CORTEXA
← Browse
arxivcs.CV2026-07-17

The Third Competition on Document Forgery Detection on ID-Cards and Passports

Juan E. Tapia, Mario Nieto, Juan M. Espin, Álvaro S. Rocamora, Javier Barrachina, Naser Damer, Christoph Busch

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.

View free PDFSource page

Related papers

arxivcs.LGcs.CRcs.CVcs.MM2026-07-23

Physiological Signals as a Forensic Modality for Talking-Face Deepfake Detection

Othmane Harraq, Tamer Aldwairi

Talking-face (TF) deepfake generation synthesizes photore- alistic facial video from a static source image and an au- dio signal, producing forgeries that current image-based detectors consistently fail to identify. Unlike face-swap ma- nipulation, TF synthesis has no underlying…

View free PDFSource page
arxivcs.CV2026-07-31

Explaining AI-Image Detection: What the Heatmap Actually Shows

Leonid Kuturin, Ilya Sotnikov, Mark Khusnutdinov, Mikhail Potemkin, Pavel Baranas, Aleksandra Korepanova, et al.

A marketplace review photograph is a document: platforms approve refunds on it, and generative models drove the cost of forging one to zero. We study that detection problem, so we build a detector and attach an attribution map as its evidence, then measure what that pair delivers…

View free PDFSource page
arxivcs.CVcs.LG2026-07-31

SciFigPlag-Bench: A Benchmark for Provenance-Aware Scientific Figure Plagiarism Detection

Zhiying Cui, Minghao Yang, Linlin Gao, Jie Liu, Pengyuan Li

Scientific figures often encode the visual evidence behind scientific findings, yet figure plagiarism remains underexplored as a benchmarked multimodal evaluation problem. We present SciFigPlag-Bench, a benchmark for provenance-aware reasoning over scientific figures in scholarly…

View free PDFSource page
arxivcs.CV2026-07-31

HierDoc: Hierarchical Page-to-Region Evidence Routing for Long-Document Visual Question Answering

Rongjian Gu, Wengang Zhou, Junyu Xiong, Yonghui Wang, Bing Yin, Bei Wang, et al.

Multi-page document visual question answering requires locating sparse evidence at both the page and region levels. Existing approaches typically emphasize one level over the other: page-centric methods focus on page acquisition, with region operations serving mainly as navigatio…

View free PDFSource page