29 citations · 33 across the 14 of their papers we have counts for
16 papers
LiPS: Lightweight Panoptic Segmentation for Resource-Constrained Robotics
Calvin Galagain, Martyna Poreba, François Goulette +1
Panoptic segmentation is a key enabler for robotic perception, as it unifies semantic understanding with object-level reasoning. However, the increasing complexity of state-of-the-…
Multimodal embodiment-aware navigation transformer
Louis Dezons, Quentin Picard, Rémi Marsal +2
Goal-conditioned navigation models for ground robots trained using supervised learning show promising zero-shot transfer, but their collision-avoidance capability nevertheless degr…
Leg Exoskeleton Odometry using a Limited FOV Depth Sensor
Fabio Elnecave Xavier, Matis Viozelange, Guillaume Burger +3
For leg exoskeletons to operate effectively in real-world environments, they must be able to perceive and understand the terrain around them. However, unlike other legged robots, e…
3DLabelProp: Geometric-Driven Domain Generalization for LiDAR Semantic Segmentation in Autonomous Driving
Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
Domain generalization aims to find ways for deep learning models to maintain their performance despite significant domain shifts between training and inference datasets. This is pa…
HD-OOD3D: Supervised and Unsupervised Out-of-Distribution object detection in LiDAR data
Louis Soum-Fontez, Jean-Emmanuel Deschaud, François Goulette
Autonomous systems rely on accurate 3D object detection from LiDAR data, yet most detectors are limited to a predefined set of known classes, making them vulnerable to unexpected o…
COLA: COarse-LAbel multi-source LiDAR semantic segmentation for autonomous driving
Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
LiDAR semantic segmentation for autonomous driving has been a growing field of interest in recent years. Datasets and methods have appeared and expanded very quickly, but methods h…
MDT3D: Multi-Dataset Training for LiDAR 3D Object Detection Generalization
Louis Soum-Fontez, Jean-Emmanuel Deschaud, François Goulette
Supervised 3D Object Detection models have been displaying increasingly better performance in single-domain cases where the training data comes from the same environment and sensor…
Multi-IMU Proprioceptive State Estimator for Humanoid Robots
Fabio Elnecave Xavier, Guillaume Burger, Marine Pétriaux +2
Algorithms for state estimation of humanoid robots usually assume that the feet remain flat and in a constant position while in contact with the ground. However, this hypothesis is…
Unsigned Distance Field as an Accurate 3D Scene Representation for Neural Scene Completion
Jean Pierre Richa, Jean-Emmanuel Deschaud, François Goulette +1
Scene Completion is the task of completing missing geometry from a partial scan of a scene. Most previous methods compute an implicit representation from range data using a Truncat…
AdaSplats: Adaptive Splatting of Point Clouds for Accurate 3D Modeling and Real-time High-Fidelity LiDAR Simulation
Jean Pierre Richa, Jean-Emmanuel Deschaud, François Goulette +1
LiDAR sensors provide rich 3D information about their surrounding{s} and are becoming increasingly important for autonomous vehicles tasks such as {localization}, semantic segmenta…
COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasets
Jules Sanchez, Jean-Emmanuel Deschaud, François Goulette
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 c…
Riedones3D: a celtic coin dataset for registration and fine-grained clustering
Sofiane Horache, Jean-Emmanuel Deschaud, François Goulette +3
Clustering coins with respect to their die is an important component of numismatic research and crucial for understanding the economic history of tribes (especially when literary p…
CT-ICP: Real-time Elastic LiDAR Odometry with Loop Closure
Pierre Dellenbach, Jean-Emmanuel Deschaud, Bastien Jacquet +1
Multi-beam LiDAR sensors are increasingly used in robotics, particularly with autonomous cars for localization and perception tasks, both relying on the ability to build a precise…
3D Point Cloud Registration with Multi-Scale Architecture and Unsupervised Transfer Learning
Sofiane Horache, Jean-Emmanuel Deschaud, François Goulette
We propose a method for generalizing deep learning for 3D point cloud registration on new, totally different datasets. It is based on two components, MS-SVConv and UDGE. Using Mult…
What's in My LiDAR Odometry Toolbox?
Pierre Dellenbach, Jean-Emmanuel Deschaud, Bastien Jacquet +1
With the democratization of 3D LiDAR sensors, precise LiDAR odometries and SLAM are in high demand. New methods regularly appear, proposing solutions ranging from small variations…
Automatic clustering of Celtic coins based on 3D point cloud pattern analysis
Sofiane Horache, Jean-Emmanuel Deschaud, François Goulette +2
The recognition and clustering of coins which have been struck by the same die is of interest for archeological studies. Nowadays, this work can only be performed by experts and is…