IDP Research
This section contains summaries and analyses of important research papers in the field of Intelligent Document Processing (IDP).
Papers are organized chronologically, with the most recent papers appearing first. Each paper has its own page with a summary, key findings, and implications for IDP applications.
Status of this list
Up to this point, this homepage provides only a limited selection of relevant research papers. Until the list is expanded, this documentation offers links to key resources you may find useful as a starting point.
- Google Scholar Profile by Lei Cui | Microsoft
- GitHub Profile by Niels Rogge | Hugging Face
- Philipp Schmid | Google
Adding New Research
If you would like to add a new research paper:
- Follow the contribution guide to learn how to set up a research paper folder
- Create a pull request with your additions
- I will review and merge your contribution
Research Categories
Document Understanding
Papers related to document understanding, classification, and interpretation
Data Extraction
Research on techniques for extracting structured data from unstructured documents
OCR Advancements
Papers focused on improving optical character recognition and text recognition
Layout Analysis
Research on document layout analysis and segmentation techniques
Multi-modal Models
Papers exploring models that combine text, vision, and other modalities for document processing
Industry Applications
Research focusing on specific industry applications of IDP technologies
