University of Oulu

Liu SQ., Yuen P.C., Li X., Zhao G. (2019) Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks. In: Marcel S., Nixon M., Fierrez J., Evans N. (eds) Handbook of Biometric Anti-Spoofing. Advances in Computer Vision and Pattern Recognition. Springer, Cham.

Recent progress on face presentation attack detection of 3D mask attacks

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Author: Liu, Si-Qi1; Yuen, Pong C.1; Li, Xiaobai2;
Organizations: 1Department of Computer Science, Hong Kong Baptist University, Kowloon, Hong Kong
2Center for Machine Vision and Signal Analysis, University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 21.2 MB)
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Language: English
Published: Springer Nature, 2019
Publish Date: 2021-01-02


With the advanced 3D reconstruction and printing technologies, creating a super-real 3D facial mask becomes feasible at an affordable cost. This brings a new challenge to face presentation attack detection (PAD) against 3D facial mask attack. As such, there is an urgent need to solve this problem as many face recognition systems have been deployed in real-world applications. Since this is a relatively new research problem, few studies has been conducted and reported. In order to attract more attentions on 3D mask face PAD, this book chapter summarizes the progress in the past few years, as well as publicly available datasets. Finally, some open problems in 3D mask attack are discussed.

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Series: Advances in computer vision and pattern recognition
ISSN: 2191-6586
ISSN-E: 2191-6594
ISSN-L: 2191-6586
ISBN: 978-3-319-92627-8
ISBN Print: 978-3-319-92626-1
Pages: 229 - 246
DOI: 10.1007/978-3-319-92627-8_11
Host publication: Handbook of Biometric Anti-Spoofing : Presentation Attack Detection
Host publication editor: Marcel, Sébastien
Nixon, Mark S.
Fierrez, Julian
Evans, Nicholas
Type of Publication: A3 Book chapter
Field of Science: 113 Computer and information sciences
Funding: This project is partially supported by Hong Kong RGC General Research Fund HKBU 12201215, Academy of Finland and FiDiPro program of Tekes (project number: 1849/31/2015).
Copyright information: © Springer Nature Switzerland AG 2019. This is a post-peer-review, pre-copyedit version of an article published in Handbook of Biometric Anti-Spoofing. Advances in Computer Vision and Pattern Recognition. The final authenticated version is available online at: