Home » Teams » MLIA » Nicolas Thome
  • Nicolas Thome

  • Full Professor
  • Team: MLIA
  • Office: 26-00 530
  • Email: nicolas.thome@isir.upmc.fr
  • Phone:(+33) 1 44 27 87 80
  • Addresse: 4, place Jussieu 75005 Paris
  • Website: https://thome.isir.upmc.fr/

Publications

  • Emanuele Dalsasso, Clément Rambour, Nicolas Trouvé, Nicolas Thome. MERLIN-Seg: self-supervised despeckling for label-efficient semantic segmentation. Computer Vision and Image Understanding, 2024, 241, ⟨10.1016/j.cviu.2024.103940⟩. ⟨hal-04163624v2⟩
  • Rémy Sun, Clément Masson, Gilles Hénaff, Nicolas Thome, Matthieu Cord. Semantic augmentation by mixing contents for semi-supervised learning. Pattern Recognition, 2024, 145, pp.109909. ⟨10.1016/j.patcog.2023.109909⟩. ⟨hal-04385089⟩
  • Clément Brochet, Laure Raynaud, Nicolas Thome, Matthieu Plu, Clément Rambour. Multivariate Emulation of Kilometer-Scale Numerical Weather Predictions with Generative Adversarial Networks: A Proof of Concept. Artificial Intelligence for the Earth Systems, 2023, 2 (4), ⟨10.1175/AIES-D-23-0006.1⟩. ⟨meteo-04438969⟩
  • Denis Coquenet, Clément Rambour, Emanuele Dalsasso, Nicolas Thome. Leveraging Vision-Language Foundation Models for Fine-Grained Downstream Tasks. 2023. ⟨hal-04162923⟩
  • Marc Lafon, Elias Ramzi, Clément Rambour, Nicolas Thome. Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection. International Conference on Machine Learning, Jul 2023, Honololu, Hawaii, United States. ⟨hal-04112184v2⟩
  • Steeven Janny, Aurélien Beneteau, Madiha Nadri, Julie Digne, Nicolas Thome, et al.. EAGLE: Large-Scale Learning of Turbulent Fluid Dynamics with Mesh Transformers. International Conference on Learning Representation, May 2023, Kigali, Rwanda. ⟨hal-03992436v2⟩
  • Nicolas Thome, Christian Wolf. Histoire des réseaux de neurones et du deep learning en traitement des signaux et des images. 2023. ⟨hal-04058482⟩
  • Loïc Themyr, Clément Rambour, Nicolas Thome, Toby Collins, Alexandre Hostettler. Full Contextual Attention for Multi-resolution Transformers in Semantic Segmentation. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Jan 2023, Waikoloa, United States. pp.3223-3232, ⟨10.1109/WACV56688.2023.00324⟩. ⟨hal-03901666⟩
  • Vincent Le Guen, Clément Rambour, Nicolas Thome. Complementing Brightness Constancy with Deep Networks for Optical Flow Prediction. ECCV 2022, Oct 2022, Tel Aviv, Israel. ⟨10.1007/978-3-031-19803-8_8⟩. ⟨hal-03717740⟩
  • Elias Ramzi, Nicolas Audebert, Nicolas Thome, Clément Rambour, Xavier Bitot. Hierarchical Average Precision Training for Pertinent Image Retrieval. ECCV 2022, Oct 2022, Tel-Aviv, Israel. ⟨hal-03712933v2⟩
  • Éric Bavu, Hadrien Pujol, Alexandre Garcia, Christophe Langrenne, Sébastien Hengy, et al.. Deeplomatics: A deep-learning based multimodal approach for aerial drone detection and localization. QUIET DRONES Second International e-Symposium on UAV/UAS Noise, INCE/Europe; CidB, Jun 2022, Paris, France. ⟨hal-03707115⟩
  • Nicolas Thome, Luc Soler, Olivier Petit. 3D Spatial Priors for Semi-Supervised Organ Segmentation with Deep Convolutional Neural Networks. International Journal of Computer Assisted Radiology and Surgery, 2022, 17 (1), pp.129-139. ⟨10.1007/s11548-021-02494-y⟩. ⟨hal-03337091⟩
  • Vincent Le Guen, Nicolas Thome. Deep Time Series Forecasting with Shape and Temporal Criteria. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 45 (1), pp.342-355. ⟨10.1109/TPAMI.2022.3152862⟩. ⟨hal-03588390⟩
  • Yuan Yin, Vincent Le Guen, Jérémie Donà, Emmanuel de Bézenac, Ibrahim Ayed, et al.. Augmenting physical models with deep networks for complex dynamics forecasting. Journal of Statistical Mechanics: Theory and Experiment, 2021, 2021 (12), pp.124012. ⟨10.1088/1742-5468/ac3ae5⟩. ⟨hal-03508401v2⟩
  • 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⟩
  • Olivier Petit, Nicolas Thome, Clement Rambour, Loic Themyr, Toby Collins, et al.. U-Net Transformer: Self and Cross Attention for Medical Image Segmentation. MICCAI workshop MLMI, Sep 2021, Strasbourg (virtuel), France. ⟨hal-03337089⟩
