Jules Sanchez - RankMe

12 papers A* 2Journal 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	3DLabelProp: Geometric-Driven Domain Generalization for LiDAR Semantic Segmentation in Autonomous Driving. CoRR Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
2025	J	`jnl`	COLA: COarse-LAbel Multisource LiDAR Semantic Segmentation for Autonomous Driving. IEEE Trans. Robotics Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
2024	J	`jnl`	ParisLuco3D: A High-Quality Target Dataset for Domain Generalization of LiDAR Perception. IEEE Robotics Autom. Lett. Jules Sanchez, Louis Soum-Fontez, Jean-Emmanuel Deschaud, François Goulette
2023	A*	`conf`	COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasets. ICRA Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
2023	J	`jnl`	COLA: COarse-LAbel multi-source LiDAR semantic segmentation for autonomous driving. CoRR Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
2023	A*	`conf`	Domain generalization of 3D semantic segmentation in autonomous driving. ICCV Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
2023	—	`—`	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). Jules Sanchez
2023	J	`jnl`	ParisLuco3D: A high-quality target dataset for domain generalization of LiDAR perception. CoRR Jules Sanchez, Louis Soum-Fontez, Jean-Emmanuel Deschaud, François Goulette
2022	J	`jnl`	COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasets. CoRR Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
2022	J	`jnl`	Domain generalization of 3D semantic segmentation in autonomous driving. CoRR Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
2022	J	`jnl`	EXplainable Neural-Symbolic Learning ( Inf. Fusion Natalia Díaz Rodríguez, Alberto Lamas, Jules Sanchez, Gianni Franchi, Ivan Donadello, Siham Tabik, David Filliat, Policarpo Cruz, Rosana Montes, Francisco Herrera
2021	J	`jnl`	EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case. CoRR Natalia Díaz Rodríguez, Alberto Lamas, Jules Sanchez, Gianni Franchi, Ivan Donadello, Siham Tabik, David Filliat, Policarpo Cruz, Rosana Montes, Francisco Herrera