All publications are listed below:
2023
Artificial intelligence to advance Earth observation: a perspective, Devis Tuia, Konrad Schindler, Begüm Demir, Gustau Camps-Valls, Xiao Xiang Zhu, Mrinalini Kochupillai, Sašo Džeroski, Jan N. van Rijn, Holger H. Hoos, Fabio Del Frate, Mihai Datcu, Jorge-Arnulfo Quiané-Ruiz, Volker Markl, Bertrand Le Saux, Rochelle Schneider, arXiv:2305.08413, May 2023.
IceCloudNet: Cirrus and mixed-phase cloud prediction from SEVIRI input learned from sparse supervision Kai Jeggle, Mikolaj Czerkawski, Federico Serva, Bertrand Le Saux, David Neubauer, Ulrike Lohmann, NeurIPS / CCAI, New Orleans, LA, Dec. 2023
[ arxiv / CCAI abstract and paper @ NeurIPS’23 / NeurIPS video and slides ]
The curse of language biases in remote sensing VQA: the role of spatial attributes, language diversity, and the need for clear evaluation Christel Chappuis, Eliot Walt, Vincent Mendez, Sylvain Lobry, Bertrand Le Saux, Devis Tuia, to appear.
[ arxiv ]
ChangeMatch: A Semi-Supervised Deep Learning Framework for Change Detection in Open-Pit Mines Using SAR Imagery Murdaca, Gianluca; Ricciuti, Federico; Rucci, Alessio; Le Saux, Bertrand; Fumagalli, Alfio; Prati, Claudio, Remote Sensing 15 (24), December 2023.
[ Remote Sensing article / doi / arxiv to appear ]
Multi-task prompt-RSVQA to explicitly count objects on aerial images Christel Chappuis, Charlotte Sertic, Nicolas Santacroce, Javiera Castillo, Sylvain Lobry, Bertrand Le Saux, Devis Tuia, BMVC workshop on Machine Vision for Earth Observation, Aberdeen, UK, Nov. 2023.
[ BMVC workshop proceedings / pdf / arxiv ]
Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images, Su-yeon Chang, M. Grossi, B. Le Saux, S. Vallecorsa, IEEE Quantum Week’23, Bellevue, WA, USA, Sep. 2023 / QTML’23, Geneva, Swittzerland, Nov. 2023.
[ abstract / IEEE QCE proceedings / arxiv ]
Quantum Machine Learning for Remote Sensing: Exploring potential and challenges Artur Miroszewski, Jakub Nalepa, Bertrand Le Saux, Jakub Mielczarek, Big Data from Space’23, Vienna, Austria, Nov. 2023
[ arxiv / BiDS proceedings / BiDS proc. #2 ]
Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection Fulvio Sanguigni, Mikolaj Czerkawski, Lorenzo Papa, Irene Amerini, Bertrand Le Saux, Big Data from Space’23, Vienna, Austria, Nov. 2023
[ arxiv / BiDS proceedings / BiDS proc. #2 / code ]
Super-resolved rainfall prediction with physics-aware deep learning S Moran, B Demir, F Serva, B Le Saux, Big Data from Space’23, Vienna, Austria, Nov. 2023
[ arxiv / BiDS proceedings / BiDS proc. #2 ]
Deep-Learning-based Change Detection with Spaceborne Hyperspectral PRISMA data JF Amieva, A Austoni, MA Brovelli, L Ansalone, P Naylor, F Serva, B Le Saux, Big Data from Space’23, Vienna, Austria, Nov. 2023
[ arxiv / BiDS proceedings / BiDS proc. #2 ]
A Single-Step Multiclass SVM based on Quantum Annealing for Remote Sensing Data Classification Amer Delilbasic, Bertrand Le Saux, Morris Riedel, Kristel Michielsen, Gabriele Cavallaro, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), Vol. 16, November 2023.
[ JSTARS article / doi / arxiv / pdf ]
Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts A. Gruca, F. Serva, …., B. Le Saux, D. Kopp, S. Hochreiter, D. Kreil, Proceedings of Machine Learning Research, vol. 220, Proceedings of the NeurIPS 2022 Competitions Track, 292-313, 2023.
[ PMLR abstract / PMLR pdf ]
Detection of Forest Fires through Deep Unsupervised Learning Modeling of Sentinel-1 Time Series Thomas di Martino, Bertrand Le Saux, Régis Guinvarc’h, Laetitia Thirion-Lefevre, Elise Colin, ISPRS International Journal of Geo-Information, vol. 12, num. 8, August 2023.
[ IJGI version / doi ]
Detecting Clouds in Multispectral Satellite Images Using Quantum-Kernel Support Vector Machines Artur Miroszewski, Jakub Mielczarek, Grzegorz Czelusta, Filip Szczepanek, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 16, August 2023.
[ JSTARS article / doi / arxiv / pdf ]
Rapid Training of Quantum Recurrent Neural Networks, M. Siemaszko, A. Buraczewski, B. Le Saux and M. Stobińska, Quantum Machine Intelligence, vol. 2, num. 5, July 2023.
