FATURA: A Multi-Layout Invoice Image Dataset for Document Analysis and Understanding
Not on the map. Why?
Abstract (arXiv)
Document analysis and understanding models often require extensive annotated data to be trained. However, various document-related tasks extend beyond mere text transcription, requiring both textual content and precise bounding-box annotations to identify different document elements. Collecting such data becomes particularly challenging, especially in the context of invoices, where privacy concerns add an additional layer of complexity. In this paper, we introduce FATURA, a pivotal resource for researchers in the field of document analysis and understanding. FATURA is a highly diverse dataset featuring multi-layout, annotated invoice document images. Comprising 10,000 invoices with 50 distinct layouts, it represents the largest openly accessible image dataset of invoice documents known to date. We also provide comprehensive benchmarks for various document analysis and understanding tasks and conduct experiments under diverse training and evaluation scenarios. The dataset is freely accessible at https://zenodo.org/record/8261508, empowering researchers to advance the field of document analysis and understanding.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 20 of its 29 references that are in the map. First posted on arXiv 20 Nov 2023.
Builds on
20 of 29 references.
References · 20
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2014Microsoft COCO: Common Objects in Contextcited by 17,608
- 2020End-to-End Object Detection with Transformerscited by 7,414
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
- 2022Generative Adversarial Networkscited by 5,627
- 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,253
- 2015Fast R-CNNcited by 2,933
- 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,162
- 2019LayoutLM: Pre-training of Text and Layout for Document Image Understandingcited by 553
- 2022LayoutLMv3: Pre-training for Document AI with Unified Text and Image Maskingcited by 485
- 2020LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understandingcited by 408
8 more
- 2021OCR-free Document Understanding Transformercited by 407
- 2019FUNSD: A Dataset for Form Understanding in Noisy Scanned Documentscited by 349
- 2021ICDAR2019 Competition on Scanned Receipt OCR and Information Extractioncited by 256
- 2015Evaluation of Deep Convolutional Nets for Document Image Classification and Retrievalcited by 213
- 2021You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detectioncited by 170
- 2022Unified Pretraining Framework for Document Understandingcited by 85
- 2022End-to-end Document Recognition and Understanding with Dessurtcited by 73
- 2021Transformer-Based Approach for Joint Handwriting and Named Entity Recognition in Historical documentscited by 17
Built on by
Citing papers per year: 2025: 2; 2026: 2.
4 papers.
- 2025BoundingDocs: a Unified Dataset for Document Question Answering with Spatial Annotationscited by 8
- 2025An Efficient Deep Learning-Based Approach to Automating Invoice Document Validationcited by 1
- 2026AMALIA-VL: A Native European Portuguese Open-Source Vision and Language Modelcited by 0
- 2026Perception, Layout, and Validation: Calibrated Confidence for Reliable Straight-Through Processing of Financial Documentscited by 0
- 2026Perception, Layout, and Validation: Calibrated Confidence for Reliable Straight-Through Processing of Financial Documents17 Sep 2026
- 2026AMALIA-VL: A Native European Portuguese Open-Source Vision and Language Model17 Jun 2026
- 2025An Efficient Deep Learning-Based Approach to Automating Invoice Document Validation15 Mar 2025
- 2025BoundingDocs: a Unified Dataset for Document Question Answering with Spatial Annotations6 Jan 2025