title: RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance
summary: Customizing diffusion models to generate identity-preserving images from
  user-provided reference images is an intriguing new problem. The prevalent
  approaches typically require training on extensive domain-specific images to
  achieve identity preservation, which lacks flexibility across different use
  cases. To address this issue, we exploit classifier guidance, a training-free
  technique that steers diffusion models using an existing classifier, for
  personalized image generation. Our study shows that based on a recent rectified
  flow framework, the major limitation of vanilla classifier guidance in
  requiring a special classifier can be resolved with a simple fixed-point
  solution, allowing flexible personalization with off-the-shelf image
  discriminators. Moreover, its solving procedure proves to be stable when
  anchored to a reference flow trajectory, with a convergence guarantee. The
  derived method is implemented on rectified flow with different off-the-shelf
  image discriminators, delivering advantageous personalization results for human
  faces, live subjects, and certain objects. Code is available at
  https://github.com/feifeiobama/RectifID.
paper_authors._id: 6650143d6f16bbd9a17f2423
paper_authors.name: Zhicheng Sun
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-05-24T10:38:08.415Z
paper_authors._id: 62fc758172a7ab50b4b89c8c
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1677251053045-62fc758172a7ab50b4b89c8c.jpeg
paper_authors.fullname: Zhicheng Sun
paper_authors.type: user
paper_authors.user: feifeiobama
paper_authors._id: 6650143d6f16bbd9a17f2424
paper_authors.name: Zhenhao Yang
paper_authors._id: 6650143d6f16bbd9a17f2425
paper_authors.name: Yang Jin
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-10-10T10:59:56.375Z
paper_authors._id: 64b79ec0a8c39dc078897430
paper_authors.avatarUrl: /avatars/8339f3ab9bb7baaf69bf174eafb7282c.svg
paper_authors.fullname: Yang Jin
paper_authors.type: user
paper_authors.user: rain1011
paper_authors._id: 6650143d6f16bbd9a17f2426
paper_authors.name: Haozhe Chi
paper_authors._id: 6650143d6f16bbd9a17f2427
paper_authors.name: Kun Xu
paper_authors._id: 6650143d6f16bbd9a17f2428
paper_authors.name: Kun Xu
paper_authors._id: 6650143d6f16bbd9a17f2429
paper_authors.name: Liwei Chen
paper_authors._id: 6650143d6f16bbd9a17f242a
paper_authors.name: Hao Jiang
paper_authors._id: 6650143d6f16bbd9a17f242b
paper_authors.name: Di Zhang
paper_authors._id: 6650143d6f16bbd9a17f242c
paper_authors.name: Yang Song
paper_authors._id: 6650143d6f16bbd9a17f242d
paper_authors.name: Kun Gai
paper_authors._id: 6650143d6f16bbd9a17f242e
paper_authors.name: Yadong Mu
paper_title: RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance
paper_summary: Customizing diffusion models to generate identity-preserving images from
  user-provided reference images is an intriguing new problem. The prevalent
  approaches typically require training on extensive domain-specific images to
  achieve identity preservation, which lacks flexibility across different use
  cases. To address this issue, we exploit classifier guidance, a training-free
  technique that steers diffusion models using an existing classifier, for
  personalized image generation. Our study shows that based on a recent rectified
  flow framework, the major limitation of vanilla classifier guidance in
  requiring a special classifier can be resolved with a simple fixed-point
  solution, allowing flexible personalization with off-the-shelf image
  discriminators. Moreover, its solving procedure proves to be stable when
  anchored to a reference flow trajectory, with a convergence guarantee. The
  derived method is implemented on rectified flow with different off-the-shelf
  image discriminators, delivering advantageous personalization results for human
  faces, live subjects, and certain objects. Code is available at
  https://github.com/feifeiobama/RectifID.
paper_ai_keywords: diffusion models classifier guidance rectified flow frameworks fixed-point solution off-the-shelf image discriminators reference flow trajectory