[ Open-access QMI html / Open-access QMI pdf / arxiv ]
2022 ECMWF-ESA workshop report: current status, progress and opportunities in machine learning for Earth system observation and prediction, Rochelle Schneider, Massimo Bonavita, Rossella Arcucci, Matthew Chantry, Marcin Chrust, Alan Geer, Bertrand Le Saux, and Claudia Vitolo, npj Climate and Atmospheric Science, vol. 6, July 2023.
[ npj article / 2022 ECMWF-ESA workshop at Reading ]
Knowledge distillation for memory-efficient on-board image classification of Mars imagery, Piotr Bosowski, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa, IGARSS 2023, July 2023, Pasadena, CA, USA.
Unbiased validation of hyperspectral unmixing algorithms, Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa, IGARSS 2023, July 2023, Pasadena, CA, USA.
Cloud detection in multispectral satellite images using support vector machines with quantum kernels, Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek, Grzegorz Czelusta, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa, IGARSS 2023, July 2023, Pasadena, CA, USA.
Optimizing Kernel-Target Alignment for cloud detection in multispectral satellite images, Artur Miroszewski, Jakub Mielczarek, Filip Szczepanek, Grzegorz Czelusta, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa, IGARSS 2023, July 2023, Pasadena, CA, USA.
Towards generation of synthetic hyperspectral image datasets with GAN, François De Vieilleville, Adrien Lagrange, Nicolas Dublé, and Bertrand Le Saux, EGU’2023, Vienna, Austria, April 2023.
[ EGU abstract / pdf / doi ]
Confidence estimation of DNN predictions for on-board applications, Nicolas Dublé, François De Vieilleville, Adrien Lagrange, and Bertrand Le Saux, EGU’2023, Vienna, Austria, April 2023.
[ EGU abstract / pdf / doi ]
Correlation between PQC Descriptors and Training Accuracy in Hybrid Quantum-Classical Model for Earth Observation Image Classification, Su-yeon Chang, B. Le Saux, S. Vallecorsa, M. Grossi, Quantum Information Processing (QIP 2023), Ghent, Belgium, February 2023.
[ QIP website ]
Multispectral Satellite Data Analysis Using Support Vector Machines With Quantum Kernels, Artur Miroszewski, F. Szczepanek, G. Czelusta, B. Grabowski, B. Le Saux, J. Nalepa and J. Mielczarek, Quantum Information Processing (QIP 2023), Ghent, Belgium, February 2023.
[ QIP website ]
2022
Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised Learning Hänsch, R.; Persello, C.; Vivone, G.; Castillo Navarro, J.; Boulch, A.; Lefèvre, S.; Le Saux, B., IEEE Geoscience and Remote Sensing Magazine, vol. 10, no. 4, pp. 270-273, Dec. 2022, doi: 10.1109/MGRS.2022.3219935.
[ IEEE GRSM version / doi / DFC 2022 benchmark / data ]
Rapid Training of Quantum Recurrent Neural Networks, M. Siemaszko, T. McDermott, A. Buraczewski, B. Le Saux and M. Stobińska, QTML’2022, Naples, Italy, Nov 2022.
[ arxiv ]
The Hyperview Challenge: Estimating Soil Parameters from Hyperspectral Images Jakub Nalepa, Bertrand Le Saux, Nicolas Longépé, Lukasz Tulczyjew, Michal Myller, Michal Kawulok, Krzysztof Smykala, Michal Gumiela, ICIP 2022, Bordeaux, France, October 2022.
[ editor version / doi / challenge ]
Learning Local Depth Regression from Defocus Blur by Soft-Assignment Encoding, R. Leroy, P. Trouvé, B. Le Saux, B. Buat, F. Champagnat, Optica Applied Optics, October 2022.
[ Appl. Opt. / pdf ]
Hybrid Quantum-Classical Networks for Reconstruction and Classification of Earth Observation Images, Su-yeon Chang, S. Vallecorsa, M. Grossi, B. Le Saux, 21st Int. Ws on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2022), Bari, Italy, October 2022.
[ [ ACAT abstract and material / slides ] ]
Multiclass SVM with Quantum Annealing, A. Delilbasic, G. Cavallaro, B. Le Saux, M. Riedel and K. Michielsen, Quantum Machine Learning workshop at ECML-PKDD 2022, Grenoble, France, Sep 2022.
Rapid Training of Quantum Recurrent Neural Network, M. Siemaszko, T. McDermott, A. Buraczewski, B. Le Saux and M. Stobińska, Quantum Machine Learning workshop at ECML-PKDD 2022, Grenoble, France, Sep 2022.
Language Transformers for Remote Sensing Visual Question Answering, C. Chappuis, V. Mendez, E. Walt, D. Tuia, S. Lobry, B. Le Saux, IGARSS 2022, July 2022.
[ IEEE pdf / IGARSS info ]
Weakly-supervised Continual Learning for Class-Incremental Segmentation, G. Lenczner, A. Chan-Hon-Tong, N. Luminari, B. Le Saux, IGARSS 2022, July 2022.
