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Cited by 227Biometric Identification and SecurityFace recognition and analysisDigital Media Forensic Detection

Deep learning for face anti-spoofing: A survey

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Yu, Zitong, Qin, Yunxiao, Li, Xiaobai, Zhao, Chenxu, Lei, Zhen, Zhao, Guoying·2022·IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI 10.1109/tpami.2022.3215850
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Abstract

Face anti-spoofing (FAS) has lately attracted increasing attention due to its vital role in securing face recognition systems from presentation attacks (PAs). As more and more realistic PAs with novel types spring up, early-stage FAS methods based on handcrafted features become unreliable due to their limited representation capacity. With the emergence of large-scale academic datasets in the recent decade, deep learning based FAS achieves remarkable performance and dominates this area. However, existing reviews in this field mainly focus on the handcrafted features, which are outdated and uninspiring for the progress of FAS community. In this paper, to stimulate future research, we present the first comprehensive review of recent advances in deep learning based FAS. It covers several novel and insightful components: 1) besides supervision with binary label (e.g., '0' for bonafide versus '1' for PAs), we also investigate recent methods with pixel-wise supervision (e.g., pseudo depth map); 2) in addition to traditional intra-dataset evaluation, we collect and analyze the latest methods specially designed for domain generalization and open-set FAS; and 3) besides commercial RGB camera, we summarize the deep learning applications under multi-modal (e.g., depth and infrared) or specialized (e.g., light field and flash) sensors. We conclude this survey by emphasizing current open issues and highlighting potential prospects.

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Cited by

Sorted by citations

Authors
Yu, Z., Qin, Y., Li, X., Zhao, C., Lei, Z., & Zhao, G.
Affiliations
  • University of Oulu (FI)
  • State Key Laboratory of Media Convergence and Communication (CN)
  • SailYond Technology, Beijing, China
  • Chinese Academy of Sciences (CN)
ORCID
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2022
Volume
45
Issue
5
Pages
1-22
ISSN
  • 0162-8828 (ISSN-L)
  • 2160-9292
  • 1939-3539
DOI
10.1109/tpami.2022.3215850
OpenAlex
W4306832857
Cited by
227
References
7
Citations by year
2026: 34 · 2025: 61 · 2024: 57 · 2023: 50 · 2022: 19 · 2021: 6
FWCI
21.57
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
Keywords
face anti-spoofing, presentation attacks, face recognition security, deep learning, domain generalization, multimodal biometrics, depth sensing, infrared detection

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