Inference from Real-World Sparse Measurements. Transactions on Machine Learning Research (TMLR), 2024. bib · pre
K. Matoba, N. Dimitriadis, and F. Fleuret. Benefits of Max Pooling in Neural Networks: Theoretical and Experimental Evidence. Transactions on Machine Learning Research (TMLR), 2023. bib · pdf
M. Pagliardini, D. Paliotta, M. Jaggi, and F. Fleuret. Faster Causal Attention Over Large Sequences Through Sparse Flash Attention. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), pages 59808–59831, 2023. bib · pdf
A. Sinha, D. Paliotta, B. Máté, J. Raine, T. Golling, and F. Fleuret. SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics. In Proceedings of the international conference on Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS), pages 64829–64856, 2023. bib · pdf
S. Kandul, V. Micheli, J. Beck, T. Burri, F. Fleuret, M. Kneer, and M. Christen. Human control redressed: Comparing AI and human predictability in a real-effort task. Computers in Human Behavior Reports, 10:100290, 2023. bib · pdf
B. Máté and F. Fleuret. Learning Interpolations between Boltzmann Densities. Transactions on Machine Learning Research (TMLR), 2023. bib · pdf
F. Mai, A. Pannatier, F. Fehr, H. Chen, F. Marelli, F. Fleuret, and J. Henderson. HyperMixer: An MLP-based Low Cost Alternative to Transformers. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2023. bib · pdf
N. Dimitriadis, P. Frossard, and F. Fleuret. Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models. In Proceedings of the International Conference on Machine Learning (ICML), 2023. bib · pdf
F. Fleuret. The Little Book of Deep Learning. lulu.com, 2023. bib · pdf
M. Johari, C. Carta, and F. Fleuret. ESLAM: Efficient Dense SLAM System Based on Hybrid Representation of Signed Distance Fields. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), 2023. bib · pdf
V. Micheli, E. Alonso, and F. Fleuret. Transformers are Sample Efficient World Models. In Proceedings of the International Conference on Learning Representations (ICLR), 2023. bib · pdf
M. Pagliardini, M. Jaggi, F. Fleuret, and S. P. Karimireddy. Agree to Disagree: Diversity through Disagreement for Better Transferability. In Proceedings of the International Conference on Learning Representations (ICLR), 2023. bib · pdf
E. Courdier, T. Prabhu, and F. Fleuret. PAUMER: Patch Pausing Transformer for Semantic Segmentation. In Proceedings of the British Machine Vision Conference (BMVC), 2022. bib · pdf
S. Srinivas, K. Matoba, H. Lakkaraju, and F. Fleuret. Flatten the Curve: Efficiently Training Low-Curvature Neural Networks. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), pages 25951–25964, 2022. bib · pdf
B. Máté, S. Klein, T. Golling, and F. Fleuret. Flowification: Everything is a normalizing flow. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), 2022. bib · pdf
E. Courdier and F. Fleuret. Borrowing from yourself: Faster future video segmentation with partial channel update. In Proceedings of the IEEE International Conference on Pattern Recognition (ICPR), pages 1–8, 2022. bib · pdf
M. Johari, Y. Lepoittevin, and F. Fleuret. GeoNeRF: Generalizing NeRF with Geometry Priors. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), 2022. bib · pdf
A. Pannatier, R. Picatoste, and F. Fleuret. Efficient Wind Speed Nowcasting with GPU-Accelerated Nearest Neighbors Algorithm. In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022. bib · pdf
A. Kanervisto, S. Milani, K. Ramanauskas, N. Topin, Z. Lin, J. Li, J. Shi, D. Ye, Q. Fu, W. Yang, W. Hong, Z. Huang, H. Chen, G. Zeng, Y. Lin, V. Micheli, E. Alonso, F. Fleuret, A. Nikulin, Y. Belousov, O. Svidchenko, and A. Shpilman. MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned. In Proceedings of the NeurIPS Competitions and Demonstrations Track, pages 13–28, 2022. bib · pdf
V. Micheli and F. Fleuret. Language Models are Few-Shot Butlers. In Proceedings of the international conference on Empirical Methods in Natural Language Processing (EMLNP), pages 9312–9318, 2021. bib · pdf
M. Johari, C. Carta, and F. Fleuret. DepthInSpace: Exploitation and Fusion of Multiple Video Frames for Structured-Light Depth Estimation. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), pages 6039–6048, 2021. bib · pdf
