Leveraging Intermediate Features of Vision Transformer for F…

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2025
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  • DOI 10.1109/cvprw67362.2025.00331
  • OpenAlex ID W4414198797
  • Type Conference-paper
  • Language EN
  • Published 11 Jun 2025
  • Pages 3464–3472
  • Source IEEE/CVF Conference on Computer Vision a…
  • FWCI 3.77
  • Countries 1
  • Institutions 2
  • Added 10 Oct 2025
  • Updated 16 Oct 2026
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Leveraging Intermediate Features of Vision Transformer for Face Anti-Spoofing

Conference-paper 2025 EN Green

Face recognition systems are designed to be robust against changes in head pose, illumination, and blurring during image capture. If a malicious person presents a face photo of the registered user, they may bypass the authentication process illegally. Such spoofing attacks need to be detected before face recognition. In this paper, we propose a spoofing attack detection method based on Vision Tran…

4

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16

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5

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3.77

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5 authors
#AuthorInstitutionsORCID
1 Mika Feng Tohoku University (JP) —
2 Koichi Ito Tohoku University (JP)
3 Takafumi Aoki Tohoku University (JP)
4 Tetsushi Ohki Shizuoka University (JP)
5 Masakatsu Nishigaki Shizuoka University (JP)

Data: OpenAlex