[ IEEE pdf / arxiv / IGARSS info / code ]
Quantum Convolutional Circuits for Earth Observation Image Classification, Su-yeon Chang, S. Vallecorsa, M. Grossi, B. Le Saux, IGARSS 2022, July 2022.
[ IEEE pdf / IGARSS info ]
ESA-ECMWF Report on recent progress and research directions in machine learning for Earth System observation and prediction, R. Schneider, M. Bonavita, A. Geer, R. Arcucci, P. Dueben, C. Vitolo, B. Le Saux, B. Demir & PP. Mathieu, npj climate and atmospheric science 5 (51), June 2022.
[ NPJ CAS version / doi / workshop website ml4esop.esa.int ]
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa, IEEE Geoscience and Remote Sensing Letters (GRSL), June 2022.
[ editor version / arxiv ]
Graph Neural Networks Extract High-Resolution Cultivated Land Maps From Sentinel-2 Image Series Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé, Bertrand Le Saux, Jakub Nalepa, IEEE Geoscience and Remote Sensing Letters (GRSL), June 2022.
[ editor version / arxiv ]
Self-supervised learning – A way to minimize time and effort for precision agriculture? M. Marszalek, B. Le Saux, PP Mathieu, A. Nowakowski, D. Springer, ISPRS Congress 2022, June 2022.
Prompt-RSVQA: Prompting Visual Context to a Language Model for Remote Sensing Visual Question Answering C. Chappuis, V. Zermatten, S. Lobry, B. Le Saux, D. Tuia, CVPR 2022 / Earth Vision workshop, June 2022.
[ CVF page with abstract / CVPR/EV22 pdf / arxiv to appear ]
2022 IEEE GRSS Data Fusion Contest: Semi-Supervised Learning Hänsch, R.; Persello, C.; Vivone, G.; Castillo Navarro, J.; Boulch, A.; Lefèvre, S.; Le Saux, B., IEEE Geoscience and Remote Sensing Magazine (GRSM), March 2022.
[ editor version / DFC 2022 benchmark / data ]
DIAL: Deep Interactive and Active Learning for Semantic Segmentation in Remote Sensing G. Lenczner, A. Chan-Hon-Tong, B. Le Saux, N. Luminari, G. Le Besnerais, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), March 2022.
[ editor version / arxiv / DIAL code ]
Deep Learning for Archaeological Object Detection on LiDAR: New Evaluation Measures and Insights Marco Fiorucci, Wouter B. Verschoof-van der Vaart, Paolo Soleni, Bertrand Le Saux and Arianna Traviglia, Remote Sensing, March 2022.
[ Open-access editor version ]
2021
Quantum Machine Learning for Earth Observation Images, Su-yeon Chang, S. Vallecorsa, B. Le Saux, NeurIPS 2nd WS on Quantum Tensor Networks in Machine Learning, Dec. 2021.
[ abstract ]
Energy-based Models in Earth Observation: from Generation to Semi-supervised Learning J. Castillo-Navarro, B. Le Saux, A. Boulch, S. Lefèbre, IEEE Trans. on Geosciences and Remote Sensing (TGRS), November 2021.
[ TGRS pdf / doi / arxiv (to appear) ]
CORTEX: An innovative solution for AI on-board, R. Ruiloba, A. Lagrange, N.-M. Lemoine, F. De Vieilleville, B. Le Saux, European CubeSat Symposium, Nov. 2021
[ pdf (to appear) / Project page / Sentinel 2 Ship detection dataset ]
On Circuit-based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification, A. Sebastianelli, D. A. Zaidenberg, D. Spiller, B. Le Saux, S. L. Ullo, IEEE JSTARS, 15, Sep. 2021
[ JSTARS pdf / arxiv / arxiv pdf / code ]
How to find a good image-text embedding for remote sensing visual question answering? C. Chappuis, S. Lobry, B. Kellenberger, B. Le Saux, D. Tuia, ECML-PKDD 2021 / MACLEAN workshop, Sept. 2021.
[ CEUR Proceedings / CEUR pdf / arxiv / arxiv pdf / video ]
Deep Learning‐based Semantic Segmentation in Remote Sensing D. Tuia, D. Marcos, K. Schindler, B. Le Saux chapter of: Deep learning for the Earth Sciences G. Camps-Valls, D. Tuia, XX Zhu, M. Reichstein (ed), Wiley, 2021
[ doi ]
Pix2Point: Learning Outdoor 3D Using Sparse Point Clouds and Optimal Transport R. Leroy, P. Trouvé, F. Champagnat, B. Le Saux, M. Carvalho, MVA 2021, August 2021.
[ MVA’21 pdf / arxiv / arxiv pdf ]
Advantages and Bottlenecks of Quantum Machine Learning for Remote Sensing D. Zaidenberg, A. Sebastianelli, D. Spiller, B. Le Saux, S. L. Ullo, IGARSS 2021, July 2021.