  • Charles Corbière, Marc Lafon, Nicolas Thome, Matthieu Cord, Patrick Pérez. Beyond First-Order Uncertainty Estimation with Evidential Models for Open-World Recognition. ICML 2021 Workshop on Uncertainty and Robustness in Deep Learning, Sep 2021, Virtual, Austria. ⟨hal-03347628⟩
  • Olivier Petit, Nicolas Thome, Luc Soler. Iterative Confidence Relabeling with Deep ConvNets for Organ Segmentation with Partial Labels. Computerized Medical Imaging and Graphics, 2021, pp.101938. ⟨10.1016/j.compmedimag.2021.101938⟩. ⟨hal-03243619⟩
  • Charles Corbière, Nicolas Thome, Antoine Saporta, Tuan-Hung Vu, Matthieu Cord, et al.. Confidence Estimation via Auxiliary Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, In press, pp.1-1. ⟨10.1109/TPAMI.2021.3085983⟩. ⟨hal-03252079⟩
  • Yuan Yin, Vincent Le Guen, Jérémie Dona, Ibrahim Ayed, Emmanuel de Bézenac, et al.. Augmenting physical models with deep networks for complex dynamics forecasting. Ninth International Conference on Learning Representations ICLR 2021, 2021, Vienna (virtual), Austria. ⟨hal-03137025⟩
  • Vincent Le Guen, Nicolas Thome. Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity. NeurIPS 2020, Dec 2020, Vancouver, Canada. ⟨hal-02992358⟩
  • Vincent Le Guen, Nicolas Thome. Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction. Computer Vision and Pattern Recognition 2020 (CVPR), Jun 2020, Seattle, United States. ⟨10.1109/CVPR42600.2020.01149⟩. ⟨hal-02947331⟩
  • Vincent Le Guen, Nicolas Thome. A Deep Physical Model for Solar Irradiance Forecasting with Fisheye Images. CVPR OmniCV worshop 2020, Jun 2020, Seattle, United States. ⟨10.1109/CVPRW50498.2020.00323⟩. ⟨hal-02947332⟩
  • Charles Corbière, Nicolas Thome, Avner Bar-Hen, Matthieu Cord, Patrick Pérez. Addressing Failure Prediction by Learning Model Confidence. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Dec 2019, Vancouver, Canada. pp.2898-2909. ⟨hal-02469747⟩
  • Vincent Le Guen, Nicolas Thome. Prévision de l’irradiance solaire par réseaux de neurones profonds à l’aide de caméras au sol. GRETSI 2019, Aug 2019, Lille, France. ⟨hal-02948131⟩
  • Thi-Lam-Thuy Le, Nicolas Thome, Sylvain Bernard, Vincent Bismuth, Fanny Patoureaux. Multitask Classification and Segmentation for Cancer Diagnosis in Mammography. 2019. ⟨hal-02986361⟩
  • Remi Cadene, Hedi Ben-Younes, Matthieu Cord, Nicolas Thome. MUREL: Multimodal Relational Reasoning for Visual Question Answering. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2019, Long Beach, CA, United States. ⟨hal-02073649⟩
  • Thibaut Durand, Nicolas Thome, Matthieu Cord. Exploiting Negative Evidence for Deep Latent Structured Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019, 41 (2), pp.337-351. ⟨10.1109/TPAMI.2017.2788435⟩. ⟨hal-01969819⟩
  • Hedi Ben-Younes, Remi Cadene, Nicolas Thome, Matthieu Cord. BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection. AAAI 2019 - 33rd AAAI Conference on Artificial Intelligence, Jan 2019, Honolulu, United States. ⟨hal-02073644⟩
  • Michael Blot, David Picard, Nicolas Thome, Matthieu Cord. Distributed Optimization for Deep Learning with Gossip Exchange. Neurocomputing, 2019, 330, pp.287-296. ⟨10.1016/j.neucom.2018.11.002⟩. ⟨hal-01930346⟩
  • Vincent Le Guen, Nicolas Thome. Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), Dec 2019, Vancouver, Canada. ⟨hal-02291601⟩
  • Taylor Mordan, Nicolas Thome, Gilles Henaff, Matthieu Cord. Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual Detection. 32nd Conference on Neural Information Processing Systems (NeurIPS), Dec 2018, Montréal, Canada. ⟨hal-01922291v3⟩
  • Marion Chevalier, Nicolas Thome, Gilles Henaff, Matthieu Cord. Classifying low-resolution images by integrating privileged information in deep CNNs. Pattern Recognition Letters, 2018, 116, pp.29-35. ⟨10.1016/j.patrec.2018.09.007⟩. ⟨hal-02470742⟩
  • Thibaut Durand, Nicolas Thome, Matthieu Cord. SyMIL: MinMax Latent SVM for Weakly Labeled Data. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29 (12), pp.6099-6112. ⟨10.1109/TNNLS.2018.2820055⟩. ⟨hal-01972163⟩
