You can download the complete bibtex file fleuret.bib.
@inproceedings{srinivas-fleuret-2021,
author = {Srinivas, S. and Fleuret, F.},
title = {Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability},
booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
year = {2021},
type = {Oral},
note = {(to appear)}
}
@inproceedings{chavdarova-et-al-2021,
author = {Chavdarova, T. and Pagliardini, M. and Stich, S. and Fleuret, F. and Jaggi, M.},
title = {Taming GANs with Lookahead-Minmax},
booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
year = {2021},
type = {Poster},
note = {(to appear)}
}
@inproceedings{vyas-et-al-2020,
author = {Vyas, A. and Katharopoulos, A. and Fleuret, F.},
title = {Fast Transformers with Clustered Attention},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2020},
url = {https://fleuret.org/papers/vyas-et-al-neurips2020.pdf},
note = {(to appear)}
}
@inproceedings{micheli-et-al-2020,
author = {Micheli, V. and d'Hoffschmidt, M. and Fleuret, F.},
title = {On the importance of pre-training data volume for compact language models},
booktitle = {Proceedings of the international Conference on Empirical Methods in Natural Language Processing (EMNLP)},
year = {2020},
pages = {7853--7858},
url = {https://fleuret.org/papers/micheli-et-al-emnlp2020.pdf}
}
@inproceedings{courdier-fleuret-2020,
author = {Courdier, E. and Fleuret, F.},
title = {Real-Time Segmentation Networks should be Latency Aware},
booktitle = {Proceedings of the Asian Conference on Computer Vision (ACCV)},
year = {2020},
url = {https://fleuret.org/papers/courdier-fleuret-accv2020.pdf},
note = {(to appear)}
}
@inproceedings{prabhu-et-al-2020,
author = {Prabhu, T. and Mai, F. and Vogels, T. and Jaggi, M. and Fleuret, F.},
title = {Optimizer Benchmarking Needs to Account for Hyperparameter Tuning},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2020},
url = {https://fleuret.org/papers/prabhu-et-al-icml2020.pdf},
pages = {8837--8846}
}
@inproceedings{katharopoulos-et-al-2020,
author = {Katharopoulos, A. and Vyas, A. and Pappas, N. and Fleuret, F.},
title = {Transformers are {RNN}s: Fast Autoregressive Transformers with Linear Attention},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2020},
url = {https://fleuret.org/papers/katharopoulos-et-al-icml2020.pdf},
pages = {5294--5303}
}
@inproceedings{chavdarova-et-al-2019,
author = {Chavdarova, T. and Gidel, G. and Fleuret, F. and Lacoste-Julien, S.},
title = {Reducing Noise in GAN Training with Variance Reduced Extragradient},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2019},
type = {Poster},
pages = {391--401},
url = {https://fleuret.org/papers/chavdarova-et-al-neurips2019.pdf}
}
@inproceedings{srinivas-fleuret-2019,
author = {Srinivas, S. and Fleuret, F.},
title = {Full-Gradient Representation for Neural Network Visualization},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2019},
type = {Poster},
pages = {4126--4135},
url = {https://fleuret.org/papers/srinivas-fleuret-neurips2019.pdf}
}
@inproceedings{tulyakov-et-al-2019,
author = {Tulyakov, S. and Fleuret, F. and Kiefel, M. and Gehler, P. and Hirsch, M.},
title = {Learning an event sequence embedding for event-based deep stereo},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2019},
type = {Oral},
pages = {1527-1537},
url = {https://fleuret.org/papers/tulyakov-et-al-iccv2019.pdf}
}
@inproceedings{katharopoulos-fleuret-2019,
author = {Katharopoulos, A. and Fleuret, F.},
title = {Processing Megapixel Images with Deep Attention-Sampling Models},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2019},
pages = {3282-3291},
type = {Short oral},
url = {https://fleuret.org/papers/katharopoulos-fleuret-icml2019.pdf}
}
@inproceedings{tulyakov-et-al-2018b,
author = {Tulyakov, S. and Ivanov, A. and Fleuret, F.},
title = {{P}ractical {D}eep {S}tereo ({PDS}): {T}oward applications-friendly deep stereo matching},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2018},
pages = {5874-5884},
type = {Poster},
url = {https://fleuret.org/papers/tulyakov-et-al-neurips2018.pdf}
}
@inproceedings{jose-et-al-2018,
author = {Jose, C. and Ciss\'e, M. and Fleuret, F.},
title = {Kronecker Recurrent Units},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2018},
pages = {2380-2389},
type = {Short oral},
url = {https://fleuret.org/papers/jose-et-al-icml2018.pdf}
}
@inproceedings{srinivas-fleuret-2018,
author = {Srinivas, S. and Fleuret, F.},
title = {Knowledge Transfer with Jacobian Matching},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2018},
pages = {4723-4731},
type = {Short oral},
url = {https://fleuret.org/papers/srinivas-fleuret-icml2018.pdf}
}
@inproceedings{katharopoulos-fleuret-2018,
author = {Katharopoulos, A. and Fleuret, F.},
title = {Not All Samples Are Created Equal: Deep Learning with Importance Sampling},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2018},
pages = {2525-2534},
type = {Short oral},
url = {https://fleuret.org/papers/katharopoulos-fleuret-icml2018.pdf}
}
@inproceedings{baque-et-al-2018,
author = {Baqu\'e, P. and Remelli, E. and Fleuret, F. and Fua, P.},
title = {Geodesic Convolutional Shape Optimization},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2018},
pages = {472-481},
type = {Long oral},
url = {https://fleuret.org/papers/baque-et-al-icml2018.pdf}
}
@inproceedings{chavdarova-fleuret-2018,
author = {Chavdarova, T. and Fleuret, F.},
title = {{SGAN}: An Alternative Training of Generative Adversarial Networks},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2018},
pages = {9407-9415},
url = {https://fleuret.org/papers/chavdarova-fleuret-cvpr2018.pdf}
}
@inproceedings{chavdarova-et-al-2018,
author = {Chavdarova, T. and Baqué, P. and Bouquet, S. and Maksai, A. and Jose, C. and Bagautdinov, T. and Lettry, L. and Fua, P. and Van Gool, L. and Fleuret, F.
