University of Oulu

Yu, Z., Komulainen, J., Li, X., Zhao, G. (2023). Review of Face Presentation Attack Detection Competitions. In: Marcel, S., Fierrez, J., Evans, N. (eds) Handbook of Biometric Anti-Spoofing. Advances in Computer Vision and Pattern Recognition. Springer, Singapore.

Review of face presentation attack detection competitions

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Author: Yu, Zitong1; Komulainen, Jukka1,2; Li, Xiaobai1;
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
2Visidon Ltd, Oulu, Finland
Format: article
Version: accepted version
Access: embargoed
Persistent link:
Language: English
Published: Springer Nature, 2023
Publish Date: 2025-02-24


Face presentation attack detection (PAD) has received increasing attention ever since the vulnerabilities to spoofing have been widely recognized. The state of the art in unimodal and multi-modal face anti-spoofing has been assessed in eight international competitions organized in conjunction with major biometrics and computer vision conferences in 2011, 2013, 2017, 2019, 2020 and 2021, each introducing new challenges to the research community. In this chapter, we present the design and results of the five latest competitions from 2019 until 2021. The first two challenges aimed at evaluating the effectiveness of face PAD in multi-modal setup introducing near-infrared (NIR) and depth modalities in addition to colour camera data, while the latest three competitions focused on evaluating domain and attack type generalization abilities of face PAD algorithms operating on conventional colour images and videos. We also discuss the lessons learnt from the competitions and future challenges in the field in general.

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Series: Advances in computer vision and pattern recognition
ISSN: 2191-6586
ISSN-E: 2191-6594
ISSN-L: 2191-6586
ISBN: 978-981-19-5288-3
ISBN Print: 978-981-19-5287-6
Pages: 287 - 336
DOI: 10.1007/978-981-19-5288-3_12
Host publication: Review of Face Presentation Attack Detection Competitions
Host publication editor: Marcel, Sébastien
Fierrez, Julian
Evans, Nicholas
Type of Publication: A3 Book chapter
Field of Science: 113 Computer and information sciences
Funding: This work was supported by Infotech Oulu and the Academy of Finland for Academy Professor project EmotionAI (grants 336116, 345122) and ICT 2023 project (grant 345948).
Academy of Finland Grant Number: 336116
Detailed Information: 336116 (Academy of Finland Funding decision)
345122 (Academy of Finland Funding decision)
345948 (Academy of Finland Funding decision)
Copyright information: © 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.