9 papers
HARP-NeXt: High-Speed and Accurate Range-Point Fusion Network for 3D LiDAR Semantic Segmentation
Samir Abou Haidar, Alexandre Chariot, Mehdi Darouich +2
LiDAR semantic segmentation is crucial for autonomous vehicles and mobile robots, requiring high accuracy and real-time processing, especially on resource-constrained embedded syst…
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…
RayGaussX: Accelerating Gaussian-Based Ray Marching for Real-Time and High-Quality Novel View Synthesis
Hugo Blanc, Jean-Emmanuel Deschaud, Alexis Paljic
RayGauss has achieved state-of-the-art rendering quality for novel-view synthesis on synthetic and indoor scenes by representing radiance and density fields with irregularly distri…
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…
RayGauss: Volumetric Gaussian-Based Ray Casting for Photorealistic Novel View Synthesis
Hugo Blanc, Jean-Emmanuel Deschaud, Alexis Paljic
Differentiable volumetric rendering-based methods made significant progress in novel view synthesis. On one hand, innovative methods have replaced the Neural Radiance Fields (NeRF)…
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…