Relation-Shape Convolutional Neural Network for Point Cloud Analysis

@article{Liu2019RelationShapeCN,
  title={Relation-Shape Convolutional Neural Network for Point Cloud Analysis},
  author={Yongcheng Liu and Bin Fan and Shiming Xiang and Chunhong Pan},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={8887-8896}
}
Point cloud analysis is very challenging, as the shape implied in irregular points is difficult to capture. In this paper, we propose RS-CNN, namely, Relation-Shape Convolutional Neural Network, which extends regular grid CNN to irregular configuration for point cloud analysis. The key to RS-CNN is learning from relation, i.e., the geometric topology constraint among points. Specifically, the convolutional weight for local point set is forced to learn a high-level relation expression from… Expand
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