Self-supervised rigid transformation equivariance for accurate 3D point cloud registration

•We build a dedicated RTE and design a Siamese structurefor 3D point cloud registration.•We propose to learn the matching matrix from the LCV more effectively instead of the hand crafted matching strategy.•Remarkable performance on several datasets topping the state of the art methods proves the effectiveness of our method.