CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration

Understand

We study the problem of extracting correspondences between a pair of point clouds for registration.

• For correspondence retrieval, existing works benefit from matching sparse keypoints detected from dense points but usually struggle to guarantee their repeatability.
• To address this issue, we present CoFiNet - Coarse-to-Fine Network which extracts hierarchical correspondences from coarse to fine without keypoint detection.
• On a coarse scale and guided by a weighting scheme, our model firstly learns to match down-sampled nodes whose vicinity points share more overlap, which significantly shrinks the search space of a consecutive stage.