[ IEEE pdf / arxiv / arxiv pdf / IGARSS info ]
Classification and Generation of Earth-observation Images using a Joint Energy-based Model J. Castillo-Navarro, B. Le Saux, A. Boulch, S. Lefèbre, IGARSS 2021, July 2021.
[ IEEE pdf / IGARSS info ]
Long-term Burned Area Reconstruction through Deep Learning S. Lampe, B. Le Saux, I. Vanderkelen, W. Thiery, ICML 2021 / Climate Change AI workshop, July 2021.
Weakly supervised change detection using guided anisotropic diffusion R. Caye Daudt, B. Le Saux, A. Boulch, Y. Gousseau, Maching Learning Journal, June 2021.
[ editor version / doi ]
Energy-based Models for Earth Observation Applications J. Castillo-Navarro, B. Le Saux, A. Boulch, S. Lefèbre, ICLR 2021 / Energy-based Model workshop, April 2021.
Machine learning for Earth system observation and prediction M. Bonavita, R. Arcucci, A. Carrassi, P. Dueben, A. J Geer, B. Le Saux, N. Longépé, P.-P. Mathieu, L. Raynaud, Bulletin of the American Meteorological Society (BAMS) 102 (4) April 2021.
[ article / doi / ECMWF-ESA Workshop on Machine Learning for Earth System Observation and Prediction (ML4ESOP) ]
Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study J. Castillo-Navarro, B. Le Saux, A. Boulch, N. Audebert, S. Lefèbre, Maching Learning Journal, April 2021.
[ editor version / doi / local file / arxiv / hal / MiniFrance dataset ]
2020
Street to Cloud: Improving Flood Maps With Crowdsourcing and Semantic Segmentation V. Sunkara, M. Purri, B. Le Saux, J. Adams, NeurIPS 2020 Workshop on Climate Change AI, virtual, December 2020
[ CCAI page with video / arxiv ]
Large-Scale Semantic 3-D Reconstruction: Outcome of the 2019 IEEE GRSS Data Fusion Contest - Part B Yanchao Lian, Tuo Feng, Jinliu Zhou, Meixia Jia, Aijin Li, Zhaoyang Wu, Licheng Jiao, M. Brown, G. Hager, N. Yokoya, R. Hänsch, B. Le Saux IEEE JSTARS, 14, 1158-1170 November 2020
[ doi (open access) / DFC2019 / Dataset on dataport ]
Large-Scale Semantic 3-D Reconstruction: Outcome of the 2019 IEEE GRSS Data Fusion Contest - Part A H. Chen, M. Lin, H. Zhang, P. D’Angelo, D. Cerra, S. M. Azimi, M. Brown, G. Hager, N. Yokoya, R. Hänsch, B. Le Saux IEEE JSTARS, 12, 922-935 October 2020
[ doi (open access) / DFC2019 / Dataset on dataport ]
Interactive Learning for Semantic Segmentation in Earth Observation G. Lenczner, B. Le Saux, N. Luminari, A. Chan-Hon-Tong, G. Le Besnerais, ECML/PKDD MACLEAN, Virtual / Ghent, Belgium, September 2020
[ Best Student Paper Award / local pdf / CEUR Proc. / ext pdf / DISIR/DISCA video / DISCA code ]
On Auxiliary Losses for Semi-Supervised Semantic Segmentation J. Castillo-Navarro, B. Le Saux, A. Boulch, S. Lefèbre, ECML/PKDD MACLEAN, Virtual / Ghent, Belgium, September 2020
[ local pdf / CEUR Proc. / ext pdf / video ]
DISIR: Deep image segmentation with interactive refinement G. Lenczner, B. Le Saux, N. Luminari, A. Chan-Hon-Tong, G. Le Besnerais, ISPRS Annals, Virtual / Nice, France, August 2020
[ local pdf / ISPRS ann. / ISPRS video / arxiv / DISIR code ]
Flood detection in times series of optical and SAR images C. Rambour, N. Audebert, É. Koeniguer, B. Le Saux, M. Crucianu, M. Datcu, ISPRS Archives, Virtual / Bice, France, August 2020
[ local pdf / ISPRS arch. / hal / SEN12-FLOOD dataset ]
A real-world hyperspectral imaging processing workflow for vegetation stress and hydrocarbon indirect detection D. Dubucq, N. Audebert, V. Achard, S. Fabre, A. Credoz, Ph. Deliot, B. Le Saux, ISPRS Archives, Virtual / Nice, France, August 2020
[ local pdf / ISPRS arch. / hal ]
Segmentation sémantique d’images aériennes avec améliorations interactivesG. Lenczner, B. Le Saux, N. Luminari, A. Chan-Hon-Tong, G. Le Besnerais, RFIAP, Virtual / Vannes, France, June 2020
Pix2Point : prédiction monoculaire de scènes 3D par réseaux de neurones hybrides et transport optimal, Rémy Leroy, Bertrand Le Saux, Marcela Carvalho, Pauline Trouvé-Peloux, and Frédéric Champagnat, RFIAP, Virtual / Vannes, France, June 2020
[ pdf ]
2019
Machine Learning Models for Scene Understanding Bertrand Le Saux, Habilitation Thesis (HDR, University of Paris-Saclay), December 2019
2019 IEEE GRSS Data Fusion Contest: Large-Scale Semantic 3D Reconstruction B. Le Saux, N. Yokoya, R. Hänsch, M. Brown, G. Hager, Geoscience and Remote Sensing Magazine (GRSM), December 2019
