University of Oulu

A. Liu et al., "3D High-Fidelity Mask Face Presentation Attack Detection Challenge," 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021, pp. 814-823, doi: 10.1109/ICCVW54120.2021.00096

3D high-fidelity mask face presentation attack detection challenge

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Author: Liu, Ajian1; Zhao, Chenxu2; Yu, Zitong3;
Organizations: 1MUST, Macau
2Mininglamp Academy of Sciences, Mininglamp Technology, China
3University of Oulu, Finland
5SAI, UCAS, China
6ChaLearn, USA
7CVC, UB, Spain
10Baidu Research, China
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.2 MB)
Persistent link:
Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2022-02-17


The threat of 3D masks to face recognition systems is increasingly serious and has been widely concerned by researchers. To facilitate the study of the algorithms, a largescale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask) has been collected. Specifically, it consists of a total amount of 54,600 videos which are recorded from 75 subjects with 225 realistic masks under 7 new kinds of sensors [21]. Based on this dataset and Protocol 3 which evaluates both the discrimination and generalization ability of the algorithm under the open set scenarios, we organized a 3D High-Fidelity Mask Face Presentation Attack Detection Challenge to boost the research of 3D mask-based attack detection. It attracted 195 teams for the development phase with a total of 18 teams qualifying for the final round. All the results were verified and re-run by the organizing team, and the results were used for the final ranking. This paper presents an overview of the challenge, including the introduction of the dataset used, the definition of the protocol, the calculation of the evaluation criteria, and the summary and publication of the competition results. Finally, we focus on introducing and analyzing the top ranking algorithms, the conclusion summary, and the research ideas for mask attack detection provided by this competition.

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Series: IEEE International Conference on Computer Vision workshops
ISSN: 2473-9944
ISSN-E: 2473-9936
ISSN-L: 2473-9944
ISBN: 978-1-6654-0191-3
ISBN Print: 978-1-6654-0192-0
Pages: 814 - 823
DOI: 10.1109/ICCVW54120.2021.00096
Host publication: 18th IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021, 11-17 Oct 2021, Montreal, BC, Canada
Conference: International Conference on Computer Vision Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This work was supported by the Chinese National Natural Science Foundation Projects #61961160704, #61876179, the External cooperation key project of Chinese Academy Sciences # 173211KYSB20200002, the Key Project of the General Logistics Department Grant No.AWS17J001, Science and Technology Development Fund of Macau (No. 0010/2019/AFJ, 0008/2019/A1, 0025/2019/AKP, 0019/2018/ASC), by the Spanish project PID2019-105093GB-I00 (MINECO/FEDER, UE), and by ICREA under the ICREA Academia programme.
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