AI RESEARCH
Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation
arXiv CS.CV
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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