Video alignment using unsupervised learning of local and global features. (arXiv:2304.06841v1 [cs.CV])

In this paper, we tackle the problem of video alignment, the process of
matching the frames of a pair of videos containing similar actions. The main
challenge in video alignment is that accurate correspondence should be
established despite the differences in the execution processes and appearances
between the two videos. We introduce an unsupervised method for alignment that
uses global and local features of the frames. In particular, we introduce
effective features for each video frame by means of three …

alignment arxiv challenge detection features global machine machine vision paper person process processes tools unsupervised unsupervised learning video videos vision