title: Avatar Fingerprinting for Authorized Use of Synthetic Talking-Head
    Videos
summary: Modern generators render talking-head videos with impressive levels of
  photorealism, ushering in new user experiences such as videoconferencing under
  constrained bandwidth budgets. Their safe adoption, however, requires a
  mechanism to verify if the rendered video is trustworthy. For instance, for
  videoconferencing we must identify cases in which a synthetic video portrait
  uses the appearance of an individual without their consent. We term this task
  avatar fingerprinting. We propose to tackle it by leveraging facial motion
  signatures unique to each person. Specifically, we learn an embedding in which
  the motion signatures of one identity are grouped together, and pushed away
  from those of other identities, regardless of the appearance in the synthetic
  video. Avatar fingerprinting algorithms will be critical as talking head
  generators become more ubiquitous, and yet no large scale datasets exist for
  this new task. Therefore, we contribute a large dataset of people delivering
  scripted and improvised short monologues, accompanied by synthetic videos in
  which we render videos of one person using the facial appearance of another.
  Project page: https://research.nvidia.com/labs/nxp/avatar-fingerprinting/.
paper_authors._id: 6458661fbb7bdc9655af8eb4
paper_authors.name: Ekta Prashnani
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-06-02T13:42:31.339Z
paper_authors._id: 616b8fd8a60751e3e7b9c9cd
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1634439068637-noauth.jpeg
paper_authors.fullname: Ekta Prashnani
paper_authors.type: user
paper_authors.user: prashnani
paper_authors._id: 6458661fbb7bdc9655af8eb5
paper_authors.name: Koki Nagano
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-06-02T13:41:29.979Z
paper_authors._id: 637eb1c71dbae09191059243
paper_authors.avatarUrl: /avatars/674b1a6e419c758a8613338d20f21544.svg
paper_authors.fullname: Koki Nagano
paper_authors.type: user
paper_authors.user: luminohope
paper_authors._id: 6458661fbb7bdc9655af8eb6
paper_authors.name: Shalini De Mello
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-06-02T13:42:12.776Z
paper_authors._id: 623f6ac3f1c25923c98a892a
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1648323201428-noauth.png
paper_authors.fullname: Shalini De Mello
paper_authors.type: user
paper_authors.user: shalinidemello
paper_authors._id: 6458661fbb7bdc9655af8eb7
paper_authors.name: David Luebke
paper_authors._id: 6458661fbb7bdc9655af8eb8
paper_authors.name: Orazio Gallo
paper_title: Avatar Fingerprinting for Authorized Use of Synthetic Talking-Head
    Videos
paper_summary: Modern generators render talking-head videos with impressive levels of
  photorealism, ushering in new user experiences such as videoconferencing under
  constrained bandwidth budgets. Their safe adoption, however, requires a
  mechanism to verify if the rendered video is trustworthy. For instance, for
  videoconferencing we must identify cases in which a synthetic video portrait
  uses the appearance of an individual without their consent. We term this task
  avatar fingerprinting. We propose to tackle it by leveraging facial motion
  signatures unique to each person. Specifically, we learn an embedding in which
  the motion signatures of one identity are grouped together, and pushed away
  from those of other identities, regardless of the appearance in the synthetic
  video. Avatar fingerprinting algorithms will be critical as talking head
  generators become more ubiquitous, and yet no large scale datasets exist for
  this new task. Therefore, we contribute a large dataset of people delivering
  scripted and improvised short monologues, accompanied by synthetic videos in
  which we render videos of one person using the facial appearance of another.
  Project page: https://research.nvidia.com/labs/nxp/avatar-fingerprinting/.
paper_ai_summary: Avatar fingerprinting uses facial motion signatures to verify the authenticity of synthetic talking-head videos, addressing privacy concerns in videoconferencing and other applications.
paper_ai_keywords: avatar fingerprinting facial motion signatures embedding synthetic videos talking-head generators