LIPE: Learning Personalized Identity Prior for Non-rigid Image Editing

arXiv:2406.17236v1 Announce Type: new
Abstract: Although recent years have witnessed significant advancements in image editing thanks to the remarkable progress of text-to-image diffusion models, the problem of non-rigid image editing still presents its complexities and challenges. Existing methods often fail to achieve consistent results due to the absence of unique identity characteristics. Thus, learning a personalized identity prior might help with consistency in the edited results. In this paper, we explore a novel task: learning the personalized identity prior for …

abstract arxiv challenges complexities consistent cs.cv diffusion diffusion models editing fail identity image image diffusion personalized prior problem progress results text text-to-image type unique