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arxiv: 2505.07540 · v1 · pith:OVIOXWAQnew · submitted 2025-05-12 · 💻 cs.CV

SynID: Passport Synthetic Dataset for Presentation Attack Detection

classification 💻 cs.CV
keywords documentssyntheticattackdatasetdetectionimagesnumberpassport
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. From Forgeries to Foundation Models: A Systematic Survey of Identity Document Attack and Detection

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    A systematic survey unifies presentation, digital injection, and GenAI synthesis attacks on identity documents, audits datasets for a reality gap, identifies SDGI in multimodal models, and reports APCER above 25% for ...

  2. Receipt Replay OOD: A Small Benchmark for Screen Replay Detection Under Domain Shift

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    Receipt Replay OOD is a new small benchmark for evaluating screen replay detection robustness under domain shift using receipt images as proxies for identity documents.