72 citations · 285 across the 34 of their papers we have counts for
5 papers · 1 filter
ALSO: Automotive Lidar Self-supervision by Occupancy estimation
Alexandre Boulch, Corentin Sautier, Björn Michele +2
We propose a new self-supervised method for pre-training the backbone of deep perception models operating on point clouds. The core idea is to train the model on a pretext task whi…
CroCo: Cross-Modal Contrastive learning for localization of Earth Observation data
Wei-Hsin Tseng, Hoàng-Ân Lê, Alexandre Boulch +2
It is of interest to localize a ground-based LiDAR point cloud on remote sensing imagery. In this work, we tackle a subtask of this problem, i.e. to map a digital elevation model (…
Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data
Corentin Sautier, Gilles Puy, Spyros Gidaris +3
Segmenting or detecting objects in sparse Lidar point clouds are two important tasks in autonomous driving to allow a vehicle to act safely in its 3D environment. The best performi…
Deep Surface Reconstruction from Point Clouds with Visibility Information
Raphael Sulzer, Loic Landrieu, Alexandre Boulch +2
Most current neural networks for reconstructing surfaces from point clouds ignore sensor poses and only operate on raw point locations. Sensor visibility, however, holds meaningful…
POCO: Point Convolution for Surface Reconstruction
Alexandre Boulch, Renaud Marlet
Implicit neural networks have been successfully used for surface reconstruction from point clouds. However, many of them face scalability issues as they encode the isosurface funct…