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Jules Sanchez

3 accepted papers

2024

ParisLuco3D: A High-Quality Target Dataset for Domain Generalization of LiDAR Perception

RA-L 2024

LiDAR is an essential sensor for autonomous driving by collecting precise geometric information regarding a scene. As the performance of various LiDAR perception tasks has improved, generalizations to new environments and sensors has emerged to test these optimized models in real-world conditions. U

Cited by 5SourceScholar
2023

COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasets

ICRA 2023poster

Transfer learning is a proven technique in 2D computer vision to leverage the large amount of data available and achieve high performance with datasets limited in size due to the cost of acquisition or annotation. In 3D, annotation is known to be a costly task; nevertheless, pre-training methods hav…

Cited by 8SourcecodeScholar
2023

Domain Generalization of 3D Semantic Segmentation in Autonomous Driving

ICCV 2023poster

Using deep learning, 3D autonomous driving semantic segmentation has become a well-studied subject, with methods that can reach very high performance. Nonetheless, because of the limited size of the training datasets, these models cannot see every type of object and scene found in real-world applica…

Cited by 33PDFcodeScholar