AI RESEARCH

Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation

arXiv CS.CV

ArXi:2605.17135v1 Announce Type: new Annotating large-scale LiDAR point clouds for 3D semantic segmentation is costly and time-consuming, which motivates the use of semi-supervised learning (SemiSL). Standard LiDAR SemiSL methods typically adopt a two-step