},
title = {{WILDTRACK}: A Multi-camera {HD} Dataset for Dense Unscripted Pedestrian Detection},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2018},
pages = {5030-5039},
type = {poster},
url = {https://fleuret.org/papers/chavdarova-et-al-cvpr2018.pdf}
}
@article{tulyakov-et-al-2018,
title = {Geometric calibration of Colour and Stereo Surface Imaging System of {ESA}'s {T}race {G}as {O}rbiter},
author = {Tulyakov, S. and Ivanov, A. and Thomas, N. and Roloff, V. and Pommerol, A. and Cremonese, G. and Weigel, T. and Fleuret, F.},
journal = {Advances in Space Research},
volume = {61},
number = {1},
pages = {487-496},
year = {2018},
url = {https://fleuret.org/papers/tulyakov-et-al-jasr2018.pdf}
}
@inproceedings{newling-fleuret-2017b,
author = {Newling, J. and Fleuret, F.},
title = {K-Medoids For K-Means Seeding},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
pages = {5195-5203},
year = {2017},
type = {Spotlight},
url = {https://fleuret.org/papers/newling-fleuret-nips2017.pdf}
}
@inproceedings{tulyakov-et-al-2017,
author = {Tulyakov, S. and Ivanov, A. and Fleuret, F.},
title = {Weakly Supervised Learning of Deep Metrics for Stereo Reconstruction},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2017},
type = {Poster},
pages = {1348-1357},
url = {https://fleuret.org/papers/tulyakov-et-al-iccv2017.pdf}
}
@inproceedings{baque-et-al-2017b,
author = {Baqu\'e, P. and Fleuret, F. and Fua, P.},
title = {Deep Occlusion Reasoning for Multi-Camera Multi-Target Detection},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2017},
type = {Poster},
pages = {271-279},
url = {https://fleuret.org/papers/baque-et-al-iccv2017.pdf}
}
@inproceedings{maksai-et-al-2017,
author = {Maksai, A. and Wang, X. and Fleuret, F. and Fua, P.},
title = {Non-Markovian Globally Consistent Multi-Object Tracking},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2017},
type = {Poster},
pages = {2563-2573},
url = {https://fleuret.org/papers/maksai-et-al-iccv2017.pdf}
}
@inproceedings{chavdarova-fleuret-2017,
author = {Chavdarova, T. and Fleuret, F.},
title = {Deep Multi-Camera People Detection},
booktitle = {Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA)},
year = {2017},
type = {Poster},
pages = {848-853},
url = {https://fleuret.org/papers/chavdarova-fleuret-icmla2017.pdf}
}
@inproceedings{abbasi-et-al-2017b,
author = {Abbasi-Sureshjani, S. and Dasht Bozorg, B. and ter Haar Romeny, B. M. and Fleuret, F.},
title = {Boosted Exudate Segmentation in Retinal Images using Residual Nets},
booktitle = {Proceedings of the MICCAI Workshop on Ophthalmic Medical Image Analysis (OMIA)},
year = {2017},
pages = {210-218},
url = {https://fleuret.org/papers/abbasi-et-al-omia2017.pdf}
}
@inproceedings{baque-et-al-2017,
author = {Baqu\'e, P. and Fleuret, F. and Fua, P.},
title = {Multi-Modal Mean-Fields via Cardinality-Based Clamping},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2017},
type = {Spotlight},
pages = {271-279},
url = {https://fleuret.org/papers/baque-et-al-cvpr2017.pdf}
}
@inproceedings{bagautdinov-et-al-2017,
author = {Bagautdinov, T. and Alahi, A. and Fleuret, F. and Fua, P. and Savarese, S.},
title = {Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2017},
type = {Oral},
pages = {3425-3434},
url = {https://fleuret.org/papers/bagautdinov-et-al-cvpr2017.pdf}
}
@inproceedings{newling-fleuret-2017,
author = {Newling, J. and Fleuret, F.},
title = {A Sub-Quadratic Exact Medoid Algorithm},
booktitle = {Proceedings of the international conference on Artificial Intelligence and Statistics (AISTATS)},
year = {2017},
type = {Oral},
pages = {185-193},
url = {https://fleuret.org/papers/newling-fleuret-aistats2017.pdf},
note = {(Best paper award)}
}
@inproceedings{abbasi-et-al-2017,
author = {Abbasi-Sureshjani, S. and Dasht Bozorg, B. and ter Haar Romeny, B. M. and Fleuret, F.},
title = {Exploratory Study on Direct Prediction of Diabetes using Deep Residual Networks},
booktitle = {Proceedings of the thematic conference on computational vision and medical image processing (VipIMAGE)},
year = {2017},
url = {https://fleuret.org/papers/abbasi-et-al-vipimage2017.pdf},
pages = {797-802}
}
@article{lefort-et-al-2017,
author = {Lefort, R. and Fusco, L. and Pertz, O. and Fleuret, F.},
title = {Machine learning-based tools to model and to remove the off-target effect},
journal = {Pattern Analysis and Applications (PAA)},
year = {2017},
volume = {20},
number = {1},
pages = {87-100},
url = {https://fleuret.org/papers/lefort-et-al-paa2017.pdf}
}
@article{fleuret-2016,
author = {Fleuret, F.},
title = {Predicting the dynamics of 2d objects with a deep residual network},
journal = {CoRR},
volume = {abs/1610.04032},
year = {2016},
url = {https://arxiv.org/pdf/1610.04032}
}
@inproceedings{newling-fleuret-2016b,
