107 citations · 288 across the 43 of their papers we have counts for
7 papers · 2 filters
LOGen: Toward Lidar Object Generation by Point Diffusion
Ellington Kirby, Mickael Chen, Renaud Marlet +1
The generation of LiDAR scans is a growing topic with diverse applications to autonomous driving. However, scan generation remains challenging, especially when compared to the rapi…
UNIT: Unsupervised Online Instance Segmentation through Time
Corentin Sautier, Gilles Puy, Alexandre Boulch +2
Online object segmentation and tracking in Lidar point clouds enables autonomous agents to understand their surroundings and make safe decisions. Unfortunately, manual annotations…
Train Till You Drop: Towards Stable and Robust Source-free Unsupervised 3D Domain Adaptation
Björn Michele, Alexandre Boulch, Tuan-Hung Vu +3
We tackle the challenging problem of source-free unsupervised domain adaptation (SFUDA) for 3D semantic segmentation. It amounts to performing domain adaptation on an unlabeled tar…
MILAN: Milli-Annotations for Lidar Semantic Segmentation
Nermin Samet, Gilles Puy, Oriane Siméoni +1
Annotating lidar point clouds for autonomous driving is a notoriously expensive and time-consuming task. In this work, we show that the quality of recent self-supervised lidar scan…
Test-time Contrastive Concepts for Open-world Semantic Segmentation with Vision-Language Models
Monika Wysoczańska, Antonin Vobecky, Amaia Cardiel +4
Recent CLIP-like Vision-Language Models (VLMs), pre-trained on large amounts of image-text pairs to align both modalities with a simple contrastive objective, have paved the way to…
Valeo4Cast: A Modular Approach to End-to-End Forecasting
Yihong Xu, Éloi Zablocki, Alexandre Boulch +11
Motion forecasting is crucial in autonomous driving systems to anticipate the future trajectories of surrounding agents such as pedestrians, vehicles, and traffic signals. In end-t…