Open AccessLU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Net
Author(s) -
Pierre Biasutti,
Vincent Lepetit,
Mathieu Brédif,
Jean-François Aujol,
Aurélie Bugeau
Publication year - 2019
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
Subject(s) - point cloud , end to end principle , net (polyhedron) , computer science , lidar , end point , cloud computing , segmentation , point (geometry) , artificial intelligence , computer vision , computer network , remote sensing , geology , mathematics , operating system , geometry