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Found 4 papers, 3 papers with code
LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis
Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks.
OLALA: Object-Level Active Learning for Efficient Document Layout Annotation
Document images often have intricate layout structures, with numerous content regions (e. g. texts, figures, tables) densely arranged on each page.
A Large Dataset of Historical Japanese Documents with Complex Layouts
Deep learning-based approaches for automatic document layout analysis and content extraction have the potential to unlock rich information trapped in historical documents on a large scale.
Information Extraction from Text Regions with Complex Tabular Structure
Recent innovations have improved layout analysis of document images, significantly improving our ability to identify text and non-text regions.
