第三届身份证和护照文件伪造检测竞赛
The Third Competition on Document Forgery Detection on ID-Cards and Passports
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中文总结 AI 辅助
第三届身份证和护照文件伪造检测竞赛分两赛道进行，赛道1评估基于合成数据的ID - PAD系统，赛道2面对异构攻击场景。获胜团队Incode在两赛道均取得优异成绩，其结果凸显PAD有效性要求，该竞赛已成该领域领先基准。
中文摘要 AI 辅助
本文全面分析了第三届身份证和护照文件伪造检测国际竞赛的结果。该竞赛分两个不同赛道进行。赛道1在可控但多样的条件下评估基于合成数据的ID - PAD系统，获胜团队Incode的AV_Rank为27.82%。赛道2面对不同领域的异构攻击场景，Incode再次以68.71%的AV_Rank位居榜首。结果表明PAD有效性不仅需要高精度，还需在不同攻击类型和成像条件下保持一致。该竞赛已成为ID文件PAD领域领先的基准，为安全身份验证的性能、可重复性和实际适用性设定了标准。今年有超63支队伍注册，超100个提交模型被评估。
英文摘要
This paper presents a comprehensive analysis of the results from the Third International Competition on Document Forgery Detection on ID-Cards and Passports, which was held across two distinct tracks. Track 1 evaluates a synthetic-data-based ID-PAD system under controlled but diverse conditions, where the winning team, \textit{Incode}, achieves an $AV_{Rank}$ of 27.82%, confirming consistent performance across metrics and highlighting the importance of a balanced, generalizable design. In Track 2, the challenge intensifies with heterogeneous attack scenarios across different domains, where \textit{Incode} again achieved the top position with an $AV_{Rank}$ of 68.71% across thresholds, outperforming some baselines and established methods. These results demonstrate that PAD effectiveness requires not only high accuracy but also consistency across diverse attack types and imaging conditions. The success of this initiative across both tracks underscores the value of collaboration between companies and academic teams. This year, more than \textit{63 teams} were registered, and more than \textit{100 submission models} were evaluated. This competition has evolved into a leading benchmark state-of-the-art in PAD on ID documents, setting the standard for performance, reproducibility, and real-world applicability in secure identity verification.
发表机构
- Hochschule Darmstadt（达姆施塔特应用技术大学）
- Facephi Biometrics（菲斯福生物识别技术公司）
- Fraunhofer Institute for Computer Graphics Research IGD（弗劳恩霍夫计算机图形研究所IGD）
- Department of Computer Science, TU Darmstadt（达姆施塔特工业大学计算机科学系）
- Incode Technologies Inc.（英科德技术公司）
- ID VisionCenter (IDVC)（ID视觉中心）
- University of Ljubljana（卢布尔雅那大学）
- L3i, La Rochelle University（拉罗谢尔大学L3i实验室）
- Mobbel Smart System（莫贝尔智能系统公司）
机构由 AI 辅助整理，请以论文原文为准。