T. Prabhu and F. Fleuret. Uncertainty Reduction for Model Adaptation in Semantic Segmentation. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 9613–9623, 2021. bib · pdf
T. Prabhu and F. Fleuret. Test time Adaptation through Perturbation Robustness. In Proceedings of the NeurIPS DistShift Workshop (NeurIPS DistShift), 2021. bib · pdf
S. Srinivas and F. Fleuret. Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability. In Proceedings of the International Conference on Learning Representations (ICLR), 2021. bib · pdf
T. Chavdarova, M. Pagliardini, S. Stich, F. Fleuret, and M. Jaggi. Taming GANs with Lookahead-Minmax. In Proceedings of the International Conference on Learning Representations (ICLR), 2021. bib · pdf
A. Vyas, A. Katharopoulos, and F. Fleuret. Fast Transformers with Clustered Attention. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), pages 21665–21674, 2020. bib · pdf
V. Micheli, M. d'Hoffschmidt, and F. Fleuret. On the importance of pre-training data volume for compact language models. In Proceedings of the international Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 7853–7858, 2020. bib · pdf
K. Matoba and F. Fleuret. Exact Preimages of Neural Network Aircraft Collision Avoidance Systems. In Machine Learning for Engineering Modeling, Simulation, and Design Workshop at NeurIPS, 2020. bib · pdf
E. Courdier and F. Fleuret. Real-Time Segmentation Networks should be Latency Aware. In Proceedings of the Asian Conference on Computer Vision (ACCV), pages 603–619, 2020. bib · pdf
T. Prabhu, F. Mai, T. Vogels, M. Jaggi, and F. Fleuret. Optimizer Benchmarking Needs to Account for Hyperparameter Tuning. In Proceedings of the International Conference on Machine Learning (ICML), pages 8837–8846, 2020. bib · pdf
A. Katharopoulos, A. Vyas, N. Pappas, and F. Fleuret. Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention. In Proceedings of the International Conference on Machine Learning (ICML), pages 5294–5303, 2020. bib · pdf
T. Chavdarova, G. Gidel, F. Fleuret, and S. Lacoste-Julien. Reducing Noise in GAN Training with Variance Reduced Extragradient. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), pages 391–401, 2019. bib · pdf
S. Srinivas and F. Fleuret. Full-Gradient Representation for Neural Network Visualization. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), pages 4126–4135, 2019. bib · pdf
S. Tulyakov, F. Fleuret, M. Kiefel, P. Gehler, and M. Hirsch. Learning an event sequence embedding for event-based deep stereo. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), pages 1527–1537, 2019. bib · pdf
A. Katharopoulos and F. Fleuret. Processing Megapixel Images with Deep Attention-Sampling Models. In Proceedings of the International Conference on Machine Learning (ICML), pages 3282–3291, 2019. bib · pdf
S. Tulyakov, A. Ivanov, and F. Fleuret. Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS), pages 5874–5884, 2018. bib · pdf
C. Jose, M. Cissé, and F. Fleuret. Kronecker Recurrent Units. In Proceedings of the International Conference on Machine Learning (ICML), pages 2380–2389, 2018. bib · pdf
S. Srinivas and F. Fleuret. Knowledge Transfer with Jacobian Matching. In Proceedings of the International Conference on Machine Learning (ICML), pages 4723–4731, 2018. bib · pdf
A. Katharopoulos and F. Fleuret. Not All Samples Are Created Equal: Deep Learning with Importance Sampling. In Proceedings of the International Conference on Machine Learning (ICML), pages 2525–2534, 2018. bib · pdf
P. Baqué, E. Remelli, F. Fleuret, and P. Fua. Geodesic Convolutional Shape Optimization. In Proceedings of the International Conference on Machine Learning (ICML), pages 472–481, 2018. bib · pdf
T. Chavdarova and F. Fleuret. SGAN: An Alternative Training of Generative Adversarial Networks. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 9407–9415, 2018. bib · pdf
T. Chavdarova, P. Baqué, S. Bouquet, A. Maksai, C. Jose, T. Bagautdinov, L. Lettry, P. Fua, L. Van Gool, and F. Fleuret. WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 5030–5039, 2018. bib · pdf
S. Tulyakov, A. Ivanov, N. Thomas, V. Roloff, A. Pommerol, G. Cremonese, T. Weigel, and F. Fleuret. Geometric calibration of Colour and Stereo Surface Imaging System of ESA's Trace Gas Orbiter. Advances in Space Research, 61(1):487–496, 2018. bib · pdf
