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: | http://urn.fi/urn:nbn:fi-fe2023033033960 |
Language: | English |
Published: |
Springer Nature,
2023
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Publish Date: | 2025-02-24 |
Description: |
AbstractFace 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. 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: | 978-981-19-5288-3 |
ISBN Print: | 978-981-19-5287-6 |
Pages: | 287 - 336 |
DOI: | 10.1007/978-981-19-5288-3_12 |
OADOI: | https://oadoi.org/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 |
Subjects: | |
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 345122 345948 |
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. |