Document understanding dataset and evaluation (dude)
J Van Landeghem, R Tito… - Proceedings of the …, 2023 - openaccess.thecvf.com
We call on the Document AI (DocAI) community to re-evaluate current methodologies and
embrace the challenge of creating more practically-oriented benchmarks. Document …
embrace the challenge of creating more practically-oriented benchmarks. Document …
Due: End-to-end document understanding benchmark
Understanding documents with rich layouts plays a vital role in digitization and hyper-
automation but remains a challenging topic in the NLP research community. Additionally, the …
automation but remains a challenging topic in the NLP research community. Additionally, the …
Ocr-free document understanding transformer
Understanding document images (eg, invoices) is a core but challenging task since it
requires complex functions such as reading text and a holistic understanding of the …
requires complex functions such as reading text and a holistic understanding of the …
mplug-docowl 1.5: Unified structure learning for ocr-free document understanding
Structure information is critical for understanding the semantics of text-rich images, such as
documents, tables, and charts. Existing Multimodal Large Language Models (MLLMs) for …
documents, tables, and charts. Existing Multimodal Large Language Models (MLLMs) for …
Xylayoutlm: Towards layout-aware multimodal networks for visually-rich document understanding
Recently, various multimodal networks for Visually-Rich Document Understanding (VRDU)
have been proposed, showing the promotion of transformers by integrating visual and layout …
have been proposed, showing the promotion of transformers by integrating visual and layout …
Docformer: End-to-end transformer for document understanding
We present DocFormer-a multi-modal transformer based architecture for the task of Visual
Document Understanding (VDU). VDU is a challenging problem which aims to understand …
Document Understanding (VDU). VDU is a challenging problem which aims to understand …
Unifying vision, text, and layout for universal document processing
Abstract We propose Universal Document Processing (UDOP), a foundation Document AI
model which unifies text, image, and layout modalities together with varied task formats …
model which unifies text, image, and layout modalities together with varied task formats …
Textmonkey: An ocr-free large multimodal model for understanding document
Y Liu, B Yang, Q Liu, Z Li, Z Ma, S Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
We present TextMonkey, a large multimodal model (LMM) tailored for text-centric tasks,
including document question answering (DocVQA) and scene text analysis. Our approach …
including document question answering (DocVQA) and scene text analysis. Our approach …
Attention where it matters: Rethinking visual document understanding with selective region concentration
We propose a novel end-to-end document understanding model called SeRum (SElective
Region Understanding Model) for extracting meaningful information from document images …
Region Understanding Model) for extracting meaningful information from document images …
Layoutlmv2: Multi-modal pre-training for visually-rich document understanding
Pre-training of text and layout has proved effective in a variety of visually-rich document
understanding tasks due to its effective model architecture and the advantage of large-scale …
understanding tasks due to its effective model architecture and the advantage of large-scale …