J. Newling and F. Fleuret. K-Medoids For K-Means Seeding. In Proceedings of the international conference on Neural Information Processing Systems (NIPS), pages 5195–5203, 2017. bib · pdf
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), pages 1348–1357, 2017. 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), pages 271–279, 2017. bib · pdf
A. Maksai, X. Wang, F. Fleuret, and P. Fua. Non-Markovian Globally Consistent Multi-Object Tracking. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), pages 2563–2573, 2017. bib · pdf
T. Chavdarova and F. Fleuret. Deep Multi-Camera People Detection. In Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA), pages 848–853, 2017. bib · pdf
S. Abbasi-Sureshjani, B. Dasht Bozorg, B. M. ter Haar Romeny, and F. Fleuret. Boosted Exudate Segmentation in Retinal Images using Residual Nets. In Proceedings of the MICCAI Workshop on Ophthalmic Medical Image Analysis (OMIA), pages 210–218, 2017. bib · pdf
P. Baqué, F. Fleuret, and P. Fua. Multi-Modal Mean-Fields via Cardinality-Based Clamping. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 271–279, 2017. 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), pages 3425–3434, 2017. 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
S. Abbasi-Sureshjani, B. Dasht Bozorg, B. M. ter Haar Romeny, and F. Fleuret. Exploratory Study on Direct Prediction of Diabetes using Deep Residual Networks. In Proceedings of the thematic conference on computational vision and medical image processing (VipIMAGE), pages 797–802, 2017. bib · pdf
R. Lefort, L. Fusco, O. Pertz, and F. Fleuret. Machine learning-based tools to model and to remove the off-target effect. Pattern Analysis and Applications (PAA), 20(1):87–100, 2017. bib · pdf
F. Fleuret. Predicting the dynamics of 2d objects with a deep residual network. CoRR, abs/1610.04032, 2016. bib · pdf
J. Newling and F. Fleuret. Fast mini-batch k-means by nesting. In Proceedings of the international conference on Neural Information Processing Systems (NIPS), pages 1352–1360, 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
J. Newling and F. Fleuret. Fast k-means with accurate bounds. In Proceedings of the International Conference on Machine Learning (ICML), pages 936–944, 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
P. Baqué, T. Bagautdinov, F. Fleuret, and P. Fua. Principled Parallel Mean-Field Inference for Discrete Random Fields. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 5848–5857, 2016. 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
X. Wang, E. Turetken, F. Fleuret, and P. Fua. Tracking Interacting Objects Using Intertwined Flows. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 38(11):2312–2326, 2016. bib · pdf
L. Fusco, R. Lefort, K. Smith, F. Benmansour, G. Gonzalez, C. Barilari, B. Rinn, F. Fleuret, P. Fua, and O. Pertz. Computer vision profiling of neurite outgrowth dynamics reveals spatio-temporal modularity of Rho GTPase signaling. Journal of Cell Biology, 212(1):91–111, 2016. bib · pdf
N. Suditu and F. Fleuret. Adaptive relevance feedback for large-scale image retrieval. Multimedia Tools and Applications (MTA), 75(12):6777–6807, 2016. bib · pdf
E. Khan, P. Baqué, F. Fleuret, and P. Fua. Kullback-Leibler Proximal Variational Inference. In Proceedings of the international conference on Neural Information Processing Systems (NIPS), pages 3402–3410, 2015. bib · pdf
T. Bagautdinov, F. Fleuret, and P. Fua. Probability Occupancy Maps for Occluded Depth Images. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 2829–2837, 2015. bib · pdf
O. Canévet and F. Fleuret. Efficient Sample Mining for Object Detection. In Proceedings of the Asian Conference on Machine Learning (ACML), pages 48–63, 2014. bib · pdf
O. Canévet, L. Lefakis, and F. Fleuret. Sample Distillation for Object Detection and Image Classification. In Proceedings of the Asian Conference on Machine Learning (ACML), pages 64–79, 2014. bib · pdf
A. Penate Sanchez, F. Moreno-Noguer, J. Andrade Cetto, and F. Fleuret. LETHA: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images. In Proceedings of the International Conference on 3D vision (3DV), volume 1, pages 517–524, 2014. bib · pdf
