title: FlashFace: Human Image Personalization with High-fidelity Identity
    Preservation
summary: This work presents FlashFace, a practical tool with which users can easily
  personalize their own photos on the fly by providing one or a few reference
  face images and a text prompt. Our approach is distinguishable from existing
  human photo customization methods by higher-fidelity identity preservation and
  better instruction following, benefiting from two subtle designs. First, we
  encode the face identity into a series of feature maps instead of one image
  token as in prior arts, allowing the model to retain more details of the
  reference faces (e.g., scars, tattoos, and face shape ). Second, we introduce a
  disentangled integration strategy to balance the text and image guidance during
  the text-to-image generation process, alleviating the conflict between the
  reference faces and the text prompts (e.g., personalizing an adult into a
  "child" or an "elder"). Extensive experimental results demonstrate the
  effectiveness of our method on various applications, including human image
  personalization, face swapping under language prompts, making virtual
  characters into real people, etc. Project Page:
  https://jshilong.github.io/flashface-page.
paper_authors._id: 660246a29ff79e8cd51a0b59
paper_authors.name: Shilong Zhang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-03-26T08:44:21.353Z
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paper_authors.fullname: Shilong Zhang
paper_authors.type: user
paper_authors.user: shilongz
paper_authors._id: 660246a29ff79e8cd51a0b5a
paper_authors.name: Lianghua Huang
paper_authors.status: admin_assigned
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paper_authors._id: 640010d9fe6383d50b31b95f
paper_authors.avatarUrl: /avatars/2e21587b123a813f84e43f1b1b2918c0.svg
paper_authors.fullname: Lianghua Huang
paper_authors.type: user
paper_authors.user: huanglianghua
paper_authors._id: 660246a29ff79e8cd51a0b5b
paper_authors.name: Xi Chen
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-03-26T07:54:20.791Z
paper_authors._id: 644a1b6401e18bf93a6f45c1
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paper_authors.fullname: xichen
paper_authors.type: user
paper_authors.user: xichenhku
paper_authors._id: 660246a29ff79e8cd51a0b5c
paper_authors.name: Yifei Zhang
paper_authors._id: 660246a29ff79e8cd51a0b5d
paper_authors.name: Zhi-Fan Wu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-03-26T08:46:49.177Z
paper_authors._id: 64f0337e1dccbf71c3946204
paper_authors.avatarUrl: /avatars/955d0533b4b7219773ef7b9a16c05848.svg
paper_authors.fullname: Wu Zhi-Fan
paper_authors.type: user
paper_authors.user: wuzhifan
paper_authors._id: 660246a29ff79e8cd51a0b5e
paper_authors.name: Yutong Feng
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-03-26T08:47:05.029Z
paper_authors._id: 64a54e468cfaa458bd6844bf
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/64a54e468cfaa458bd6844bf/5Gmf4tAr59GNl-2VaZDbu.png
paper_authors.fullname: Yutong Feng
paper_authors.type: user
paper_authors.user: fengyutong
paper_authors._id: 660246a29ff79e8cd51a0b5f
paper_authors.name: Wei Wang
paper_authors._id: 660246a29ff79e8cd51a0b60
paper_authors.name: Yujun Shen
paper_authors._id: 660246a29ff79e8cd51a0b61
paper_authors.name: Yu Liu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-03-26T08:48:23.626Z
paper_authors._id: 636de85cc4a7a729c164d2b5
paper_authors.avatarUrl: /avatars/3e281e547e1697e1c06805e7e63f3918.svg
paper_authors.fullname: Yu Liu
paper_authors.type: user
paper_authors.user: YuLiu
paper_authors._id: 660246a29ff79e8cd51a0b62
paper_authors.name: Ping Luo
paper_title: FlashFace: Human Image Personalization with High-fidelity Identity
    Preservation
paper_summary: This work presents FlashFace, a practical tool with which users can easily
  personalize their own photos on the fly by providing one or a few reference
  face images and a text prompt. Our approach is distinguishable from existing
  human photo customization methods by higher-fidelity identity preservation and
  better instruction following, benefiting from two subtle designs. First, we
  encode the face identity into a series of feature maps instead of one image
  token as in prior arts, allowing the model to retain more details of the
  reference faces (e.g., scars, tattoos, and face shape ). Second, we introduce a
  disentangled integration strategy to balance the text and image guidance during
  the text-to-image generation process, alleviating the conflict between the
  reference faces and the text prompts (e.g., personalizing an adult into a
  "child" or an "elder"). Extensive experimental results demonstrate the
  effectiveness of our method on various applications, including human image
  personalization, face swapping under language prompts, making virtual
  characters into real people, etc. Project Page:
  https://jshilong.github.io/flashface-page.
paper_ai_summary: FlashFace personalizes photos using face identity encoding into feature maps and disentangled integration of text and image guidance.
paper_ai_keywords: feature maps disentangled integration strategy text-to-image generation face swapping virtual characters real people