PCB-RandNet: Rethinking Random Sampling for LiDAR Semantic Segmentation in Autonomous Driving Scene
Xian-Feng Han,Huixian Cheng,Hang Jiang,Dehong He,Guoqiang Xiao,Xian-Feng Han,Huixian Cheng,Hang Jiang,Dehong He,Guoqiang Xiao
Fast and efficient semantic segmentation of large-scale LiDAR point clouds is a fundamental problem in autonomous driving. To achieve this goal, the existing point-based methods mainly choose to adopt Random Sampling strategy to process large-scale point clouds. However, our quantative and qualitative studies have found that Random Sampling may be less suitable for the autonomous driving scenario,...
