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Nicolas Audebert

I am an associate professor in computer science at the Conservatoire national des arts et métiers (Cnam) in Paris, France. My research focuses on deep representation learning for images and signals, with an applicative taste for remote sensing and Earth Observation. I also dabble in machine learning for games and other applications that look fun and challenging.

I hold a PhD in Computer Science from the University of South Brittany (France), prepared jointly between ONERA and IRISA, supervised by Sébastien Lefèvre and Bertrand Le Saux, focused on deep multi-modal learning for automated mapping from aerial and satellite images.

Take a look at my personal website for more information.

Journal articles7 documents

  • Javiera Castillo-Navarro, Bertrand Le Saux, Alexandre Boulch, Nicolas Audebert, Sébastien Lefèvre. Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance suite, dataset analysis and multi-task network study. Machine Learning, Springer Verlag, 2021, ⟨10.1007/s10994-020-05943-y⟩. ⟨hal-03132924⟩
  • Clément Rambour, Nicolas Audebert, E. Koeniguer, B. Le Saux, M. Crucianu, et al.. Flood detection in time series of optical and sar images. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Copernicus GmbH (Copernicus Publications), 2020, XLIII-B2-2020, pp.1343-1346. ⟨10.5194/isprs-archives-XLIII-B2-2020-1343-2020⟩. ⟨hal-02924220⟩
  • Nicolas Audebert, Alexandre Boulch, Bertrand Le Saux, Sébastien Lefèvre. Distance transform regression for spatially-aware deep semantic segmentation. Computer Vision and Image Understanding, Elsevier, 2019, 189, pp.102809. ⟨10.1016/j.cviu.2019.102809⟩. ⟨hal-02277621⟩
  • Nicolas Audebert, Bertrand Saux, Sébastien Lefèvre. Deep Learning for Classification of Hyperspectral Data: A Comparative Review. IEEE geoscience and remote sensing magazine, IEEE, 2019, 7 (2), pp.159-173. ⟨10.1109/MGRS.2019.2912563⟩. ⟨hal-02104998⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks. ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, 2018, 140, pp.20-32. ⟨10.1016/j.isprsjprs.2017.11.011⟩. ⟨hal-01636145⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. Segment-before-Detect: Vehicle Detection and Classification through Semantic Segmentation of Aerial Images. Remote Sensing, MDPI, 2017, 9 (4), page 1-18. ⟨10.3390/rs9040368⟩. ⟨hal-01529624⟩
  • Alexandre Boulch, Joris Guerry, Bertrand Le Saux, Nicolas Audebert. SnapNet: 3D point cloud semantic labeling with 2D deep segmentation networks. Computers and Graphics, Elsevier, 2017, 71, pp.189-198. ⟨10.1016/j.cag.2017.11.010⟩. ⟨hal-02467932⟩

