PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Gra…

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2022
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Work Details
  • DOI 10.1109/cvpr52688.2022.01964
  • OpenAlex ID W4312836647
  • Type Conference-paper
  • Language EN
  • Published 01 Jun 2022
  • Pages 20249–20258
  • Source IEEE Computer Society Conference on Comp…
  • Publisher Institute of Electrical and Electro…
  • FWCI 24.71
  • Countries 2
  • Institutions 2
  • Added 05 Jan 2023
  • Updated 16 Oct 2026
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PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition

Conference-paper 2022 EN Green

Face anti-spoofing (FAS) plays a critical role in securing face recognition systems from different presentation attacks. Previous works leverage auxiliary pixel-level supervision and domain generalization approaches to address unseen spoof types. However, the local characteristics of image captures, i.e., capturing devices and presenting materials, are ignored in existing works and we argue that s…

167

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34

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4

Authors

24.71

FWCI

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4 authors
#AuthorInstitutionsORCID
1 Chien-Yi Wang Microsoft (United States) (US)
2 Yu-Ding Lu HTC (Taiwan) (TW) —
3 Shang-Ta Yang Microsoft (United States) (US) —
4 Shang‐Hong Lai Microsoft (United States) (US)

Data: OpenAlex