11 citations · 17 across the 5 of their papers we have counts for
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cs.CV2023
Cross-modal & Cross-domain Learning for Unsupervised LiDAR Semantic Segmentation
Yiyang Chen, Shanshan Zhao, Changxing Ding +3
In recent years, cross-modal domain adaptation has been studied on the paired 2D image and 3D LiDAR data to ease the labeling costs for 3D LiDAR semantic segmentation (3DLSS) in th…
cs.CV2023★ 6 cited
All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation
Liyao Tang, Zhe Chen, Shanshan Zhao +2
Pseudo-labels are widely employed in weakly supervised 3D segmentation tasks where only sparse ground-truth labels are available for learning. Existing methods often rely on empiri…