author = {Newling, J. and Fleuret, F.},
title = {Fast mini-batch k-means by nesting},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
year = {2016},
type = {Poster},
pages = {1352-1360},
url = {https://fleuret.org/papers/newling-fleuret-nips2016.pdf}
}
@inproceedings{jose-fleuret-2016,
author = {Jose, C. and Fleuret, F.},
title = {Scalable Metric Learning via Weighted Approximate Rank Component Analysis},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2016},
type = {Poster},
pages = {875-890},
url = {https://fleuret.org/papers/jose-fleuret-eccv2016.pdf}
}
@inproceedings{newling-fleuret-2016,
author = {Newling, J. and Fleuret, F.},
title = {Fast k-means with accurate bounds},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
pages = {936-944},
year = {2016},
type = {Oral},
url = {https://fleuret.org/papers/newling-fleuret-icml2016.pdf}
}
@inproceedings{canevet-et-al-2016,
author = {Can{\'e}vet, O. and Jose, C. and Fleuret, F.},
title = {Importance Sampling Tree for Large-scale Empirical Expectation},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
pages = {1454-1462},
year = {2016},
type = {Oral},
url = {https://fleuret.org/papers/canevet-et-al-icml2016.pdf}
}
@inproceedings{canevet-fleuret-2016,
author = {Can\'evet, O. and Fleuret, F.},
title = {Large Scale Hard Sample Mining with Monte Carlo Tree Search},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2016},
type = {Poster},
pages = {5128-5137},
url = {https://fleuret.org/papers/canevet-fleuret-cvpr2016.pdf}
}
@inproceedings{baque-et-al-2016,
author = {Baqu\'e, P. and Bagautdinov, T. and Fleuret, F. and Fua, P.},
title = {Principled Parallel Mean-Field Inference for Discrete Random Fields},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2016},
type = {Poster},
pages = {5848-5857},
url = {https://fleuret.org/papers/baque-et-al-cvpr2016.pdf}
}
@article{lefakis-fleuret-2016,
author = {Lefakis, L. and Fleuret, F.},
title = {Jointly Informative Feature Selection Made Tractable by Gaussian Modeling},
journal = {Journal of Machine Learning Research (JMLR)},
year = {2016},
pages = {1-39},
volume = {17},
number = {182},
url = {https://fleuret.org/papers/lefakis-fleuret-jmlr2016.pdf}
}
@article{wang-et-al-2016,
author = {Wang, X. and Turetken, E. and Fleuret, F. and Fua, P.},
title = {Tracking Interacting Objects Using Intertwined Flows},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
volume = {38},
number = {11},
pages = {2312-2326},
year = {2016},
url = {https://fleuret.org/papers/wang-et-al-tpami2016.pdf}
}
@article{fusco-et-al-2016,
author = {Fusco, L. and Lefort, R. and Smith, K. and Benmansour, F. and Gonzalez, G. and Barilari, C. and Rinn, B. and Fleuret, F. and Fua, P. and Pertz, O.},
title = {Computer vision profiling of neurite outgrowth dynamics reveals spatio-temporal modularity of Rho GTPase signaling},
journal = {Journal of Cell Biology},
volume = {212},
number = {1},
pages = {91-111},
year = {2016},
url = {https://fleuret.org/papers/fusco-et-al-jcb2016.pdf}
}
@article{suditu-fleuret-2016,
author = {Suditu, N. and Fleuret, F.},
title = {Adaptive relevance feedback for large-scale image retrieval},
journal = {Multimedia Tools and Applications (MTA)},
volume = {75},
number = {12},
pages = {6777--6807},
year = {2016},
url = {https://fleuret.org/papers/suditu-fleuret-mta2016.pdf}
}
@inproceedings{khan-et-al-2015,
author = {Khan, E. and Baqu\'e, P. and Fleuret, F. and Fua, P.},
title = {Kullback-Leibler Proximal Variational Inference},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
year = {2015},
type = {Poster},
url = {https://fleuret.org/papers/khan-et-al-nips2015.pdf},
pages = {3402-3410}
}
@inproceedings{bagautdinov-et-al-2015,
author = {Bagautdinov, T. and Fleuret, F. and Fua, P.},
title = {Probability Occupancy Maps for Occluded Depth Images},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2015},
pages = {2829-2837},
type = {Poster},
url = {https://fleuret.org/papers/bagautdinov-et-al-cvpr2015.pdf}
}
@inproceedings{canevet-fleuret-2014,
author = {Can\'evet, O. and Fleuret, F.},
title = {Efficient Sample Mining for Object Detection},
booktitle = {Proceedings of the Asian Conference on Machine Learning (ACML)},
year = {2014},
pages = {48-63},
type = {Oral},
url = {https://fleuret.org/papers/canevet-fleuret-acml2014.pdf}
}
@inproceedings{canevet-et-al-2014,
author = {Can\'evet, O. and Lefakis, L. and Fleuret, F.},
title = {Sample Distillation for Object Detection and Image Classification},
booktitle = {Proceedings of the Asian Conference on Machine Learning (ACML)},
year = {2014},
pages = {64-79},
type = {Oral},
url = {https://fleuret.org/papers/canevet-et-al-acml2014.pdf}
}
@inproceedings{penate-et-al-2014,
author = {Penate Sanchez, A. and Moreno-Noguer, F. and Andrade Cetto, J. and Fleuret, F.},
