Synthetic dataset of ID and Travel Document
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Abstract (arXiv)
This paper presents a new synthetic dataset of ID and travel documents, called SIDTD. The SIDTD dataset is created to help training and evaluating forged ID documents detection systems. Such a dataset has become a necessity as ID documents contain personal information and a public dataset of real documents can not be released. Moreover, forged documents are scarce, compared to legit ones, and the way they are generated varies from one fraudster to another resulting in a class of high intra-variability. In this paper we trained state-of-the-art models on this dataset and we compare them to the performance achieved in larger, but private, datasets. The creation of this dataset will help to document image analysis community to progress in the task of ID document verification.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 8 of its 15 references that are in the map. First posted on arXiv 3 Jan 2024.
Builds on
8 of 15 references.
References · 8
- 2017Attention Is All You Needcited by 60,361
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
- 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
- 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
- 2021TransFG: A Transformer Architecture for Fine-grained Recognitioncited by 132
- 2021MIDV-2020: A Comprehensive Benchmark Dataset for Identity Document Analysiscited by 32
- 2022Synthetic ID Card Image Generation for Improving Presentation Attack Detectioncited by 18
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Citing papers per year: 2024: 1; 2025: 2.
3 papers.