[ doi / Open-Access pdf / DFC 2019 website ]
Multitask learning of Height and Semantics From Aerial Images M. Pinheiro de Carvalho, B. Le Saux, P. Trouvé-Peloux, F. Champagnat, A. Almansa Geoscience and Remote Sensing Letters (GRSL), Nov. 2019
[ doi / hal / pdf #1 / code on github ]
Distance transform regression for spatially-aware deep semantic segmentation N. Audebert, A. Boulch, B. Le Saux, S. Lefèvre, Computer Vision and Image Understanding (CVIU), vol. 189, Dec. 2019
Multitask learning for large-scale semantic change detection R. Caye Daudt, B. Le Saux, A. Boulch, Y. Gousseau Computer Vision and Image Understanding (CVIU), vol. 187, Oct. 2019
[ doi / arxiv / pdf / HRSCD dataset ]
Réseaux de neurones semi-supervisés pour la segmentation sémantique en télédétection J. Castillo Navarro, B. Le Saux, A. Boulch, S. Lefèvre Colloque GRETSI, Lille, France, Sept. 2019
Learning to understand Earth-observation images with weak and unreliable ground-truth R. Caye Daudt, A. Chan-Hon-Tong, B. Le Saux, A. Boulch IGARSS 2019, Yokohama, Japan, July 2019
[ ]
Deep Learning for Classification of Hyperspectral Data: A Comparative Review N. Audebert, B. Le Saux, S. Lefèvre IEEE Geoscience and Remote Sensing Magazine, vol. 7 (2), June 2019
[ doi / arxiv / hal / DeepHyperX toolbox ]
Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest Y. Xu, B. Du, L. Zhang, D. Cerra, M. Pato, E. Carmona, S. Prasad, N. Yokoya, R. Hänsch, B. Le Saux IEEE JSTARS, June 2019
[ doi (open access) / DFC2018 ]
Guided Anisotropic Diffusion and Iterative Learning for Weakly Supervised Change Detection R. Caye Daudt, B. Le Saux, A. Boulch, Y. Gousseau IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR / EarthVision 19) Long Beach, Cal., USA, June 2019
[ Best Student Paper Award pdf#1 / pdf#2 / arxiv ]
What data do we need for semantic segmentation in Earth-observation? J. Castillo Navarro, N. Audebert, A. Boulch, B. Le Saux, S. Lefèvre IEEE Joint Urban Remote Sensing Event (JURSE’2019) Vannes, France, May 2019
2019 IEEE GRSS Data Fusion Contest: Large-Scale Semantic 3D Reconstruction B. Le Saux, N. Yokoya, R. Hänsch, M. Brown, G. Hager, Geoscience and Remote Sensing Magazine (GRSM), March 2019
[ doi / Open-Access pdf / DFC 2019 website ]
2018
Fully Convolutional Siamese Networks for Change Detection R. Caye Daudt, B. Le Saux, A. Boulch IEEE Int. Conf. on Image Processing (ICIP’2018) Athens, Greece, October 2018
On Regression Losses for Deep Depth Estimation M. Pinheiro de Carvalho, B. Le Saux, P. Trouvé-Peloux, F. Champagnat, A. Almansa IEEE Int. Conf. on Image Processing (ICIP’2018) Athens, Greece, October 2018
[ pdf / hal / D3-Net code ]
Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks? M. Pinheiro de Carvalho, B. Le Saux, P. Trouvé-Peloux, F. Champagnat, A. Almansa IEEE Eur. Conf. on Computer Vision (ECCV’2018) / Workshop on 3D Reconstruction in the Wild Munich, Germany, September 2018
[ arxiv / pdf / pdf #2 / code and dataset ]
Urban Change Detection for Multispectral Earth Observation Using Convolutional Neural Networks R. Caye Daudt, B. Le Saux, A. Boulch, Y. Gousseau IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2018) Valencia, Spain, July 2018
[ pdf ]
Generative adversarial networks for realistic synthesis of hyperspectral samples N. Audebert, B. Le Saux, S. Lefèvre IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2018) Valencia, Spain, July 2018
Railway Detection: from filtering to segmentation networks B. Le Saux, A. Beaupère, A. Boulch, J. Brossard, A. Manier, G. Villemin IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2018) Valencia, Spain, July 2018
[ pdf ]
Learning speckle suppression in SAR images without ground truth: application to Sentinel-1 time-series A. Boulch, P. Trouvé, É. Koeniguer, F. Janez, B. Le Saux IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2018) Valencia, Spain, July 2018
[ pdf ]
Large-scale semantic classification: outcome of the first year of INRIA Aerial Image Labeling Benchmark B.H. Huang, K.K. Lu, N. Audebert, A. Khalel, Y. Tarabalka, J. Malof, A. Boulch, B. Le Saux, L. Collins, K. Bradbury, S. Lefèvre, M. El-Saban IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2018) Valencia, Spain, July 2018
