SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning
SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning
A wide range of computer vision algorithms rely on identifying sparse interest points in images and establishing correspondences between them. However, only a subset of the initially identified interest points results in true correspondences (inliers). In this paper, we seek a detector that finds the minimum number of points that …