首次独立评估身份证活体攻击检测技术，揭示当前最佳方法表现。
First Competition on Presentation Attack Detection on ID Card
- 采用隔离测试集与基线算法，对参赛模型进行公平对比
- 最佳团队在跨国家数据集上达到77.65%平均准确率
- 为身份证活体检测提供首个跨数据集基准评估
本文总结了2024年国际生物特征会议（IJCB2024）上举办的身份证活体攻击检测竞赛（PAD-IDCard）。比赛共吸引来自学术界和产业界的十支队伍注册，最终提交五份有效方案，由主办方评估八种模型。竞赛旨在独立评估当前最先进算法的性能。由于目前缺乏跨数据集的独立评估，本工作确立了身份证活体攻击检测的最新水平。为此，使用了包含四个不同国家身份证的隔离测试集，并提供了基线算法进行统一评测。结果显示，匿名团队以74.80%的平均排名成绩位居第一，紧随其后的是IDVC团队，达到77.65%。
原文摘要 · Abstract (English)
This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB2024). 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%.
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