title = {{L}{E}{T}{H}{A}: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images},
booktitle = {Proceedings of the International Conference on 3D vision (3DV)},
year = {2014},
pages = {517-524},
volume = {1},
type = {Oral},
url = {https://fleuret.org/papers/penate-et-al-3dv2014.pdf}
}
@inproceedings{wang-et-al-2014,
author = {Wang, X. and Turetken, E. and Fleuret, F. and Fua, P.},
title = {Tracking Interacting Objects Optimally Using Integer Programming},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2014},
type = {Oral},
pages = {17-32},
url = {https://fleuret.org/papers/wang-et-al-eccv2014.pdf}
}
@inproceedings{lefakis-fleuret-2014b,
author = {Lefakis, L. and Fleuret, F.},
title = {Dynamic Programming Boosting for Discriminative Macro-Action Discovery},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2014},
type = {Oral},
pages = {1548-1556},
url = {https://fleuret.org/papers/lefakis-fleuret-icml2014.pdf}
}
@article{dubout-fleuret-2014,
author = {Dubout, C. and Fleuret, F.},
title = {Adaptive Sampling for Large Scale {B}oosting},
journal = {Journal of Machine Learning Research (JMLR)},
year = {2014},
volume = {15},
pages = {1431-1453},
url = {https://fleuret.org/papers/dubout-fleuret-jmlr2014.pdf}
}
@inproceedings{lefakis-fleuret-2014,
author = {Lefakis, L. and Fleuret, F.},
title = {Jointly Informative Feature Selection},
booktitle = {Proceedings of the international conference on Artificial Intelligence and Statistics (AISTATS)},
pages = {567-575},
year = {2014},
type = {Poster},
url = {https://fleuret.org/papers/lefakis-fleuret-aistats2014.pdf}
}
@incollection{fleuret-et-al-2014,
author = {Fleuret, F. and Ben Shitrit, H. and Fua, P.},
editor = {Gong, S. and Cristani, M. and Shuicheng, Y. and Loy, C. C.},
title = {Re-Identification for Improved People Tracking},
booktitle = {Person Re-Identification},
pages = {311-336},
publisher = {Springer},
year = {2014},
url = {https://fleuret.org/papers/fleuret-et-al-chapter2014.pdf}
}
@article{benshitrit-et-al-2013,
author = {Ben Shitrit, H. and Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Multi-Commodity Network Flow for Tracking Multiple People},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2013},
volume = {36},
number = {8},
pages = {1614-1627},
url = {https://fleuret.org/papers/benshitrit-et-al-tpami2013.pdf}
}
@inproceedings{lefakis-fleuret-2013,
author = {Lefakis, L. and Fleuret, F.},
title = {Reservoir {B}oosting : Between Online and Offline Ensemble Learning},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
pages = {1412-1420},
year = {2013},
type = {Poster},
url = {https://fleuret.org/papers/lefakis-fleuret-nips2013.pdf}
}
@inproceedings{dubout-fleuret-2013b,
author = {Dubout, C. and Fleuret, F.},
title = {Deformable Part Models with Individual Part Scaling},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2013},
pages = {28.1-28.10},
type = {Poster},
url = {https://fleuret.org/papers/dubout-fleuret-bmvc2013.pdf}
}
@inproceedings{dubout-fleuret-2013,
author = {Dubout, C. and Fleuret, F.},
title = {Accelerated Training of Linear Object Detectors},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
year = {2013},
type = {Oral},
pages = {572-577},
url = {https://fleuret.org/papers/dubout-fleuret-spws2013.pdf}
}
@inproceedings{sznitman-et-al-2013,
author = {Sznitman, R. and Becker, C. and Fleuret, F. and Fua, P.},
title = {Fast Object Detection with Entropy-Driven Evaluation},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2013},
pages = {3270-3277},
type = {Poster},
url = {https://fleuret.org/papers/sznitman-et-al-cvpr2013.pdf}
}
@article{lefort-fleuret-2013,
author = {Lefort, R. and Fleuret, F.},
title = {Tree{K}{L}: A distance between high dimension empirical distributions},
journal = {Pattern Recognition Letters (PRL)},
year = {2013},
volume = {34},
number = {2},
pages = {140-145},
url = {https://fleuret.org/papers/lefort-fleuret-prl2013.pdf}
}
@inproceedings{lefakis-fleuret-2012,
author = {Lefakis, L. and Fleuret, F.},
title = {Macro-Action Discovery Based on Change Point Detection and {B}oosting},
booktitle = {Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA)},
year = {2012},
volume = {1},
pages = {574-577},
type = {Poster},
url = {https://fleuret.org/papers/lefakis-fleuret-icmla2012.pdf}
}
@inproceedings{suditu-fleuret-2012,
author = {Suditu, N. and Fleuret, F.},
title = {Iterative Relevance Feedback with Adaptive Exploration / Exploitation Trade-off},
booktitle = {Proceedings of the ACM Conference on Information and Knowledge Management (CIKM)},
year = {2012},
pages = {1323-1331},
type = {Oral},
url = {https://fleuret.org/papers/suditu-fleuret-cimk2012.pdf}
}
@inproceedings{dubout-fleuret-2012,
author = {Dubout, C. and Fleuret, F.},