Estimation de profondeur monoculaire par réseau de neurones et l’apport du flou de défocalisation M. Pinheiro de Carvalho, B. Le Saux, P. Trouvé-Peloux, F. Champagnat, A. Almansa Congrès Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP’2018) Marne-la-Vallée, France, July 2018
[ Best Paper Award pdf #1 / pdf #2 / hal ]
Détection dense de changements par réseaux de neurones siamois R. Caye Daudt, B. Le Saux, A. Boulch, Y. Gousseau Congrès Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP’2018) Marne-la-Vallée, France, July 2018
[ Rodrigo’s site pdf ]
Segmentation sémantique profonde par régression sur cartes de distances signées N. Audebert, A. Boulch, B. Le Saux, S. Lefèvre Congrès Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP’2018) Marne-la-Vallée, France, July 2018
Open data for global multimodal land use classification: Outcome of the 2017 IEEE GRSS Data Fusion Contest N. Yokoya, P. Ghamisi, J. Xia, S. Sukhanov, R. Heremans, C. Debes, B. Bechtel, B. Le Saux, G. Moser, D. Tuia, IEEE JSTARS, 2018
[ https://doi.org/10.1109/JSTARS.2018.2799698 (open access) or pdf #1 ]
Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, ISPRS Journal of Photogrammetry and Remote Sensing, 2018
[ doi arxiv pdf #1 pdf #2 code ]
2017
SnapNet: Unstructured point cloud semantic labeling using deep segmentation networks Alexandre Boulch, Joris Guerry, Bertrand Le Saux, Nicolas Audebert, Computer and Graphics, 2017
SnapNet-R: Consistent 3D Multi-View Semantic Labeling for Robotics Joris Guerry, Alexandre Boulch, Bertrand Le Saux, Julien Moras, aurélien Plyer, David Filliat, ICCV / 3D Reconstruction Meets Semantics workshop, Venice, Italy, Oct. 2017
“Look At This One”: Detection sharing between modality-independent classifiers for robotic people discovery Joris Guerry, Bertrand Le Saux, David Filliat, Eur. Conf. on Mobile Robotics (ECMR), Paris, France, Sept. 2017
Estimation de profondeur à partir d’une seule image avec un réseau adversaire M. Pinheiro de Carvalho, B. Le Saux, P. Trouvé-Peloux, A. Almansa, F. Champagnat, Colloque GRETSI, Juan-les-Pins, France, Sept. 2017
[ pdf ]
Couplage de données géographiques participatives et d’images aériennes par apprentissage profond Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, Colloque GRETSI, Juan-les-Pins, France, Sept. 2017
[ pdf ]
RCNN RGBD pour la détection de personnes en conditions difficiles Joris Guerry, Bertrand Le Saux, David Filliat, Colloque GRETSI, Juan-les-Pins, France, Sept. 2017
[ pdf ]
Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, CVPR / Earth Vision workshop, Hawaï, USA, July 2017
3D laser imaging techniques to improve USaR operations for wide-area surveillance and monitoring of collapsed buildings N. Riviere, A. Amditis, A. Amiez, G. Athanasiou, J. Berggren, A. Boulch, N. Bozabalian, D. Duarte, P.-E. Dupouy, P. Escalas, M. Gerke, F. Giroud, C. Grand, N. Kerle, Y. Lambert, F. Nex, B. Le Saux, A. Schilling , G. Told, Int. Conf. on Information Systems for Crisis Response and Management (ISCRAM), Albi, France, May 2017
[ pdf ]
Multitemporal Very High Resolution From Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest L. Mou, X. Zhu, M. Vakalopoulou, K. Karantzalos, N. Paragios, B. Le Saux, G. Moser, D. Tuia,, IEEE J. of Selected Topics in Applied Earth Observations and Remote Sensing, 2017
[ http://dx.doi.org/10.1109/JSTARS.2017.2696823 (open access) pdf ]
Segment-before-Detect: Vehicle Detection and Classification through Semantic Segmentation of Aerial Images Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, Remote Sensing 9 (4), 2017
Unstructured point cloud semantic labeling using deep segmentation networks Alexandre Boulch, Bertrand Le Saux, Nicolas Audebert, EuroGraphics/3D Object Recognition workshop (3DOR), Lyon, France, April 2017
[pdf ]
SHREC: Point-Cloud Shape Retrieval of Non-Rigid Toys F. A. Limberger, R. C. Wilson, M. Aono, N. Audebert, A. Boulch, B. Bustos, A. Giachetti, A. Godil, B. Le Saux, B. Li, Y. Lu, H.-D. Nguyen, V.-T. Nguyen, V.-K. Pham, I. Sipiran, A. Tatsuma, M.-T. Tran, and S. Velasco-Forero, EuroGraphics/3D Object Recognition workshop (3DOR) / SHREC competition, Lyon, France, April 2017
SHREC: 3D Hand Gesture Recognition Using a Depth and Skeletal Dataset Quentin De Smedt, Hazem Wannous, Jean-Philippe Vandeborre, J. Guerry, B. Le Saux, and D. Filliat, EuroGraphics/3D Object Recognition workshop (3DOR) / SHREC competition, Lyon, France, April 2017
