RGM: A Robust Generalizable Matching Model

arXiv:2310.11755v4 Announce Type: replace
Abstract: Finding corresponding pixels within a pair of images is a fundamental computer vision task with various applications. Due to the specific requirements of different tasks like optical flow estimation and local feature matching, previous works are primarily categorized into dense matching and sparse feature matching focusing on specialized architectures along with task-specific datasets, which may somewhat hinder the generalization performance of specialized models. In this paper, we propose a deep model for sparse and dense …

abstract applications architectures arxiv computer computer vision cs.cv feature flow images optical optical flow pixels requirements robust tasks type vision