title = {Exact Acceleration of Linear Object Detectors},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2012},
pages = {301-311},
type = {Oral},
url = {https://fleuret.org/papers/dubout-fleuret-eccv2012.pdf}
}
@inproceedings{lefort-fleuret-2012,
author = {Lefort, R. and Fleuret, F.},
title = {A tree-based distance between distributions: application to classification of neurons},
booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2012},
pages = {2237-2240},
type = {Poster},
url = {https://fleuret.org/papers/lefort-fleuret-icassp2012.pdf}
}
@article{ali-et-al-2012,
author = {Ali, K. and Fleuret, F. and Hasler, D. and Fua, P.},
title = {A Real-Time Deformable Detector},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2012},
volume = {34},
number = {2},
pages = {225-239},
url = {https://fleuret.org/papers/ali-et-al-tpami2012.pdf}
}
@article{fleuret-et-al-2011b,
author = {Fleuret, F. and Li, T. and Dubout, C. and Wampler, E. K. and Yantis, S. and Geman, D.},
title = {Comparing machines and humans on a visual categorization test},
journal = {Proceedings of the National Academy of Sciences (PNAS)},
year = {2011},
volume = {108},
number = {43},
pages = {17621-17625},
url = {https://fleuret.org/papers/fleuret-et-al-pnas2011.pdf}
}
@inproceedings{dubout-fleuret-2011b,
author = {Dubout, C. and Fleuret, F.},
title = {{B}oosting with Maximum Adaptive Sampling},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
pages = {1332-1340},
year = {2011},
type = {Poster},
url = {https://fleuret.org/papers/dubout-fleuret-nips2011.pdf}
}
@inproceedings{dubout-fleuret-2011,
author = {Dubout, C. and Fleuret, F.},
title = {Tasting Families of Features for Image Classification},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
pages = {929-936},
year = {2011},
type = {Poster},
url = {https://fleuret.org/papers/dubout-fleuret-iccv2011.pdf}
}
@inproceedings{suditu-fleuret-2011,
author = {Suditu, N. and Fleuret, F.},
title = {{H}{E}{A}{T}: Iterative Relevance Feedback with One Million Images},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
pages = {2118-2125},
year = {2011},
type = {Poster},
url = {https://fleuret.org/papers/suditu-fleuret-iccv2011.pdf}
}
@inproceedings{benshitrit-et-al-2011,
author = {Ben Shitrit, H. and Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Tracking Multiple Objects under Global Appearance Constraints},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
pages = {137-144},
year = {2011},
type = {Poster},
url = {https://fleuret.org/papers/benshitrit-et-al-iccv2011.pdf}
}
@inproceedings{fleuret-et-al-2011,
author = {Fleuret, F. and Abbet, P. and Dubout, C. and Lefakis, L.},
title = {The {M}{A}{S}{H} project},
booktitle = {Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)},
year = {2011},
pages = {626-629},
type = {Demo},
url = {https://fleuret.org/papers/fleuret-et-al-ecml2011.pdf}
}
@techreport{penedones-et-al-tr2011,
author = {Penedones, H. and Collobert, R. and Fleuret, F. and Grangier, D.},
title = {Improving Object Classification using Pose Information },
institution = {Idiap Research Institute},
year = {2011},
key = {30-2012},
url = {https://fleuret.org/papers/penedones-et-al-tr2011.pdf}
}
@inproceedings{ali-et-al-2011,
author = {Ali, K. and Hasler, D. and Fleuret, F.},
title = {FlowBoost -- {A}ppearance Learning from Sparsely Annotated Video},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
pages = {1433-1440},
year = {2011},
type = {Oral},
url = {https://fleuret.org/papers/ali-hasler-fleuret-cvpr2011.pdf}
}
@article{berclaz-et-al-2011,
title = {Multiple Object Tracking using K-Shortest Paths Optimization},
author = {Berclaz, J. and Fleuret, F. and Turetken, E. and Fua, P.},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2011},
volume = {33},
number = {9},
pages = {1806-1819},
url = {https://fleuret.org/papers/berclaz-et-al-tpami2011.pdf}
}
@inproceedings{lefakis-fleuret-2010,
author = {Lefakis, L. and Fleuret, F.},
title = {Joint Cascade Optimization Using a Product of Boosted Classifiers},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
year = {2010},
pages = {1315-1323},
type = {Poster},
url = {https://fleuret.org/papers/lefakis-fleuret-nips2010.pdf}
}
@inproceedings{gonzalez-et-al-2010,
author = {Gonzalez, G. and Turetken, E. and Fleuret, F. and Fua, P.},
title = {Delineating Trees in Noisy 2D Images and 3D Image Stacks},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2010},
pages = {2799-2806},
type = {Poster},
url = {https://fleuret.org/papers/gonzalez-et-al-cvpr2010.pdf}
}
@inproceedings{berclaz-et-al-2009,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Multiple Object Tracking using Flow Linear Programming},
booktitle = {Proceedings of the 12th IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (Winter-PETS)},
