Infinite-ID: Identity-preserved Personalization via ID-semantics Decoupling Paradigm

arXiv:2403.11781v1 Announce Type: new
Abstract: Drawing on recent advancements in diffusion models for text-to-image generation, identity-preserved personalization has made significant progress in accurately capturing specific identities with just a single reference image. However, existing methods primarily integrate reference images within the text embedding space, leading to a complex entanglement of image and text information, which poses challenges for preserving both identity fidelity and semantic consistency. To tackle this challenge, we propose Infinite-ID, an ID-semantics decoupling paradigm for identity-preserved personalization. Specifically, …

abstract arxiv cs.cv diffusion diffusion models embedding entanglement however identity image image generation images paradigm personalization progress reference semantics space text text embedding text-to-image type via