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Présentation de l'équipe
Dernières entrées
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Jean Mélou, Yvain Quéau, Antoine Laurent, Marjorie Redon, Jean-Denis Durou, et al.. Thin Details Meet Large-Scale 3D-Reconstruction: Photometric Stereo for Cultural Heritage. 1st international conference on artificIAl Intelligence and applied MAthematics for History and Archaeology (IAMAHA 2023), CEPAM; INRIA Côte d'Azur; I3S, Nov 2023, Nice, France. pp.Session 3 : AI-AM FOR MATERIALS OF THE PAST. ⟨hal-04559503⟩
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Baptiste Brument, Robin Bruneau, Yvain Quéau, Jean Mélou, François Lauze, et al.. RNb-NeuS: Reflectance and Normal-based Multi-View 3D Reconstruction. IEEE / CVF International Conference on Computer Vision and Pattern Recognition (CVPR 2024), IEEE, Jun 2024, Seattle, United States. à paraître. ⟨hal-04526751v2⟩
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Julien Denize, Mykola Liashuha, Jaonary Rabarisoa, Astrid Orcesi, Romain Hérault. COMEDIAN: Self-supervised learning and knowledge distillation for action spotting using transformers. WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision, Jan 2024, Waikoloa, United States. ⟨10.48550/arXiv.2309.01270⟩. ⟨hal-04462159⟩
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Lucas Deregnaucourt, Alexis Lerchervy, Hind Laghmara, Samia Ainouz. An Evidential Deep Network Based on Dempster-Shafer Theory for Large Dataset. Florentin Smarandache; Jean Dezert; Albena Tchamova. Advances and Applications of DSmT for Information Fusion: Collected Works(Volume 5), pp.907-914, 2023. ⟨hal-04448387⟩