2017
Self-Supervised Visual Descriptor Learning for Dense Correspondence
RA-L 2017
Robust estimation of correspondences between image pixels is an important problem in robotics, with applications in tracking, mapping, and recognition of objects, environments, and other agents. Correspondence estimation has long been the domain of hand-engineered features, but more recently deep le