year = {2009},
pages = {1-8},
url = {https://fleuret.org/papers/berclaz-et-al-pets2009.pdf}
}
@inproceedings{berclaz-et-al-2009b,
author = {Berclaz, J. and Shahrokni, A. and Fleuret, F. and Ferryman, J. and Fua, P.},
title = {Evaluation of Probabilistic Occupancy Map People Detection for Surveillance Systems},
booktitle = {Proceedings of the IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS)},
year = {2009},
pages = {55-62},
url = {https://fleuret.org/papers/berclaz-et-al-pets2009b.pdf}
}
@techreport{berclaz-et-al-2009c,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Multiple Object Tracking using Flow Linear Programming},
institution = {IDIAP Research Institute},
year = {2009},
number = {10-2009},
url = {https://fleuret.org/papers/berclaz-et-al-rr-10-2009.pdf}
}
@inproceedings{ali-et-al-2009,
author = {Ali, K. and Fleuret, F. and Hasler, D. and Fua, P.},
title = {Joint Pose Estimator and Feature Learning for Object Detection},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2009},
pages = {1373-1380},
type = {Poster},
url = {https://fleuret.org/papers/ali-et-al-iccv2009.pdf}
}
@inproceedings{gonzalez-et-al-2009,
author = {Gonzalez, G. and Fleuret, F. and Fua, P.},
title = {Learning Rotational Features for Filament Detection},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2009},
pages = {1582-1589},
url = {https://fleuret.org/papers/gonzalez-et-al-cvpr2009.pdf}
}
@inproceedings{gonzalez-et-al-2009b,
author = {Gonzalez, G. and Aguet, F. and Fleuret, F. and Unser, M. and Fua, P.},
title = {Steerable Features for Statistical 3D Dendrite Detection},
booktitle = {Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)},
year = {2009},
pages = {625-632},
url = {https://fleuret.org/papers/gonzalez-et-al-miccai2009.pdf}
}
@article{fleuret-2009,
author = {Fleuret, F.},
title = {Multi-Layer {B}oosting for Pattern Recognition},
journal = {Pattern Recognition Letters (PRL)},
year = {2009},
volume = {30},
pages = {237-241},
url = {https://fleuret.org/papers/fleuret-prl2009.pdf}
}
@article{shahrokni-et-al-2009,
author = {Shahrokni, A. and Fleuret, F. and Drummond, T. and Fua, P.},
title = {Classification-based Probabilistic Modeling of Texture Transition for Fast Line Search Tracking and Delineation},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2009},
volume = {31},
number = {3},
pages = {570-576},
url = {https://fleuret.org/papers/shahrokni-et-al-tpami2009.pdf}
}
@article{fleuret-geman-2008,
author = {Fleuret, F. and Geman, D.},
title = {Stationary Features and Cat Detection},
journal = {Journal of Machine Learning Research (JMLR)},
year = {2008},
volume = {9},
pages = {2549-2578},
url = {https://fleuret.org/papers/fleuret-geman-jmlr2008.pdf}
}
@inproceedings{berclaz-et-al-2008,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Multi-Camera Tracking and Atypical Motion Detection with Behavioral Maps},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2008},
pages = {112-125},
url = {https://fleuret.org/papers/berclaz-et-al-eccv2008.pdf}
}
@inproceedings{gonzalez-et-al-2008,
author = {Gonzalez, G. and Fleuret, F. and Fua, P.},
title = {Automated Delineation of Dendritic Networks in Noisy Image Stacks},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2008},
pages = {214-227},
url = {https://fleuret.org/papers/gonzalez-et-al-eccv2008.pdf}
}
@article{fleuret-et-al-2008,
author = {Fleuret, F. and Berclaz, J. and Lengagne, R. and Fua, P.},
title = {Multi-Camera People Tracking with a Probabilistic Occupancy Map},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2008},
volume = {30},
number = {2},
pages = {267-282},
url = {https://fleuret.org/papers/fleuret-et-al-tpami2008.pdf}
}
@inproceedings{berclaz-fleuret-fua-2008,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Principled Detection-by-classification from Multiple Views},
booktitle = {Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP)},
year = {2008},
volume = {2},
pages = {375-382},
url = {https://fleuret.org/papers/berclaz-et-al-visapp2008.pdf}
}
@inproceedings{lanza-et-al-2007,
author = {Lanza, A. and Di Stefano, L. and Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Robust Multi-View Change Detection},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2007},
url = {https://fleuret.org/papers/lanza-et-al-bmvc2007.pdf}
}
@inproceedings{blanchard-fleuret-2007,
author = {Blanchard, G. and Fleuret, F.},
title = {Occam's Hammer},
booktitle = {Proceedings of the Annual Conference on Learning Theory (COLT)},
year = {2007},
pages = {112-126},
url = {https://fleuret.org/papers/blanchard-fleuret-colt2007.pdf}
}
@techreport{fleuret-et-al-2006,
author = {Fleuret, F. and Berclaz, J. and Lengagne, R. and Fua, P.},
title = {Multi-Camera People Tracking with a Probabilistic Occupancy Map},
