PuLID: Pure and Lightning ID Customization via Contrastive Alignment
원문 초록
We propose Pure and Lightning ID customization (PuLID), a novel tuning-free ID customization method for text-to-image generation. By incorporating a Lightning T2I branch with a standard diffusion one, PuLID introduces both contrastive alignment loss and accurate ID loss, minimizing disruption to the original model and ensuring high ID fidelity. Experiments show that PuLID achieves superior performance in both ID fidelity and editability. Another attractive property of PuLID is that the image elements (e.g., background, lighting, composition, and style) before and after the ID insertion are kept as consistent as possible. Codes and models are available at https://github.com/ToTheBeginning/PuLID
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
CharaConsist: Fine-Grained Consistent Character Generation
NeoBabel: A Multilingual Open Tower for Visual Generation
Ovis-U1 Technical Report
Rethink Sparse Signals for Pose-guided Text-to-image Generation
XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation
ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.