3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.CV2021
LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis
Zejiang Shen, Ruochen Zhang, Melissa Dell +3
Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production…
cs.LG2020
OLALA: Object-Level Active Learning for Efficient Document Layout Annotation
Zejiang Shen, Jian Zhao, Melissa Dell +2
Document images often have intricate layout structures, with numerous content regions (e.g. texts, figures, tables) densely arranged on each page. This makes the manual annotation…
cs.CV2020★ 3 cited
A Large Dataset of Historical Japanese Documents with Complex Layouts
Zejiang Shen, Kaixuan Zhang, Melissa Dell
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for automatic document layout analysis and content extraction have the potential to unlock rich information trapped in historical documents on a larg…