  • Michael Blot, Thomas Robert, Nicolas Thome, Matthieu Cord. SHADE: Information-Based Regularization for Deep Learning. ICIP 2018 - 25th IEEE International Conference on Image Processing, Oct 2018, Athènes, Greece. pp.813-817, ⟨10.1109/ICIP.2018.8451092⟩. ⟨hal-01994740⟩
  • Thomas Robert, Nicolas Thome, Matthieu Cord. HybridNet: Classification and Reconstruction Cooperation for Semi-supervised Learning. ECCV 2018 - 15th European Conference on Computer Vision, Sep 2018, Munich, Germany. pp.158-175, ⟨10.1007/978-3-030-01234-2_10⟩. ⟨hal-02073640⟩
  • Olivier Petit, Nicolas Thome, Arnaud Charnoz, Alexandre Hostettler, Luc Soler. Handling Missing Annotations for Semantic Segmentation with Deep ConvNets. MICCAI workshop DLMIA, Sep 2018, Grenade, Spain. pp.20-28, ⟨10.1007/978-3-030-00889-5_3⟩. ⟨hal-02471187⟩
  • Taylor Mordan, Nicolas Thome, Gilles Henaff, Matthieu Cord. End-to-End Learning of Latent Deformable Part-Based Representations for Object Detection. International Journal of Computer Vision, 2018, ⟨10.1007/s11263-018-1109-z⟩. ⟨hal-01842031⟩
  • Micael Carvalho, Rémi Cadène, David Picard, Laure Soulier, Nicolas Thome, et al.. Cross-Modal Retrieval in the Cooking Context. SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, Jul 2018, Ann Arbor, Michigan, United States. pp.35-44, ⟨10.1145/3209978.3210036⟩. ⟨hal-01839068⟩
  • Xin Wang, Nicolas Thome, Matthieu Cord. Gaze Latent Support Vector Machine for Image Classification Improved by Weakly Supervised Region Selection. Pattern Recognition, 2017, 72, pp.59-71. ⟨10.1016/j.patcog.2017.07.001⟩. ⟨hal-01557368⟩
  • Hedi Ben-Younes, Remi Cadene, Matthieu Cord, Nicolas Thome. MUTAN: Multimodal Tucker Fusion for Visual Question Answering. 2017 IEEE International Conference on Computer Vision (ICCV), Oct 2017, Venice, Italy. pp.2631-2639, ⟨10.1109/ICCV.2017.285⟩. ⟨hal-02073637⟩
  • Taylor Mordan, Nicolas Thome, Matthieu Cord, Gilles Henaff. Deformable Part-based Fully Convolutional Network for Object Detection. British Machine Vision Conference (BMVC), Sep 2017, London, United Kingdom. ⟨hal-01637070⟩
  • Thibaut Durand, Taylor Mordan, Nicolas Thome, Matthieu Cord. WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), IEEE, Jul 2017, Honolulu, HI, United States. pp.5957-5966, ⟨10.1109/CVPR.2017.631⟩. ⟨hal-01515640⟩
  • Micael Carvalho, Matthieu Cord, Sandra Avila, Nicolas Thome, Eduardo Valle. Deep Neural Networks Under Stress. IEEE International Conference on Image Processing (ICIP 2016), Sep 2016, Phoenix, AZ, United States. ⟨10.1109/ICIP.2016.7533200⟩. ⟨hal-01340298⟩
  • Xin Wang, Nicolas Thome, Matthieu Cord. GAZE LATENT SUPPORT VECTOR MACHINE FOR IMAGE CLASSIFICATION. IEEE International Conference on Image Processing (ICIP), IEEE, Sep 2016, Phoenix, AZ, United States. ⟨10.1109/ICIP.2016.7532354⟩. ⟨hal-01342580⟩
  • Thibaut Durand, Nicolas Thome, Matthieu Cord. WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Jun 2016, Las Vegas, NV, United States. ⟨hal-01343785⟩
  • Marion Chevalier, Nicolas Thome, Matthieu Cord, Jérôme Fournier, Gilles Henaff, et al.. LOW RESOLUTION CONVOLUTIONAL NEURAL NETWORK FOR AUTOMATIC TARGET RECOGNITION. 7th International Symposium on Optronics in Defence and Security, Feb 2016, Paris, France. ⟨hal-01332061⟩
  • Michael Blot, Matthieu Cord, Nicolas Thome. Max-min convolutional neural networks for image classification. ICIP 2016 - IEEE International Conference on Image Processing, Sep 2016, Phoenix, United States. pp.3678-3682, ⟨10.1109/ICIP.2016.7533046⟩. ⟨hal-01372216⟩
  • Marc T. Law, Nicolas Thome, Matthieu Cord. Learning a Distance Metric from Relative Comparisons between Quadruplets of Images. International Journal of Computer Vision, 2016, pp.1-30. ⟨10.1007/s11263-016-0923-4⟩. ⟨hal-01346190⟩
  • Thibaut Durand, Nicolas Thome, Matthieu Cord. MANTRA: Minimum Maximum Latent Structural SVM for Image Classification and Ranking. IEEE International Conference on Computer Vision (ICCV15), Dec 2015, Santiago, Chile. ⟨hal-01343784⟩