The survey provides a comprehensive overview of deep learning methods for geometric data (point clouds, voxels, network graphs etc.). The relevant knowledge and theoretical background of geometric deep learning is presented first. In the following section, different network models for graph and manifold data are reviewed. Finally, applications of these methods in various fields and public datasets are described.
