SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data
This competition addresses privacy issues in biometric security for researchers and industry, but it is incremental as it builds on existing face presentation attack detection methods.
The paper summarizes the SynFacePAD 2023 competition, which tackled the problem of face presentation attack detection using only synthetic training data to address privacy concerns, resulting in 8 participating teams outperforming a baseline in benchmarks.
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.