institution = {EPFL},
year = {2006},
number = {EPFL/CVLAB2006.06},
url = {https://fleuret.org/papers/fleuret-berclaz-lengagne-fua-TR-EPFL_CVLAB2006.06.pdf}
}
@techreport{fleuret-fua-2006,
author = {Fleuret, F. and Fua, P.},
title = {Dendrite Tracking in Microscopic Images using Minimum Spanning Trees and Localized {E}-{M}},
institution = {EPFL},
year = {2006},
number = {EPFL/CVLAB2006.02},
url = {https://fleuret.org/papers/fleuret-fua-TR-EPFL_CVLAB2006.02.pdf}
}
@inproceedings{berclaz-fleuret-fua-2006,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Robust People Tracking with Global Trajectory Optimization},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2006},
volume = {1},
pages = {744-750},
url = {https://fleuret.org/papers/berclaz-fleuret-fua-cvpr2006.pdf}
}
@inproceedings{oezuysal-et-al-2006,
author = {Oezuysal, M. and Lepetit, V. and Fleuret, F. and Fua, P.},
title = {Feature Harvesting for Tracking-by-Detection},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2006},
volume = {3953},
pages = {592-605},
url = {https://fleuret.org/papers/oezuysal-et-al-eccv2006.pdf}
}
@misc{fleuret-2006,
author = {Fleuret, F.},
title = {{M}od\`eles G\'en\'eratifs et Efficacit\'e Algorithmique pour la Pr\'ediction},
howpublished = {Habilitation dissertation, University of Paris XIII},
year = {2006},
url = {https://fleuret.org/papers/fleuret-synthese-hdr.pdf}
}
@inproceedings{fleuret-gerstner-2005,
author = {Fleuret, F. and Gerstner, W.},
title = {A {B}ayesian Kernel for the Prediction of Neuron Properties from Binary Gene Profiles},
booktitle = {Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA)},
year = {2005},
pages = {129-134},
url = {https://fleuret.org/papers/fleuret-gerstner-icmla2005.pdf}
}
@inproceedings{fleuret-blanchard-2005,
author = {Fleuret, F. and Blanchard, G.},
title = {Pattern Recognition from One Example by {C}hopping},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
year = {2005},
pages = {371-378},
url = {https://fleuret.org/papers/fleuret-blanchard-nips2005.pdf}
}
@inproceedings{fleuret-lengagne-fua-2005,
author = {Fleuret, F. and Lengagne, R. and Fua, P.},
title = {Fixed Point Probability Field for Complex Occlusion Handling},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2005},
volume = {1},
pages = {694-700},
url = {https://fleuret.org/papers/fleuret-lengagne-fua-iccv2005.pdf}
}
@inproceedings{shahrokni-fleuret-fua-2005,
author = {Shahrokni, A. and Fleuret, F. and Fua, P.},
title = {Classifier-based Contour Tracking for Rigid and Deformable Objects},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2005},
volume = {2},
pages = {699-708},
url = {https://fleuret.org/papers/shahrokni-fleuret-fua-bmvc2005.pdf}
}
@inproceedings{boughorbel-et-al-2005,
author = {Boughorbel, S. and Tarel, J-P. and Fleuret, F. and Boujemaa, N.},
title = {The {G}{C}{S} Kernel For {S}{V}{M} Based Image Recognition},
booktitle = {Proceedings of the International Conference on Artificial Neural Networks (ICANN)},
year = {2005},
volume = {2},
pages = {595-600},
url = {https://fleuret.org/papers/boughorbel-et-al-ICCAN2005.pdf}
}
@article{fleuret-2004,
author = {Fleuret, F.},
title = {Fast Binary Feature Selection with Conditional Mutual Information},
journal = {Journal of Machine Learning Research (JMLR)},
year = {2004},
volume = {5},
pages = {1531-1555},
url = {https://fleuret.org/papers/fleuret-jmlr2004.pdf}
}
@techreport{fleuret-lengagne-fua-2004,
author = {Fleuret, F. and Lengagne, R. and Fua, P.},
title = {Fixed Point Probability Field for Occlusion Handling},
institution = {EPFL},
year = {2004},
number = {IC/2004/87},
url = {https://fleuret.org/papers/IC_TECH_REPORT_200487.pdf}
}
@inproceedings{boughorbel-et-al-2004,
author = {Boughorbel, S. and Tarel, J-P. and Fleuret, F.},
title = {Non-{M}ercer Kernel for {S}{V}{M} Object Recognition},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2004},
pages = {137-146},
url = {https://fleuret.org/papers/boughorbel-et-al-bmvc2004.pdf}
}
@inproceedings{boujemaa-et-al-2004,
author = {Boujemaa, N. and Fleuret, F. and Gouet, V. and Sahbi, H.},
title = {Automatic Textual Annotation of Video News Based on Semantic Visual Object Extraction},
booktitle = {Proceedings of the conference of the International Society for Optical Engineering (SPIE)},
volume = {5307},
year = {2004},
pages = {329-339},
url = {https://fleuret.org/papers/boujemaa-et-al-spie2004.pdf}
}
@inproceedings{fleuret-sahbi-2003,
author = {Fleuret, F. and Sahbi, H.},
title = {Scale Invariance of Support Vector Machines based on the Triangular Kernel},
booktitle = {Proceedings of the workshop on Statistical and Computational Theories of Vision of the IEEE International Conference on Computer Vision (ICCV/SCTV)},
year = {2003},
