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Self-supervised learning of a facial attribute embedding from video

Abstract:

We propose a self-supervised framework for learning facial attributes by simply watching videos of a human face speaking, laughing, and moving over time. To perform this task, we introduce a network, Facial Attributes-Net (FAb-Net), that is trained to embed multiple frames from the same video face-track into a common low-dimensional space. With this approach, we make three contributions: first, we show that the network can leverage information from multiple source frames by predicting confide...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0002-8945-8573
Publisher:
British Machine Vision Association Publisher's website
Publication date:
2018-09-06
Acceptance date:
2018-07-02
Pubs id:
pubs:944867
URN:
uri:2e5e0096-7ccb-4127-9125-7a93c4fa04ba
UUID:
uuid:2e5e0096-7ccb-4127-9125-7a93c4fa04ba
Local pid:
pubs:944867

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