RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

25 Nov 2019Qingyong HuBo YangLinhai XieStefano RosaYulan GuoZhihua WangNiki TrigoniAndrew Markham

We study the problem of efficient semantic segmentation for large-scale 3D point clouds. By relying on expensive sampling techniques or computationally heavy pre/post-processing steps, most existing approaches are only able to be trained and operate over small-scale point clouds... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Semantic Segmentation Semantic3D RandLA-Net mIoU 76.0% # 1
3D Semantic Segmentation SemanticKITTI RandLA-Net mIoU 50.3 # 2