url = {https://fleuret.org/papers/sctv2003-fleuret-sahbi.pdf}
}
@article{fleuret-sahbi-ercim2003,
author = {Fleuret, F. and Sahbi, H.},
title = {Coarse-to-fine object detection},
journal = {ERCIM News},
year = {2003},
volume = {55},
url = {https://fleuret.org/papers/fleuret-sahbi-ercim2003.pdf}
}
@inproceedings{rossi-et-al-2002,
author = {Rossi, F. and Conan-Guez, B. and Fleuret, F.},
title = {Functional Data Analysis With Multi Layer Perceptrons},
booktitle = {Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN)},
year = {2002},
pages = {2843-2848},
url = {https://fleuret.org/papers/rossi-conan-fleuret-ijcn2002.pdf}
}
@inproceedings{rossi-et-al-2002b,
author = {Rossi, F. and Conan-Guez, B. and Fleuret, F.},
title = {Theoretical Properties of Functional Multi Layer Perceptrons},
booktitle = {Proceedings of the European Symposium on Artificial Neural Networks (ESANN)},
pages = {7-12},
year = {2002},
url = {https://fleuret.org/papers/rossi-conan-fleuret-esann2002.pdf}
}
@inproceedings{fleuret-geman-2002,
author = {Fleuret, F. and Geman, D.},
title = {Fast Face Detection with Precise Pose Estimation},
booktitle = {Proceedings of the IEEE International Conference on Pattern Recognition (ICPR)},
pages = {235-238},
volume = {1},
year = {2002},
url = {https://fleuret.org/papers/fleuret-geman-icpr2002.pdf}
}
@article{fleuret-geman-2001,
author = {Fleuret, F. and Geman, D.},
title = {Coarse-to-fine Face Detection},
journal = {International Journal of Computer Vision (IJCV)},
year = {2001},
volume = {41},
number = {1/2},
pages = {85-107},
url = {https://fleuret.org/papers/fleuret-geman-preprint-ijcv2001.pdf},
urlps = {https://fleuret.org/papers/fleuret-geman-preprint-ijcv2001.ps.gz}
}
@inproceedings{boujemaa-et-al-2001,
author = {Boujemaa, N. and Fauqueur, F. and Ferecatu, M. and Fleuret, F. and Gouet, V. and Le Saux, B. and Sahbi, H.},
title = {Interactive Specific and Generic Image Retrieval},
booktitle = {Proceedings of the international workshop on Multi-Media Content Based Indexing and Retrieval (MMCBIR)},
year = {2001},
url = {https://fleuret.org/papers/boujemaa-et-al-mmcbir2001.pdf}
}
@phdthesis{fleuret-2000,
author = {Fleuret, F.},
title = {D{\'e}tection hi{\'e}rarchique de visages par apprentissage statistique},
school = {University of Paris VI},
year = {2000},
urlps = {https://fleuret.org/papers/fleuret-these.ps.gz},
url = {https://fleuret.org/papers/fleuret-these.pdf}
}
@inproceedings{fleuret-vezien-2000,
author = {Fleuret, F. and V{\'e}zien, J-M.},
title = {D{\'e}tection de visages dans des s{\'e}quences vid{\'e}o {\`a} l'aide d'arbres de d{\'e}cision},
booktitle = {Actes de la conf\'erence Reconnaissance des Formes et Intelligence Artificielle (RFIA)},
pages = {17-25},
volume = {1},
year = {2000},
url = {https://fleuret.org/papers/fleuret-vezien-rfia2000.pdf}
}
@inproceedings{fleuret-geman-2000,
author = {Fleuret, F. and Geman, D.},
title = {Apprentissage hi{\'e}rarchique pour la d{\'e}tection de visages},
booktitle = {Actes de la conf\'erence Reconnaissance des Formes et Intelligence Artificielle (RFIA)},
pages = {349-357},
volume = {2},
year = {2000},
url = {https://fleuret.org/papers/fleuret-geman-rfia2000.pdf}
}
@article{fleuret-brunet-2000,
author = {Fleuret, F. and Brunet, E.},
title = {{D}{E}{A}~: An Architecture for Goal Planning and Classification},
journal = {Neural Computation},
year = {2000},
volume = {12},
pages = {1987-2008},
url = {https://fleuret.org/papers/fleuret-brunet-preprint-nc2000.pdf}
}
@inproceedings{fleuret-geman-1999,
author = {Fleuret, F. and Geman, D.},
title = {Graded learning for object detection},
booktitle = {Proceedings of the workshop on Statistical and Computational Theories of Vision of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR/SCTV)},
year = {1999},
url = {https://fleuret.org/papers/fleuret-geman-cvpr1999.pdf},
urlps = {https://fleuret.org/papers/fleuret-geman-cvpr1999.ps.gz}
}
@inproceedings{oisel-et-al-1998,
author = {Oisel, L. and Fleuret, F. and Horain, P. and Morin, L. and V{\'e}zien, J. M. and Pr{\^e}teux, F. and Gagalowicz, A. and Labit, C. and Leray, P.},
title = {Analyse de s{\'e}quences non calibr{\'e}es pour la reconstruction 3D de sc{\`e}nes},
booktitle = {Actes de la conf\'erence Reconnaissance des Formes et Intelligence Artificielle (RFIA)},
pages = {189-198},
volume = {1},
year = {1998},
url = {https://fleuret.org/papers/oisel-et-al-rfia1998.pdf}
}
@inproceedings{jedynak-fleuret-1996,
author = {Jedynak, B. and Fleuret, F.},
title = {Reconnaissance d'objets 3D {\`a} l'aide d'arbres de classification},
booktitle = {Actes de la conf\'erence Images et Communication (IMAGECOM)},
year = {1996},
url = {https://fleuret.org/papers/jedynak-fleuret-imagecom1996.pdf},
urlps = {https://fleuret.org/papers/jedynak-fleuret-imagecom1996.ps.gz}
}