# Synthetic ID Card Image Generation for Improving Presentation Attack Detection

arXiv: https://arxiv.org/abs/2211.00098 · HTML: https://mlsanity.com/paper/2211.00098/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 28 references that are in the map.
- First posted on arXiv 31 Oct 2022.

## Builds on (most cited first, 14 of 14)

- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [MobileNetV2: Inverted Residuals and Linear Bottlenecks](https://mlsanity.com/paper/1801.04381/) (2018)
- [Improved Techniques for Training GANs](https://mlsanity.com/paper/1606.03498/) (2016)
- [Training Generative Adversarial Networks with Limited Data](https://mlsanity.com/paper/2006.06676/) (2020)
- [An empirical study on evaluation metrics of generative adversarial networks](https://mlsanity.com/paper/1806.07755/) (2018)
- [StyleGAN2 Distillation for Feed-forward Image Manipulation](https://mlsanity.com/paper/2003.03581/) (2020)
- [CycleGAN, a Master of Steganography](https://mlsanity.com/paper/1712.02950/) (2017)
- [MIDV-500: A Dataset for Identity Documents Analysis and Recognition on Mobile Devices in Video Stream](https://mlsanity.com/paper/1807.05786/) (2018)
- [SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data](https://mlsanity.com/paper/2208.07337/) (2022)
- [Large-scale Bisample Learning on ID Versus Spot Face Recognition](https://mlsanity.com/paper/1806.03018/) (2018)
- [DocFace: Matching ID Document Photos to Selfies](https://mlsanity.com/paper/1805.02283/) (2018)
- [DocFace+: ID Document to Selfie Matching](https://mlsanity.com/paper/1809.05620/) (2018)
- [Identity Document to Selfie Face Matching Across Adolescence](https://mlsanity.com/paper/1912.10021/) (2019)
- [Towards an Efficient Semantic Segmentation Method of ID Cards for Verification Systems](https://mlsanity.com/paper/2111.12764/) (2021)

## Built on by (most cited first, 18 of 18)

- [First Competition on Presentation Attack Detection on ID Card](https://mlsanity.com/paper/2409.00372/) (2024)
- [Privacy-Aware Detection of Fake Identity Documents: Methodology, Benchmark, and Improved Algorithms (FakeIDet2)](https://mlsanity.com/paper/2508.11716/) (2025)
- [Few-Shot Learning: Expanding ID Cards Presentation Attack Detection to Unknown ID Countries](https://mlsanity.com/paper/2409.06842/) (2024)
- [SynID: Passport Synthetic Dataset for Presentation Attack Detection](https://mlsanity.com/paper/2505.07540/) (2025)
- [Synthetic dataset of ID and Travel Document](https://mlsanity.com/paper/2401.01858/) (2024)
- [METR: Image Watermarking with Large Number of Unique Messages](https://mlsanity.com/paper/2408.08340/) (2024)
- [FakeIDet: Exploring Patches for Privacy-Preserving Fake ID Detection](https://mlsanity.com/paper/2504.07761/) (2025)
- [Improving Presentation Attack Detection for ID Cards on Remote Verification Systems](https://mlsanity.com/paper/2301.09542/) (2023)
- [Multi-modal Document Presentation Attack Detection With Forensics Trace Disentanglement](https://mlsanity.com/paper/2404.06663/) (2024)
- [Generating Automatically Print/Scan Textures for Morphing Attack Detection Applications](https://mlsanity.com/paper/2408.09558/) (2024)
- [AI-based Identity Fraud Detection: A Systematic Review](https://mlsanity.com/paper/2501.09239/) (2025)
- [Can Foundation Models Generalise the Presentation Attack Detection Capabilities on ID Cards?](https://mlsanity.com/paper/2506.05263/) (2025)
- [Identity Card Presentation Attack Detection: A Systematic Review](https://mlsanity.com/paper/2511.06056/) (2025)
- [Open-Set: ID Card Presentation Attack Detection using Neural Transfer Style](https://mlsanity.com/paper/2312.13993/) (2023)
- [ID-Card Synthetic Generation: Toward a Simulated Bona fide Dataset](https://mlsanity.com/paper/2508.13078/) (2025)
- [From Vision to Text: A Compact Multimodal Approach for Robust, Cross-Domain Presentation Attack Detection on ID Cards](https://mlsanity.com/paper/2606.06966/) (2026)
- [FakeIDet3-DB: Refining Digital Attacks and Patch Extraction for Secure ID Benchmarking](https://mlsanity.com/paper/2607.26641/) (2026)
- [IDSPACE: A Novel Document Generator for Reliable Evaluation of Digital Identity Verification Systems [Extended Technical Report]](https://mlsanity.com/paper/2609.03052/) (2026)

## Abstract (arXiv)

Currently, it is ever more common to access online services for activities which formerly required physical attendance. From banking operations to visa applications, a significant number of processes have been digitised, especially since the advent of the COVID-19 pandemic, requiring remote biometric authentication of the user. On the downside, some subjects intend to interfere with the normal operation of remote systems for personal profit by using fake identity documents, such as passports and ID cards. Deep learning solutions to detect such frauds have been presented in the literature. However, due to privacy concerns and the sensitive nature of personal identity documents, developing a dataset with the necessary number of examples for training deep neural networks is challenging. This work explores three methods for synthetically generating ID card images to increase the amount of data while training fraud-detection networks. These methods include computer vision algorithms and Generative Adversarial Networks. Our results indicate that databases can be supplemented with synthetic images without any loss in performance for the print/scan Presentation Attack Instrument Species (PAIS) and a loss in performance of 1% for the screen capture PAIS.