This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition attracted a total of 8 participating teams with valid submissions from academia and industry. The competition aimed to motivate and attract solutions that target detecting face presentation attacks while considering synthetic-based training data motivated by privacy, legal and ethical concerns associated with personal data. To achieve that, the training data used by the participants was limited to synthetic data provided by the organizers. The submitted solutions presented innovations and novel approaches that led to outperforming the considered baseline in the investigated benchmarks.
@article{arxiv.2311.05336,
title = {SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data},
author = {Meiling Fang and Marco Huber and Julian Fierrez and Raghavendra Ramachandra and Naser Damer and Alhasan Alkhaddour and Maksim Kasantcev and Vasiliy Pryadchenko and Ziyuan Yang and Huijie Huangfu and Yingyu Chen and Yi Zhang and Yuchen Pan and Junjun Jiang and Xianming Liu and Xianyun Sun and Caiyong Wang and Xingyu Liu and Zhaohua Chang and Guangzhe Zhao and Juan Tapia and Lazaro Gonzalez-Soler and Carlos Aravena and Daniel Schulz},
journal= {arXiv preprint arXiv:2311.05336},
year = {2023}
}