Pointnet
Found 5 free book(s)
PCT: Point Cloud Transformer - arXiv
arxiv.orgPointNet [21] pioneered point cloud learning. Subse-quently, Qi et al. proposed PointNet++ [22], which uses query ball grouping and hierarchical PointNet to capture lo-cal structures. Several subsequent works considered how to define convolution operations on point clouds. One main approach is to convert a point cloud into a regular voxel
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object ...
openaccess.thecvf.comconvolution or PointNet-based networks as the backbone. Generally, the 3D voxel sparse CNNs are more efficient [37, 28] and are able to generate high-quality 3D proposals, while the PointNet-based methods can capture more accu-rate contextual information with flexible receptive fields. Our PV-RCNN deeply integrates the advantages of two
PointNet Deep Hierarchical Feature Learning on Point Sets ...
proceedings.neurips.ccPointNet [20] is a pioneering effort that directly processes point sets. The basic idea of PointNet is to learn a spatial encoding of each point and then aggregate all individual point features to a global point cloud signature. By its design, PointNet does
PointNet++: Deep Hierarchical Feature Learning on Point ...
arxiv.orgPointNet [20] is a pioneer in this direction. However, by design PointNet does not capture local structures induced by the metric space points live in, limiting its ability to recognize fine-grained patterns and generalizability to complex scenes. In this work, we introduce a hierarchical
PointNet: Deep Learning on Point Sets for 3D ...
openaccess.thecvf.comPointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Charles R. Qi* Hao Su* Kaichun Mo Leonidas J. Guibas Stanford University Abstract Point cloud is an important type of geometric data structure. Due to its irregular format, most researchers