Lepard: Learning partial point cloud matching in rigid and deformable scenes

Understand

We present Lepard, a Learning based approach for partial point cloud matching in rigid and deformable scenes.

• The key characteristics are the following techniques that exploit 3D positional knowledge for point cloud matching: 1) An architecture that disentangles point cloud representation into feature space and 3D position space.
• 2) A position encoding method that explicitly reveals 3D relative distance information through the dot product of vectors.
• 3) A repositioning technique that modifies the crosspoint-cloud relative positions.