Avatar Fingerprinting for Authorized Use of Synthetic Talking-Head
  Videos
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/.
6458661fbb7bdc9655af8eb4
Ekta Prashnani
admin_assigned
2023-06-02T13:42:31.339Z
616b8fd8a60751e3e7b9c9cd
https://cdn-avatars.huggingface.co/v1/production/uploads/1634439068637-noauth.jpeg
Ekta Prashnani
user
prashnani
6458661fbb7bdc9655af8eb5
Koki Nagano
admin_assigned
2023-06-02T13:41:29.979Z
637eb1c71dbae09191059243
/avatars/674b1a6e419c758a8613338d20f21544.svg
Koki Nagano
user
luminohope
6458661fbb7bdc9655af8eb6
Shalini De Mello
admin_assigned
2023-06-02T13:42:12.776Z
623f6ac3f1c25923c98a892a
https://cdn-avatars.huggingface.co/v1/production/uploads/1648323201428-noauth.png
Shalini De Mello
user
shalinidemello
6458661fbb7bdc9655af8eb7
David Luebke
6458661fbb7bdc9655af8eb8
Orazio Gallo
Avatar Fingerprinting for Authorized Use of Synthetic Talking-Head
  Videos
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/.
Avatar fingerprinting uses facial motion signatures to verify the authenticity of synthetic talking-head videos, addressing privacy concerns in videoconferencing and other applications.
avatar fingerprinting facial motion signatures embedding synthetic videos talking-head generators