Self-Supervised Learning of Rotation-Invariant 3D Point Set Features using Transformer and its Self-Distillation

The proposed algorithm learns accurate and rotation-invariant 3D point set features in a self-supervised manner by using a novel DNN architecture and a self-distillation training framework.