8 citations · 13 across the 9 of their papers we have counts for
10 papers
GlobalDoc: A Cross-Modal Vision-Language Framework for Real-World Document Image Retrieval and Classification
Souhail Bakkali, Sanket Biswas, Zuheng Ming +4
Visual document understanding (VDU) has rapidly advanced with the development of powerful multi-modal language models. However, these models typically require extensive document pr…
Estimating Post-OCR Denoising Complexity on Numerical Texts
Arthur Hemmer, Jérôme Brachat, Mickaël Coustaty +1
Post-OCR processing has significantly improved over the past few years. However, these have been primarily beneficial for texts consisting of natural, alphabetical words, as oppose…
EAML: Ensemble Self-Attention-based Mutual Learning Network for Document Image Classification
Souhail Bakkali, Ziheng Ming, Mickael Coustaty +1
In the recent past, complex deep neural networks have received huge interest in various document understanding tasks such as document image classification and document retrieval. A…
Document Understanding Dataset and Evaluation (DUDE)
Jordy Van Landeghem, Rubén Tito, Łukasz Borchmann +10
We call on the Document AI (DocAI) community to reevaluate current methodologies and embrace the challenge of creating more practically-oriented benchmarks. Document Understanding…
CHIC: Corporate Document for Visual question Answering
Ibrahim Souleiman Mahamoud, Mickael Coustaty, Aurelie Joseph +2
The massive use of digital documents due to the substantial trend of paperless initiatives confronted some companies to find ways to process thousands of documents per day automati…
DocILE Benchmark for Document Information Localization and Extraction
Štěpán Šimsa, Milan Šulc, Michal Uřičář +8
This paper introduces the DocILE benchmark with the largest dataset of business documents for the tasks of Key Information Localization and Extraction and Line Item Recognition. It…