Optimizing DINOv2 with Registers for Face Anti-Spoofing
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- DOI 10.1109/iccvw69036.2025.00345
- OpenAlex ID W7131069200
- Type Conference-paper
- Language EN
- Published 19 Oct 2025
- Pages 3287–3293
- Source IEEE International Conference on Compute…
- Countries 1
- Institutions 1
- Added 24 Feb 2026
- Updated 28 Oct 2026
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Optimizing DINOv2 with Registers for Face Anti-Spoofing
Conference-paper 2025 EN Green
Face recognition systems are designed to be robust against variations in head pose, illumination, and image blur during capture. However, malicious actors can exploit these systems by presenting a face photo of a registered user, potentially bypassing the authentication process. Such spoofing attacks must be detected prior to face recognition. In this paper, we propose a DINOv2-based spoofing atta…
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4 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Mika Feng | Tohoku University (JP) | — |
| 2 | Pierre Gallin-Martel | Tohoku University (JP) | — |
| 3 | Koichi Ito | Tohoku University (JP) | |
| 4 | Takafumi Aoki | Tohoku University (JP) |
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