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Nicolas Thome
- Professeur des universités
- Équipe: MLIA
- Bureau: 26-00 530
- Email: nicolas.thome@isir.upmc.fr
- Telephone:(+33) 1 44 27 87 80
- Addresse: 4, place Jussieu 75005 Paris
- Site web: https://thome.isir.upmc.fr/
Publications
- Yannis Karmim, Marc Lafon, Raphaël Fournier-S'Niehotta, Nicolas Thome. Supra-Laplacian Encoding for Transformer on Dynamic Graphs. The Thirty-eighth Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver (CA), Canada. ⟨hal-04785441⟩
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William Brice Ndzimbong, Nicolas Thome, Nicolas Fourniol, Yvonne Keeza, Benoit Sauer, et al.. Global Registration of Kidneys in 3D Ultrasound and CT images. International Journal of Computer Assisted Radiology and Surgery, 2024, ⟨10.1007/s11548-024-03255-3⟩. ⟨hal-04696291⟩
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- Yannis Karmim, Elias Ramzi, Raphaël Fournier-S 'Niehotta, Nicolas Thome. ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation. Transactions on Machine Learning Research Journal, In press. ⟨hal-04645098⟩
- 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⟩
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William Brice Ndzimbong, Nicolas Thome, Nicolas Fourniol, Yvonne Keeza, Benoit Sauer, et al.. Global Registration of Kidneys in 3D Ultrasound and CT images. IABM - Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale, Grenoble, France, mars 2024, Mar 2024, Grenoble, France. ⟨hal-04530113⟩
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- 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⟩
- Marc Lafon, Elias Ramzi, Clément Rambour, Nicolas Audebert, Nicolas Thome. GalLoP: Learning Global and Local Prompts for Vision-Language Models. The 18th European Conference on Computer Vision ECCV 2024, Sep 2024, Milan, Italy. ⟨10.48550/arXiv.2407.01400⟩. ⟨hal-04635800⟩
- Yannis Karmim, Leshanshui Yang, Raphaël Fournier-S'Niehotta, Clément Chatelain, Sébastien Adam, et al.. Temporal receptive field in dynamic graph learning: A comprehensive analysis. MLG Workshop at ECML-PKDD, Sep 2024, Vilnius (Lituanie), France. ⟨hal-04647025v2⟩
- Mustafa Shukor, Nicolas Thome, Matthieu Cord. Vision and Structured-Language Pretraining for Cross-Modal Food Retrieval. Computer Vision and Image Understanding, 2024, 247. ⟨hal-04743466⟩
- 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⟩
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Denis Coquenet, Clément Rambour, Emanuele Dalsasso, Nicolas Thome. Leveraging Vision-Language Foundation Models for Fine-Grained Downstream Tasks. 2023. ⟨hal-04162923⟩
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- 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⟩
- Elias Ramzi, Nicolas Audebert, Nicolas Thome, Clément Rambour, Xavier Bitot. Hierarchical Average Precision Training for Pertinent Image Retrieval. ORASIS 2023, Laboratoire LIS, UMR 7020, May 2023, Carqueiranne, France. ⟨hal-04219526⟩
- 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⟩
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Laura Calem, Hedi Ben-Younes, Patrick Perez, Nicolas Thome. Diverse Probabilistic Trajectory Forecasting with Admissibility Constraints. 2022 26th International Conference on Pattern Recognition (ICPR), Aug 2022, Montreal, Canada. pp.3478-3484, ⟨10.1109/ICPR56361.2022.9956270⟩. ⟨hal-04071275⟩
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- 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⟩
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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, 2022, 44 (10), pp.6043-6055. ⟨10.1109/TPAMI.2021.3085983⟩. ⟨hal-03252079⟩
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- Rémy Sun, Clément Masson, Gilles Hénaff, Nicolas Thome, Matthieu Cord. Swapping Semantic Contents for Mixing Images. 2022 26th International Conference on Pattern Recognition (ICPR), Aug 2022, Montreal, Canada. pp.1280-1286, ⟨10.1109/ICPR56361.2022.9956602⟩. ⟨hal-03951744⟩
- 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⟩
- Rémy Sun, Alexandre Ramé, Clément Masson, Nicolas Thome, Matthieu Cord. Towards efficient feature sharing in MIMO architectures. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Jun 2022, New Orleans, United States. pp.2696-2700, ⟨10.1109/CVPRW56347.2022.00303⟩. ⟨hal-03951737⟩
- 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⟩
- 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⟩
- Loic Themyr, Clément Rambour, Nicolas Thome, Toby Collins, Alexandre Hostettler. Memory transformers for full context and high-resolution 3D Medical Segmentation. Machine Learning in Medical Imaging. MLMI 2022, 2022, Singapour, Singapore. ⟨10.48550/arXiv.2210.05313⟩. ⟨hal-03769673⟩
- 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⟩
- 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. 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⟩
- 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⟩
- 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⟩
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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⟩
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- 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⟩
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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⟩
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