title: PuLID: Pure and Lightning ID Customization via Contrastive Alignment
summary: 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 will be available at
  https://github.com/ToTheBeginning/PuLID
paper_authors._id: 662a71ec309bb68eb4c9efe9
paper_authors.name: Zinan Guo
paper_authors._id: 662a71ec309bb68eb4c9efea
paper_authors.name: Yanze Wu
paper_authors.status: extracted_confirmed
paper_authors.statusLastChangedAt: 2024-04-25T15:18:37.744Z
paper_authors._id: 639709c2be8a14bb9eeea8f6
paper_authors.avatarUrl: /avatars/c142d71b541dccff91fcfd08a2cc0ce0.svg
paper_authors.fullname: Yanze Wu
paper_authors.type: user
paper_authors.user: yanze
paper_authors._id: 662a71ec309bb68eb4c9efeb
paper_authors.name: Zhuowei Chen
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-04-25T18:07:40.993Z
paper_authors._id: 6304e2dabad6ce7fc0287d57
paper_authors.avatarUrl: /avatars/3fd4a9a62b0ef98db2573411463a9247.svg
paper_authors.fullname: Zhuowei_Chen
paper_authors.type: user
paper_authors.user: ZhuoweiChen
paper_authors._id: 662a71ec309bb68eb4c9efec
paper_authors.name: Lang Chen
paper_authors._id: 662a71ec309bb68eb4c9efed
paper_authors.name: Qian He
paper_title: PuLID: Pure and Lightning ID Customization via Contrastive Alignment
paper_summary: 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 will be available at
  https://github.com/ToTheBeginning/PuLID
paper_ai_summary: PuLID combines a Lightning T2I branch with a diffusion model to provide ID customization in text-to-image generation, maintaining ID fidelity and consistency in image elements.
paper_ai_keywords: Lightning T2I diffusion model contrastive alignment loss accurate ID loss ID fidelity editability image elements consistency