FATURA: A Multi-Layout Invoice Image Dataset for Document Analysis and Understanding
This dataset addresses a bottleneck for researchers in document analysis, particularly for invoices where privacy complicates data collection, though it is incremental as it builds on existing dataset efforts.
The authors tackled the lack of diverse annotated invoice data for document analysis by introducing FATURA, a dataset of 10,000 invoice images with 50 layouts, which is the largest openly accessible resource of its kind.
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.