Improving RGB-D Point Cloud Registration by Learning Multi-scale Local Linear Transformation. (arXiv:2208.14893v2 [cs.CV] UPDATED)

Point cloud registration aims at estimating the geometric transformation
between two point cloud scans, in which point-wise correspondence estimation is
the key to its success. In addition to previous methods that seek
correspondences by hand-crafted or learnt geometric features, recent point
cloud registration methods have tried to apply RGB-D data to achieve more
accurate correspondence. However, it is not trivial to effectively fuse the
geometric and visual information from these two distinctive modalities,
especially for the registration problem. In this …

arxiv cloud learning linear registration scale transformation