SynID: Passport Synthetic Dataset for Presentation Attack Detection

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Tapia, Juan E., Stockhardt, Fabian, González-Soler, Lázaro Janier, Busch, Christoph
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866910938501742592
author Tapia, Juan E.
Stockhardt, Fabian
González-Soler, Lázaro Janier
Busch, Christoph
author_facet Tapia, Juan E.
Stockhardt, Fabian
González-Soler, Lázaro Janier
Busch, Christoph
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2505_07540
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle SynID: Passport Synthetic Dataset for Presentation Attack Detection
Tapia, Juan E.
Stockhardt, Fabian
González-Soler, Lázaro Janier
Busch, Christoph
Computer Vision and Pattern Recognition
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.
title SynID: Passport Synthetic Dataset for Presentation Attack Detection
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2505.07540