Fusion of heterogeneous data in convolutional networks for urban semantic labeling Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, Joint Urban Remote Sensing Event (JURSE’2017) Dubai, UAE, March 2017
[ 2nd Best Student Paper Award arxiv hal pdf ]
Deep learning for Urban Remote Sensing Nicolas Audebert, Alexandre Boulch, Hicham Randrianarivo, Bertrand Le Saux, Marin Ferecatu, Sébastien Lefèvre, Renaud Marlet, Joint Urban Remote Sensing Event (JURSE’2017) Dubai, UAE, March 2017
[ pdf ]
Cartographie et interprétation de l’environnement par drone Martial Sanfourche, Bertrand Le Saux, Aurélien Plyer et Guy Le Besnerais, Revue Française de Photogramm. et de Télédétection (RFPT), n° spécial drones, 213-214,pp. 55-62, 2017
2016
Semantic segmentation of Earth-observation data using multimodal and multi-scale deep networks Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, Asian Conf. on Computer Vision (ACCV’2016), Taipei, Taiwan, Nov. 2016
[ pdf ]
Processing of Extremely High-Resolution LiDAR and RGB Data: Outcome of the 2015 IEEE GRSS Data Fusion Contest-Part A: 2D Contest M. Campos-Taberner, A. Romero-Soriano, G. Camps-Valls, A. Lagrange, B. Le Saux, A. Beaupère, A. Boulch, A. Chan-Hon-Tong, S. Herbin, H. Randrianarivo, M. Ferecatu, M. Shimoni, G. Moser, D. Tuia, IEEE J. of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
[ pdf #1 or http://dx.doi.org/10.1109/JSTARS.2016.2569162 ]
On the usability of deep networks for object-based image analysis Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, Conf. on Geo Object-Based Image Analysis (GEOBIA’2016) Enschede, Netherlands, Sept. 2016
[ Award for Best Contribution to the ISPRS 2D Semantic Labeling Contest pdf ]
How useful is region-based classification of remote sensing images in a deep learning framework? Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2016) Beijing, China, July 2016
[ pdf ]
Sélection d’algorithmes de classification par réseau de neurones Joris Guerry, Bertrand Le Saux, David Filliat, Rec. Formes et Int. Artificielle (RFIA), Clermont-Ferrand, France, July 2016
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Deep Learning for Remote Sensing Nicolas Audebert, Alexandre Boulch, Adrien Lagrange, Bertrand Le Saux, Sébastien Lefèvre, ONERA-DLR ODAS Workshop, Oberpfaffenhofen, Germany, June 2016
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Structural classifiers for contextual semantic labeling of aerial images Hicham Randrianarivo, Bertrand Le Saux, Nicolas Audebert, Michel Crucianu, Marin Ferecatu, ESA Big Data in Space (BiDS), Tenerife, Spain, March 2016
[ pdf ]
2015
Discriminatively-trained model mixture for object detection in aerial images Hicham Randrianarivo, Bertrand Le Saux, Michel Crucianu, Marin Ferecatu, Image Info. Mining (IIM), Bucharest, Romania, October 2015
Benchmarking classification of Earth-observation data: from learning explicit features to convolutional networks Adrien Lagrange, Bertrand Le Saux, Anne Beaupère, Alexandre Boulch, Adrien Chan Hon Tong, Stéphane Herbin, Hicham Randrianarivo, Marin Ferecatu, IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2015) Milan, Italy, July 2015
[ 2nd place Award in the Data Fusion 2D Contest 2015 link pdf ]
Réseaux de neurones profonds pour estimer la profondeur grâce au flou de défocalisation Thierry Dumas, Pauline Trouvé-Peloux, Bertrand Le Saux, Colloque Gretsi 2015, Lyon, France, September 2015
[ pdf ]
Détection de véhicules en imagerie aérienne par mélange de modèles discriminatifs Hicham Randrianarivo, Bertrand Le Saux, Marin Ferecatu, Colloque Gretsi 2015, Lyon, September 2015
[ pdf ]
Environment Mapping and Interpretation by Drone Martial Sanfourche, Bertrand Le Saux, Aurélien Plyer, Guy Le Besnerais, Joint Urban Remote Sensing Event (JURSE’2015), Lausanne, April 2015
[ pdf ]
2014
Interactive Design of Object Classifiers in Remote Sensing Bertrand Le Saux, International Conference on Pattern Recognition (ICPR’2014), Stockholm, Sweden, August 2014
[ pdf ]
Multimodal Classification with Deformable Part Models for Urban Cartography Hicham Randrianarivo, Bertrand Le Saux, Marin Ferecatu, IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2014), Quebec City, Canada, July 2014. Invited paper in the Data Fusion session.
