- Abstract:
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Face recognition performance evaluation has traditionally focused on one-to-one verification, popularized by the Labeled Faces in the Wild dataset [1] for imagery and the YouTubeFaces dataset [2] for videos. In contrast, the newly released IJB-A face recognition dataset [3] unifies evaluation of one-to-many face identification with one-to-one face verification over templates, or sets of imagery and videos for a subject. In this paper, we study the problem of template adaptation, a form of tra...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted manuscript
- Files:
-
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(pdf, 4.3MB)
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- Publisher copy:
- 10.1109/FG.2017.11
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- Publisher:
- Institute of Electrical and Electronics Engineers Publisher's website
- Publication date:
- 2017-06-05
- Acceptance date:
- 2017-01-27
- DOI:
- Pubs id:
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pubs:684087
- URN:
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uri:a5065bb4-5e94-469a-8dd9-18fd6cb166fc
- UUID:
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uuid:a5065bb4-5e94-469a-8dd9-18fd6cb166fc
- Local pid:
- pubs:684087
- Copyright holder:
- Institute of Electrical and Electronics Engineers
- Copyright date:
- 2017
- Notes:
- © 2017 IEEE
Conference item
Template adaptation for face verification and identification
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