First Competition on Presentation Attack Detection on ID Card

This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB 2024). The competition attracted a total of ten registered teams, both from academia and industry. In the end, the participating teams submitted five valid submissions, with eight models to be evaluated by the organisers. The competition presented an independent assessment of current state-of-the-art algorithms. Today, no independent evaluation on cross-dataset is available; therefore, this work determined the state-of-the-art on ID cards. To reach this goal, a sequestered test set and baseline algorithms were used to evaluate and compare all the proposals. The sequestered test dataset contains ID cards from four different countries. In summary, a team that chose to be "Anonymous" reached the best average ranking results of 74.80%, followed very closely by the "IDVC" team with 77.65%.

1. Introduction

The accelerated evolution in consumer smartphone cameras and the COVID-19 pandemic has increased the interest in remote biometric verification systems. The capacity to reach the customer remotely for services such as e-commerce, digital banking, and general fintech requires robust systems for remote identity verification. One approach for this verification is using a picture of an official identity document, such as a national ID card, and comparing the data with a frontal face photograph (selfie) of the person in question, both captured remotely by the user "in the wild" condition.