SynFacePAD 2023: Competition on Face Presentation Attack Detection Based
  on Privacy-aware Synthetic Training Data
Meiling Fang Marco Huber Julian Fierrez Raghavendra Ramachandra Naser Damer Alhasan Alkhaddour Maksim Kasantcev Vasiliy Pryadchenko Ziyuan Yang Huijie Huangfu Yingyu Chen Yi Zhang Yuchen Pan Junjun Jiang Xianming Liu Xianyun Sun Caiyong Wang Xingyu Liu Zhaohua Chang Guangzhe Zhao Juan Tapia Lazaro Gonzalez-Soler Carlos Aravena Daniel Schulz
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.