PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
This paper builds off of ideas from PointNet (Qi et al., 2017).
PointNet and PointNet++ are deep neural network architecture that take point clouds as their input and perform the tasks such as classification or part segmentation or scene segmentation.
PointNet differs from other point cloud processing networks by directly taking the unordered points from the point cloud as input, instead of re-representing the point cloud by voxelization or 2D images.
Review of PointNet
Robust Feature Learning under Non-Uniform Sampling Density
1. Charles R. Qi, Li Yi, Hao Su, Leonidas J. Guibas. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space, 2017
2. Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation, 2017