[ pdf ]
Cartographie et interprétation de l’environnement par drone Martial Sanfourche, Bertrand Le Saux, Aurélien Plyer, Guy Le Besnerais, Congrès de la SFPT - colloque drones, Montpellier, France, June 2014.
[ pdf ]
2013
Rapid semantic mapping: learn environment classifiers on the fly Bertrand Le Saux and Martial Sanfourche, International Conference on Robots and Systems (IROS’2013), Tokyo, November 2013
Apprentissage interactif par Online Gradient Boost en télédétection Bertrand Le Saux, Colloque Gretsi 2013, Brest, September 2013
[ pdf ]
Urban change detection in SAR images by interactive learning Bertrand Le Saux, Hicham Randrianarivo, IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2013), Melbourne, Australia, July 2013
[ pdf ]
Man-made structure detection with deformable part-based models Hicham Randrianarivo, Bertrand Le Saux, Marin Ferecatu, IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2013), Melbourne, Australia, July 2013
[ pdf ]
2012
Boosting for interactive man-made structure classification Nicolas Chauffert, Jonathan Israël, Bertrand Le Saux, IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2012), Munich, Germany, July 2012
[ pdf ]
GPU-accelerated One-Class SVM for exploration of remote sensing data Fabien Giannesini and Bertrand Le Saux, IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2012), Munich, Germany, July 2012
[ pdf ]
2011
Robust vehicle categorization from aerial images by 3D-template matching and multiple classifier system Bertrand Le Saux and Martial Sanfourche, IEEE International Symposium on Image and Signal Processing and Analysis (ISPA’2011), Dubrovnik, Croatia, September 2011
[ pdf ]
2009
Isotropic high resolution 3D confocal micro-rotation imaging for non-adherent living cells Bertrand Le Saux, Bernard Chalmond, Yong Yu, Alain Trouvé, Olivier Renaud, Spencer L. Shorte, Journal of Microscopy, 233, pp.404-416, 2009
[ pdf ]
2008
Micro-rotation Imaging Deconvolution Bertrand Le Saux, Bernard Chalmond, Yong Yu, Alain Trouvé, Olivier Renaud, Spencer L. Shorte, IEEE International Symposium on Biomedical Imaging (ISBI’08), Paris, France, May 2008
[ pdf ]
2006
Combining SVM and Graph Matching in a Multiple Classifier System for Image Content Recognition Bertrand Le Saux and Horst Bunke, Workshop on Statistical Pattern Recognition (S+SSPR’06) of the IAPR International Conference on Pattern Recognition (ICPR’06), Hong Kong, China, August 2006
2005
Feature selection for graph-based image classifiers Bertrand Le Saux and Horst Bunke, IAPR Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA’05), Estoril, Portugal, June 2005
2004
Image recognition for digital libraries Bertrand Le Saux and Giuseppe Amato, ACM MultiMedia/Workshop on Multimedia Information Retrieval (MIR’04), New-York, NY, USA, October 2004
Image classifiers for scene analysis Bertrand Le Saux and Giuseppe Amato, International Conference on Computer Vision and Graphics (ICCVG’04), Warsaw, Poland, September 2004
Image Annotation with Presence-Vector Classifiers Bertrand Le Saux and Giuseppe Amato, ERCIM news, issue 58, July 2004
Image recognition for digital libraries Bertrand Le Saux and Giuseppe Amato, ISTI research report #2004-TR-24
[ pdf ]
Image database clustering with SVM-based class personalization Bertrand Le Saux and Nozha Boujemaa, IS&T/SPIE Conference on Storage and Retrieval Methods and Applications for Multimedia / Electronic Imaging symposium, San José, CA, USA, January 2004
2003
Classification non exclusive et personnalisation par apprentissage : Application à la navigation dans les bases d’images Bertrand Le Saux, PhD Thesis, July 2003
Adaptive Robust Clustering with Proximity-Based Merging for Video-Summary, Bertrand Le Saux, Nizar Grira and Nozha Boujemaa, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’2003), Saint-Louis, MO, USA, May 2003
2002
Unsupervised Robust Clustering for Image Database Categorization, Bertrand Le Saux and Nozha Boujemaa, IEEE-IAPR International Conference on Pattern Recognition (ICPR’2002), Québec, Canada, August 2002
Unsupervised Categorization for Image Database Overview, Bertrand Le Saux and Nozha Boujemaa, International Conference on Visual Information System (VISUAL’2002), Hsin-Chu, Taiwan, March 2002 - LNCS 2314
2001
Interactive Specific and Generic Image Retrieval, Nozha Boujemaa, Julien Fauqueur, Marin Ferecatu, François Fleuret, Valérie Gouet, Bertrand Le Saux and Hichem Sahbi, NSF/INRIA/Berkeley/IBM MMCBIR Workshop, INRIA Rocquencourt, France, September 2001
[ pdf ]
Image Database Browsing, Bertrand Le Saux and Nozha Boujemaa, NSF/INRIA/Berkeley/IBM MMCBIR Workshop, INRIA Rocquencourt, France, September 2001