# First Competition on Presentation Attack Detection on ID Card

arXiv: https://arxiv.org/abs/2409.00372 · HTML: https://mlsanity.com/paper/2409.00372/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 27 references that are in the map.
- First posted on arXiv 31 Aug 2024.

## Builds on (most cited first, 13 of 13)

- [Densely Connected Convolutional Networks](https://mlsanity.com/paper/1608.06993/) (2016)
- [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://mlsanity.com/paper/1704.04861/) (2017)
- [Xception: Deep Learning with Depthwise Separable Convolutions](https://mlsanity.com/paper/1610.02357/) (2016)
- [Searching for MobileNetV3](https://mlsanity.com/paper/1905.02244/) (2019)
- [Dynamic Snake Convolution based on Topological Geometric Constraints for Tubular Structure Segmentation](https://mlsanity.com/paper/2307.08388/) (2023)
- [MIDV-500: A Dataset for Identity Documents Analysis and Recognition on Mobile Devices in Video Stream](https://mlsanity.com/paper/1807.05786/) (2018)
- [MIDV-2020: A Comprehensive Benchmark Dataset for Identity Document Analysis](https://mlsanity.com/paper/2107.00396/) (2021)
- [PW-MAD: Pixel-wise Supervision for Generalized Face Morphing Attack Detection](https://mlsanity.com/paper/2108.10291/) (2021)
- [MIDV-2019: Challenges of the modern mobile-based document OCR](https://mlsanity.com/paper/1910.04009/) (2019)
- [Synthetic ID Card Image Generation for Improving Presentation Attack Detection](https://mlsanity.com/paper/2211.00098/) (2022)
- [DocFace+: ID Document to Selfie Matching](https://mlsanity.com/paper/1809.05620/) (2018)
- [e-Counterfeit: a mobile-server platform for document counterfeit detection](https://mlsanity.com/paper/1708.06126/) (2017)
- [Improving Presentation Attack Detection for ID Cards on Remote Verification Systems](https://mlsanity.com/paper/2301.09542/) (2023)

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

- [Second Competition on Presentation Attack Detection on ID Card](https://mlsanity.com/paper/2507.20404/) (2025)
- [Privacy-Aware Detection of Fake Identity Documents: Methodology, Benchmark, and Improved Algorithms (FakeIDet2)](https://mlsanity.com/paper/2508.11716/) (2025)
- [FantasyID: A dataset for detecting digital manipulations of ID-documents](https://mlsanity.com/paper/2507.20808/) (2025)
- [SynID: Passport Synthetic Dataset for Presentation Attack Detection](https://mlsanity.com/paper/2505.07540/) (2025)
- [FakeIDet: Exploring Patches for Privacy-Preserving Fake ID Detection](https://mlsanity.com/paper/2504.07761/) (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)
- [EdgeDoc: Hybrid CNN-Transformer Model for Accurate Forgery Detection and Localization in ID Documents](https://mlsanity.com/paper/2508.16284/) (2025)
- [Detecting Text Manipulation in Images using Vision Language Models](https://mlsanity.com/paper/2509.10278/) (2025)
- [From Forgeries to Foundation Models: A Systematic Survey of Identity Document Attack and Detection](https://mlsanity.com/paper/2607.01442/) (2026)
- [ID-Card Synthetic Generation: Toward a Simulated Bona fide Dataset](https://mlsanity.com/paper/2508.13078/) (2025)
- [Multimodal Models Meet Presentation Attack Detection on ID Documents](https://mlsanity.com/paper/2603.29422/) (2026)
- [Field-Localized Forgery Detection for Digital Identity Documents](https://mlsanity.com/paper/2605.09089/) (2026)
- [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)
- [Verification of Dynamic Holographic Behavior in Identity Documents](https://mlsanity.com/paper/2607.06466/) (2026)
- [The Third Competition on Document Forgery Detection on ID-Cards and Passports](https://mlsanity.com/paper/2607.15734/) (2026)
- [FakeIDet3-DB: Refining Digital Attacks and Patch Extraction for Secure ID Benchmarking](https://mlsanity.com/paper/2607.26641/) (2026)
- [Towards Zero-Shot Domain Generalization for ID Cards Presentation Attack Detection](https://mlsanity.com/paper/2608.16591/) (2026)

## Abstract (arXiv)

This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB2024). The competition attracted a total of ten registered teams, both from academia and industry. In the end, the participating teams submitted five valid submissions, with eight models to be evaluated by the organisers. The competition presented an independent assessment of current state-of-the-art algorithms. Today, no independent evaluation on cross-dataset is available; therefore, this work determined the state-of-the-art on ID cards. To reach this goal, a sequestered test set and baseline algorithms were used to evaluate and compare all the proposals. The sequestered test dataset contains ID cards from four different countries. In summary, a team that chose to be "Anonymous" reached the best average ranking results of 74.80%, followed very closely by the "IDVC" team with 77.65%.