X. Wang, E. Turetken, F. Fleuret, and P. Fua. Tracking Interacting Objects Optimally Using Integer Programming. In Proceedings of the European Conference on Computer Vision (ECCV), pages 17–32, 2014. bib · pdf
L. Lefakis and F. Fleuret. Dynamic Programming Boosting for Discriminative Macro-Action Discovery. In Proceedings of the International Conference on Machine Learning (ICML), pages 1548–1556, 2014. bib · pdf
C. Dubout and F. Fleuret. Adaptive Sampling for Large Scale Boosting. Journal of Machine Learning Research (JMLR), 15:1431–1453, 2014. bib · pdf
L. Lefakis and F. Fleuret. Jointly Informative Feature Selection. In Proceedings of the international conference on Artificial Intelligence and Statistics (AISTATS), pages 567–575, 2014. bib · pdf
F. Fleuret, H. Ben Shitrit, and P. Fua. Re-Identification for Improved People Tracking. In S. Gong, M. Cristani, Y. Shuicheng, and C. C. Loy, editors, Person Re-Identification, pages 311–336. Springer, 2014. bib · pdf
H. Ben Shitrit, J. Berclaz, F. Fleuret, and P. Fua. Multi-Commodity Network Flow for Tracking Multiple People. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 36(8):1614–1627, 2013. bib · pdf
L. Lefakis and F. Fleuret. Reservoir Boosting : Between Online and Offline Ensemble Learning. In Proceedings of the international conference on Neural Information Processing Systems (NIPS), pages 1412–1420, 2013. bib · pdf
C. Dubout and F. Fleuret. Deformable Part Models with Individual Part Scaling. In Proceedings of the British Machine Vision Conference (BMVC), pages 28.1–28.10, 2013. bib · pdf
C. Dubout and F. Fleuret. Accelerated Training of Linear Object Detectors. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pages 572–577, 2013. bib · pdf
R. Sznitman, C. Becker, F. Fleuret, and P. Fua. Fast Object Detection with Entropy-Driven Evaluation. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 3270–3277, 2013. bib · pdf
R. Lefort and F. Fleuret. TreeKL: A distance between high dimension empirical distributions. Pattern Recognition Letters (PRL), 34(2):140–145, 2013. bib · pdf
L. Lefakis and F. Fleuret. Macro-Action Discovery Based on Change Point Detection and Boosting. In Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA), volume 1, pages 574–577, 2012. bib · pdf
N. Suditu and F. Fleuret. Iterative Relevance Feedback with Adaptive Exploration / Exploitation Trade-off. In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), pages 1323–1331, 2012. bib · pdf
C. Dubout and F. Fleuret. Exact Acceleration of Linear Object Detectors. In Proceedings of the European Conference on Computer Vision (ECCV), pages 301–311, 2012. bib · pdf
R. Lefort and F. Fleuret. A tree-based distance between distributions: application to classification of neurons. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 2237–2240, 2012. bib · pdf
K. Ali, F. Fleuret, D. Hasler, and P. Fua. A Real-Time Deformable Detector. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 34(2):225–239, 2012. 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
C. Dubout and F. Fleuret. Boosting with Maximum Adaptive Sampling. In Proceedings of the international conference on Neural Information Processing Systems (NIPS), pages 1332–1340, 2011. bib · pdf
C. Dubout and F. Fleuret. Tasting Families of Features for Image Classification. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), pages 929–936, 2011. bib · pdf
N. Suditu and F. Fleuret. HEAT: Iterative Relevance Feedback with One Million Images. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), pages 2118–2125, 2011. bib · pdf
H. Ben Shitrit, J. Berclaz, F. Fleuret, and P. Fua. Tracking Multiple Objects under Global Appearance Constraints. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), pages 137–144, 2011. bib · pdf
F. Fleuret, P. Abbet, C. Dubout, and L. Lefakis. The MASH project. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pages 626–629, 2011. bib · pdf
H. Penedones, R. Collobert, F. Fleuret, and D. Grangier. Improving Object Classification using Pose Information. Technical report, Idiap Research Institute, 2011. bib · pdf
K. Ali, D. Hasler, and F. Fleuret. FlowBoost – Appearance Learning from Sparsely Annotated Video. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 1433–1440, 2011. bib · pdf
J. Berclaz, F. Fleuret, E. Turetken, and P. Fua. Multiple Object Tracking using K-Shortest Paths Optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 33(9):1806–1819, 2011. bib · pdf
