SynID: Passport Synthetic Dataset for Presentation Attack Detection
By: Juan E. Tapia , Fabian Stockhardt , Lázaro Janier González-Soler and more
Potential Business Impact:
Finds fake ID cards using fake and real pictures.
The demand for Presentation Attack Detection (PAD) to identify fraudulent ID documents in remote verification systems has significantly risen in recent years. This increase is driven by several factors, including the rise of remote work, online purchasing, migration, and advancements in synthetic images. Additionally, we have noticed a surge in the number of attacks aimed at the enrolment process. Training a PAD to detect fake ID documents is very challenging because of the limited number of ID documents available due to privacy concerns. This work proposes a new passport dataset generated from a hybrid method that combines synthetic data and open-access information using the ICAO requirement to obtain realistic training and testing images.
Similar Papers
ID-Card Synthetic Generation: Toward a Simulated Bona fide Dataset
CV and Pattern Recognition
Makes fake IDs harder to spot.
Identity Card Presentation Attack Detection: A Systematic Review
Cryptography and Security
Stops fake IDs from fooling online systems.
Privacy-Aware Detection of Fake Identity Documents: Methodology, Benchmark, and Improved Algorithms (FakeIDet2)
Cryptography and Security
Detects fake IDs even when they look real.