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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: | embargoed |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe2019080723637 |
| Language: | English |
| Published: |
Springer Nature,
2019
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| Publish Date: | 2021-01-02 |
| Description: |
AbstractWith 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. see all
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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 |
| OADOI: | https://oadoi.org/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 |
| Subjects: | |
| 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: https://doi.org/10.1007/978-3-319-92627-8_11.
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