DANet: Dynamic Attention to Spoof Patterns for Face Anti-Spo…

Emerging


9
Citations
48
Refs
2022
Year
Search Works
Work Details
  • DOI 10.1109/icpr56361.2022.9956725
  • OpenAlex ID W4312792082
  • Type Conference-paper
  • Language EN
  • Published 21 Aug 2022
  • Pages 1929–1936
  • Source Proceedings - International Conference o…
  • FWCI 1.24
  • Countries 1
  • Institutions 1
  • Added 05 Jan 2023
  • Updated 16 Oct 2026
MENU
0

DANet: Dynamic Attention to Spoof Patterns for Face Anti-Spoofing

Conference-paper 2022 EN

Face anti-spoofing is a vital part to protect the security of face recognition systems. Many existing face anti-spoofing methods rely on convolutional neural networks (CNNs) and achieve competitive performance. However, due to the power of CNNs, these methods will extract information that is irrelevant to spoof patterns, such as acquisition equipment and environmental characteristics, which makes…

9

Citations

48

References

5

Authors

1.24

FWCI

Citations by Year
Last 4 years
Topics
Keywords
Authors & Affiliations
5 authors
#AuthorInstitutionsORCID
1 Chunyu Sun University of Science and Tech… (CN) —
2 Song-Lu Chen University of Science and Tech… (CN)
3 Xinjie Li University of Science and Tech… (CN)
4 Feng Chen University of Science and Tech… (CN)
5 Xu-Cheng Yin University of Science and Tech… (CN)

Data: OpenAlex