The existing 3D deep learning methods adopt either individual point-based features or local-neighboring voxel-based features, and demonstrate great potential for processing data. However, the models are inefficient due to unordered nature of point clouds suffer from large information loss. Motivated by success recent point-voxel representation, such as PVCNN DRINet, we propose a new convolution...
