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Jules Sanchez
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2020 – today
- 2024
- [j2]Jules Sanchez, Louis Soum-Fontez, Jean-Emmanuel Deschaud, François Goulette:
ParisLuco3D: A High-Quality Target Dataset for Domain Generalization of LiDAR Perception. IEEE Robotics Autom. Lett. 9(6): 5496-5503 (2024) - 2023
- [b1]Jules Sanchez:
Généralisation de domaine pour la segmentation sémantique de données LiDAR pour le véhicule autonome. (Domain generalization for the semantic segmentation of LiDAR data for autonomous vehicles). PSL University, Paris, France, 2023 - [c2]Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette:
Domain generalization of 3D semantic segmentation in autonomous driving. ICCV 2023: 18031-18041 - [c1]Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette:
COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasets. ICRA 2023: 11343-11350 - [i5]Jules Sanchez, Louis Soum-Fontez, Jean-Emmanuel Deschaud, François Goulette:
ParisLuco3D: A high-quality target dataset for domain generalization of LiDAR perception. CoRR abs/2310.16542 (2023) - [i4]Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette:
COLA: COarse-LAbel multi-source LiDAR semantic segmentation for autonomous driving. CoRR abs/2311.03017 (2023) - 2022
- [j1]Natalia Díaz Rodríguez, Alberto Lamas, Jules Sanchez, Gianni Franchi, Ivan Donadello, Siham Tabik, David Filliat, Policarpo Cruz, Rosana Montes, Francisco Herrera:
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: The MonuMAI cultural heritage use case. Inf. Fusion 79: 58-83 (2022) - [i3]Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette:
COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasets. CoRR abs/2202.06884 (2022) - [i2]Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette:
Domain generalization of 3D semantic segmentation in autonomous driving. CoRR abs/2212.04245 (2022) - 2021
- [i1]Natalia Díaz Rodríguez, Alberto Lamas, Jules Sanchez, Gianni Franchi, Ivan Donadello, Siham Tabik, David Filliat, Policarpo Cruz, Rosana Montes, Francisco Herrera:
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case. CoRR abs/2104.11914 (2021)
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