Challenge description


With the goal of giving continuity to our effort in this relevant problem, we are proposing the third edition of the Face Anti-Spoofing Workshop and Competition@ICCV 2021. Unlike the previous editions that focused on 2D face print and video-replay attacks and a diversity of subjects in terms of ethnicity and age, the 2021 challenge will focus on 3D high-fidelity mask attacks. Most existing 3D mask PAD benchmarks suffer from several drawbacks: 1) a limited number of mask identities, types of sensors, and a total number of videos; 2) low-fidelity quality of facial masks. Basic deep models and remote photoplethysmography (rPPG) methods achieved acceptable performance on these benchmarks but still far from the needs of practical scenarios. To bridge the gap to real-world applications, we introduce a largescale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask). For more information about the HiFiMask dataset, please refer to [1].

Note: the 3rd Face Anti-spoofing challenge@ICCV2021 is beginning. (link)



[1] Ajian Liu, Chenxu Zhao, Zitong Yu, Jun Wan*, Anyang Su, Xing Liu, Zichang Tan, Sergio Escalera, Junliang Xing, Yanyan Liang, Guodong Guo, Zhen Lei, Stan Z. Li, Du Zhang, Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection", arxiv, 2021. [Link]


Additional details about this challenge can be found here.


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