L. Lefakis and F. Fleuret. Joint Cascade Optimization Using a Product of Boosted Classifiers. In Proceedings of the international conference on Neural Information Processing Systems (NIPS), pages 1315–1323, 2010. bib · pdf
G. Gonzalez, E. Turetken, F. Fleuret, and P. Fua. Delineating Trees in Noisy 2D Images and 3D Image Stacks. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 2799–2806, 2010. bib · pdf
J. Berclaz, F. Fleuret, and P. Fua. Multiple Object Tracking using Flow Linear Programming. In Proceedings of the 12th IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (Winter-PETS), pages 1–8, 2009. bib · pdf
J. Berclaz, A. Shahrokni, F. Fleuret, J. Ferryman, and P. Fua. Evaluation of Probabilistic Occupancy Map People Detection for Surveillance Systems. In Proceedings of the IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS), pages 55–62, 2009. bib · pdf
J. Berclaz, F. Fleuret, and P. Fua. Multiple Object Tracking using Flow Linear Programming. Technical Report 10-2009, IDIAP Research Institute, 2009. bib · pdf
K. Ali, F. Fleuret, D. Hasler, and P. Fua. Joint Pose Estimator and Feature Learning for Object Detection. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), pages 1373–1380, 2009. bib · pdf
G. Gonzalez, F. Fleuret, and P. Fua. Learning Rotational Features for Filament Detection. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), pages 1582–1589, 2009. bib · pdf
G. Gonzalez, F. Aguet, F. Fleuret, M. Unser, and P. Fua. Steerable Features for Statistical 3D Dendrite Detection. In Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pages 625–632, 2009. bib · pdf
F. Fleuret. Multi-Layer Boosting for Pattern Recognition. Pattern Recognition Letters (PRL), 30:237–241, 2009. bib · pdf
A. Shahrokni, F. Fleuret, T. Drummond, and P. Fua. Classification-based Probabilistic Modeling of Texture Transition for Fast Line Search Tracking and Delineation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 31(3):570–576, 2009. bib · pdf
F. Fleuret and D. Geman. Stationary Features and Cat Detection. Journal of Machine Learning Research (JMLR), 9:2549–2578, 2008. bib · pdf
J. Berclaz, F. Fleuret, and P. Fua. Multi-Camera Tracking and Atypical Motion Detection with Behavioral Maps. In Proceedings of the European Conference on Computer Vision (ECCV), pages 112–125, 2008. bib · pdf
G. Gonzalez, F. Fleuret, and P. Fua. Automated Delineation of Dendritic Networks in Noisy Image Stacks. In Proceedings of the European Conference on Computer Vision (ECCV), pages 214–227, 2008. bib · pdf
F. Fleuret, J. Berclaz, R. Lengagne, and P. Fua. Multi-Camera People Tracking with a Probabilistic Occupancy Map. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 30(2):267–282, 2008. bib · pdf
J. Berclaz, F. Fleuret, and P. Fua. Principled Detection-by-classification from Multiple Views. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP), volume 2, pages 375–382, 2008. bib · pdf
A. Lanza, L. Di Stefano, J. Berclaz, F. Fleuret, and P. Fua. Robust Multi-View Change Detection. In Proceedings of the British Machine Vision Conference (BMVC), 2007. bib · pdf
G. Blanchard and F. Fleuret. Occam's Hammer. In Proceedings of the Annual Conference on Learning Theory (COLT), pages 112–126, 2007. bib · pdf
F. Fleuret, J. Berclaz, R. Lengagne, and P. Fua. Multi-Camera People Tracking with a Probabilistic Occupancy Map. Technical Report EPFL/CVLAB2006.06, EPFL, 2006. bib · pdf
F. Fleuret and P. Fua. Dendrite Tracking in Microscopic Images using Minimum Spanning Trees and Localized E-M. Technical Report EPFL/CVLAB2006.02, EPFL, 2006. bib · pdf
J. Berclaz, F. Fleuret, and P. Fua. Robust People Tracking with Global Trajectory Optimization. In Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 744–750, 2006. bib · pdf
M. Oezuysal, V. Lepetit, F. Fleuret, and P. Fua. Feature Harvesting for Tracking-by-Detection. In Proceedings of the European Conference on Computer Vision (ECCV), volume 3953, pages 592–605, 2006. bib · pdf
F. Fleuret. Modèles Génératifs et Efficacité Algorithmique pour la Prédiction. Habilitation dissertation, University of Paris XIII, 2006. bib · pdf
