Enhancing Visually-Rich Document Understanding via Layout Structure Modeling
Abstract
Supplementary Material
- Download
- 21.28 MB
References
Index Terms
- Enhancing Visually-Rich Document Understanding via Layout Structure Modeling
Recommendations
VRDU: A Benchmark for Visually-rich Document Understanding
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningUnderstanding visually-rich business documents to extract structured data and automate business workflows has been receiving attention both in academia and industry. Although recent multi-modal language models have achieved impressive results, we find ...
Enhancing Visually-Rich Document Understanding via Layout Structure Modeling
MMAsia '23 Workshops: Proceedings of the 5th ACM International Conference on Multimedia in Asia WorkshopsIn recent years, the use of multi-modal pre-trained Transformers has led to significant advancements in visually-rich document understanding. However, existing models have mainly focused on features such as text and vision while neglecting the ...
Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer
Document Analysis and Recognition – ICDAR 2021AbstractWe address the challenging problem of Natural Language Comprehension beyond plain-text documents by introducing the TILT neural network architecture which simultaneously learns layout information, visual features, and textual semantics. Contrary ...
Comments
Information & Contributors
Information
Published In
![cover image ACM Conferences](/cms/asset/450b3a72-578a-415e-89ca-c05916d664d2/3581783.cover.jpg)
- General Chairs:
- Abdulmotaleb El Saddik,
- Tao Mei,
- Rita Cucchiara,
- Program Chairs:
- Marco Bertini,
- Diana Patricia Tobon Vallejo,
- Pradeep K. Atrey,
- M. Shamim Hossain
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- Fundamental Research Funds for the Central Universities
- National Science Fund for Distinguished Young Scholars
Conference
Acceptance Rates
Upcoming Conference
- Sponsor:
- sigmm
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 95Total Downloads
- Downloads (Last 12 months)95
- Downloads (Last 6 weeks)10
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in