Conference papers19 documents

  • Xinying Cheng, Rafik Zayani, Marin Ferecatu, Nicolas Audebert. Efficient Autoprecoder-based deep learning for massive MU-MIMO Downlink under PA Non-Linearities. IEEE Wireless Communications and Networking Conference, Apr 2022, Austin, United States. ⟨hal-03551457⟩
  • Francesco Foscarin, Nicolas Audebert, Raphaël Fournier-S'Niehotta. PKSpell: Data-Driven Pitch Spelling and Key Signature Estimation. International Society for Music Information Retrieval Conference (ISMIR), Nov 2021, Online, India. ⟨hal-03300102⟩
  • Chen Dang, Hicham Randrianarivo, Raphaël Fournier-S'Niehotta, Nicolas Audebert. Web Image Context Extraction with Graph Neural Networks and Sentence Embeddings on the DOM tree. GEM: Graph Embedding and Mining - ECML/PKDD Workshops, Sep 2021, Bilbao, Spain. ⟨hal-03324009⟩
  • Elias Ramzi, Nicolas Thome, Clément Rambour, Nicolas Audebert, Xavier Bitot. Robust and Decomposable Average Precision for Image Retrieval. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), Dec 2021, Sydney, Australia. ⟨hal-03359605v3⟩
  • Dominique Dubucq, Nicolas Audebert, Véronique Achard, Alexandre Alakian, Sophie Fabre, et al.. A real-world hyperspectral image processing workflow for vegetatotion stress and hydrocarbon indirect detection. XXIV ISPRS Congress, Aug 2020, Nice, France. ⟨10.5194/isprs-archives-XLIII-B3-2020-395-2020⟩. ⟨hal-02924091⟩
  • Javiera Castillo-Navarro, Nicolas Audebert, Alexandre Boulch, Bertrand Le Saux, Sébastien Lefèvre. What Data are needed for Semantic Segmentation in Earth Observation?. 2019 Joint Urban Remote Sensing Event (JURSE), May 2019, Vannes, France. pp.1-4, ⟨10.1109/JURSE.2019.8809071⟩. ⟨hal-02343915v2⟩
  • Nicolas Audebert, Catherine Herold, Kuider Slimani, Cédric Vidal. Multimodal deep networks for text and image-based document classification. Conférence Nationale sur les Applications Pratiques de l'Intelligence Artificielle (APIA), Jul 2019, Toulouse, France. ⟨hal-02163257⟩
  • Bohao Huang, Kangkang Lu, Nicolas Audebert, Andrew Khalel, Yuliya Tarabalka, et al.. Large-scale semantic classification: outcome of the first year of Inria aerial image labeling benchmark. IGARSS 2018 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2018, Valencia, Spain. pp.1-4, ⟨10.1109/IGARSS.2018.8518525⟩. ⟨hal-01767807⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. Generative Adversarial Networks for Realistic Synthesis of Hyperspectral Samples. International Geoscience and Remote Sensing Symposium (IGARSS 2018), Jul 2018, Valencia, Spain. ⟨10.1109/IGARSS.2018.8518321⟩. ⟨hal-01809872⟩
  • Nicolas Audebert, Alexandre Boulch, Bertrand Le Saux, Sébastien Lefèvre. Segmentation sémantique profonde par régression sur cartes de distances signées. Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP), Jun 2018, Marne-la-Vallée, France. ⟨hal-01809991⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps. EARTHVISION 2017 IEEE/ISPRS CVPR Workshop. Large Scale Computer Vision for Remote Sensing Imagery, Jul 2017, Honolulu, United States. ⟨10.1109/CVPRW.2017.199⟩. ⟨hal-01523573⟩
  • Amina Ben Hamida, Alexandre Benoit, P. Lambert, L Klein, Chokri Ben Amar, et al.. DEEP LEARNING FOR SEMANTIC SEGMENTATION OF REMOTE SENSING IMAGES WITH RICH SPECTRAL CONTENT. IEEE International Geoscience and Remote Sensing Symposium, Jul 2017, Fort Worth, United States. ⟨hal-01654187⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. Réseaux de neurones profonds et fusion de données pour la segmentation sémantique d'images aériennes. ORASIS, GREYC, 2017, Colleville-sur-Mer, France. ⟨hal-01672871⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. Fusion of Heterogeneous Data in Convolutional Networks for Urban Semantic Labeling (Invited Paper). Joint Urban Remote Sensing Event (JURSE), Mar 2017, Dubai, United Arab Emirates. ⟨10.1109/JURSE.2017.7924566⟩. ⟨hal-01438499⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. Couplage de données géographiques participatives et d'images aériennes par apprentissage profond. GRETSI, 2017, Juan-les-Pins, France. ⟨hal-01672870⟩
  • Nicolas Audebert, Alexandre Boulch, Hicham Randrianarivo, Bertrand Le Saux, Marin Ferecatu, et al.. Deep learning for urban remote sensing. Joint Urban Remote Sensing Event (JURSE), Mar 2017, Dubai, United Arab Emirates. ⟨10.1109/JURSE.2017.7924536⟩. ⟨hal-01672854⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. On the usability of deep networks for object-based image analysis. International Conference on Geographic Object-Based Image Analysis (GEOBIA), Sep 2016, Enschede, Netherlands. ⟨hal-01320010⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. How Useful is Region-based Classification of Remote Sensing Images in a Deep Learning Framework?. IEEE International Geosciences and Remote Sensing Symposium (IGARSS), Jul 2016, Beijing, China. ⟨10.1109/IGARSS.2016.7730327⟩. ⟨hal-01320016⟩
  • Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre. Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks. Asian Conference on Computer Vision (ACCV16), Nov 2016, Taipei, Taiwan. ⟨10.1007/978-3-319-54181-5_12⟩. ⟨hal-01360166⟩

Preprints, Working Papers, ...2 documents

  • Perla Doubinsky, Nicolas Audebert, Michel Crucianu, Hervé Le Borgne. Multi-Attribute Balanced Sampling for Disentangled GAN Controls. 2022. ⟨hal-03404279v2⟩
  • Adrien Chan-Hon-Tong, Nicolas Audebert. Pointing is sufficient for remote sensing images. 2017. ⟨hal-01412086v6⟩

Theses1 document

  • Nicolas Audebert. Classification de données massives de télédétection. Vision par ordinateur et reconnaissance de formes [cs.CV]. Université de Bretagne Sud, 2018. Français. ⟨NNT : 2018LORIS502⟩. ⟨tel-02073908⟩