F. Fleuret and W. Gerstner. A Bayesian Kernel for the Prediction of Neuron Properties from Binary Gene Profiles. In Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA), pages 129–134, 2005. bib · pdf
F. Fleuret and G. Blanchard. Pattern Recognition from One Example by Chopping. In Proceedings of the international conference on Neural Information Processing Systems (NIPS), pages 371–378, 2005. bib · pdf
F. Fleuret, R. Lengagne, and P. Fua. Fixed Point Probability Field for Complex Occlusion Handling. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), volume 1, pages 694–700, 2005. bib · pdf
A. Shahrokni, F. Fleuret, and P. Fua. Classifier-based Contour Tracking for Rigid and Deformable Objects. In Proceedings of the British Machine Vision Conference (BMVC), volume 2, pages 699–708, 2005. bib · pdf
S. Boughorbel, J-P. Tarel, F. Fleuret, and N. Boujemaa. The GCS Kernel For SVM Based Image Recognition. In Proceedings of the International Conference on Artificial Neural Networks (ICANN), volume 2, pages 595–600, 2005. 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, R. Lengagne, and P. Fua. Fixed Point Probability Field for Occlusion Handling. Technical Report IC/2004/87, EPFL, 2004. bib · pdf
S. Boughorbel, J-P. Tarel, and F. Fleuret. Non-Mercer Kernel for SVM Object Recognition. In Proceedings of the British Machine Vision Conference (BMVC), pages 137–146, 2004. bib · pdf
N. Boujemaa, F. Fleuret, V. Gouet, and H. Sahbi. Automatic Textual Annotation of Video News Based on Semantic Visual Object Extraction. In Proceedings of the conference of the International Society for Optical Engineering (SPIE), volume 5307, pages 329–339, 2004. bib · pdf
F. Fleuret and H. Sahbi. Scale Invariance of Support Vector Machines based on the Triangular Kernel. In Proceedings of the workshop on Statistical and Computational Theories of Vision of the IEEE International Conference on Computer Vision (ICCV/SCTV), 2003. bib · pdf
F. Fleuret and H. Sahbi. Coarse-to-fine object detection. ERCIM News, 55, 2003. bib · pdf
F. Rossi, B. Conan-Guez, and F. Fleuret. Functional Data Analysis With Multi Layer Perceptrons. In Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), pages 2843–2848, 2002. bib · pdf
F. Rossi, B. Conan-Guez, and F. Fleuret. Theoretical Properties of Functional Multi Layer Perceptrons. In Proceedings of the European Symposium on Artificial Neural Networks (ESANN), pages 7–12, 2002. bib · pdf
F. Fleuret and D. Geman. Fast Face Detection with Precise Pose Estimation. In Proceedings of the IEEE International Conference on Pattern Recognition (ICPR), volume 1, pages 235–238, 2002. 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
N. Boujemaa, F. Fauqueur, M. Ferecatu, F. Fleuret, V. Gouet, B. Le Saux, and H. Sahbi. Interactive Specific and Generic Image Retrieval. In Proceedings of the international workshop on Multi-Media Content Based Indexing and Retrieval (MMCBIR), 2001. bib · pdf
F. Fleuret. Détection hiérarchique de visages par apprentissage statistique. PhD thesis, University of Paris VI, 2000. bib · ps · pdf
F. Fleuret and J-M. Vézien. Détection de visages dans des séquences vidéo à l'aide d'arbres de décision. In Actes de la conférence Reconnaissance des Formes et Intelligence Artificielle (RFIA), volume 1, pages 17–25, 2000. bib · pdf
F. Fleuret and D. Geman. Apprentissage hiérarchique pour la détection de visages. In Actes de la conférence Reconnaissance des Formes et Intelligence Artificielle (RFIA), volume 2, pages 349–357, 2000. bib · pdf
F. Fleuret and E. Brunet. DEA : An Architecture for Goal Planning and Classification. Neural Computation, 12:1987–2008, 2000. bib · pdf
F. Fleuret and D. Geman. Graded learning for object detection. In Proceedings of the workshop on Statistical and Computational Theories of Vision of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR/SCTV), 1999. bib · ps · pdf
L. Oisel, F. Fleuret, P. Horain, L. Morin, J. M. Vézien, F. Prêteux, A. Gagalowicz, C. Labit, and P. Leray. Analyse de séquences non calibrées pour la reconstruction 3D de scènes. In Actes de la conférence Reconnaissance des Formes et Intelligence Artificielle (RFIA), volume 1, pages 189–198, 1998. bib · pdf
B. Jedynak and F. Fleuret. Reconnaissance d'objets 3D à l'aide d'arbres de classification. In Actes de la conférence Images et Communication (IMAGECOM), 1996. bib · ps · pdf