RePL refines pseudo-labels for semi-supervised LiDAR semantic segmentation via masked reconstruction, achieving state-of-the-art results on nuScenes-lidarseg and SemanticKITTI.
Implication.In a semi-supervised setting, however,Tconveys semantic cues such as tentative class assignments or boundary structures that are not directly available fromX
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RePL: Pseudo-label Refinement for Semi-supervised LiDAR Semantic Segmentation
RePL refines pseudo-labels for semi-supervised LiDAR semantic segmentation via masked reconstruction, achieving state-of-the-art results on nuScenes-lidarseg and SemanticKITTI.