Edit-Your-Motion: Space-Time Diffusion Decoupling Learning for Video Motion Editing

arXiv:2405.04496v1 Announce Type: new
Abstract: Existing diffusion-based video editing methods have achieved impressive results in motion editing. Most of the existing methods focus on the motion alignment between the edited video and the reference video. However, these methods do not constrain the background and object content of the video to remain unchanged, which makes it possible for users to generate unexpected videos. In this paper, we propose a one-shot video motion editing method called Edit-Your-Motion that requires only a single …

abstract alignment arxiv cs.cv diffusion edit editing focus however object reference results space type video