Correspondence Problem

The fundamental problem in stereo and optical flow: finding matching pixels or features in two or more images that correspond to the same 3D point. Solving correspondence enables depth estimation from stereo cameras and motion estimation from sequential frames. Deep learning approaches (RAFT, StereoNet) have largely replaced hand-crafted matching costs for dense correspondence.