166 citations · 272 across the 13 of their papers we have counts for
13 papers
ORCA: Orchestrated Reasoning with Collaborative Agents for Document Visual Question Answering
Aymen Lassoued, Mohamed Ali Souibgui, Yousri Kessentini
Document Visual Question Answering (DocVQA) remains challenging for existing Vision-Language Models (VLMs), especially under complex reasoning and multi-step workflows. Current app…
FATURA: A Multi-Layout Invoice Image Dataset for Document Analysis and Understanding
Mahmoud Limam, Marwa Dhiaf, Yousri Kessentini
Document analysis and understanding models often require extensive annotated data to be trained. However, various document-related tasks extend beyond mere text transcription, requ…
MSdocTr-Lite: A Lite Transformer for Full Page Multi-script Handwriting Recognition
Marwa Dhiaf, Ahmed Cheikh Rouhou, Yousri Kessentini +1
The Transformer has quickly become the dominant architecture for various pattern recognition tasks due to its capacity for long-range representation. However, transformers are data…
ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents
Sana Khamekhem Jemni, Sourour Ammar, Mohamed Ali Souibgui +2
Keyword spotting (KWS) in historical documents is an important tool for the initial exploration of digitized collections. Nowadays, the most efficient KWS methods are relying on ma…
CSSL-MHTR: Continual Self-Supervised Learning for Scalable Multi-script Handwritten Text Recognition
Marwa Dhiaf, Mohamed Ali Souibgui, Kai Wang +4
Self-supervised learning has recently emerged as a strong alternative in document analysis. These approaches are now capable of learning high-quality image representations and over…
Text-DIAE: A Self-Supervised Degradation Invariant Autoencoders for Text Recognition and Document Enhancement
Mohamed Ali Souibgui, Sanket Biswas, Andres Mafla +6
In this paper, we propose a Text-Degradation Invariant Auto Encoder (Text-DIAE), a self-supervised model designed to tackle two tasks, text recognition (handwritten or scene-text)…
DocEnTr: An End-to-End Document Image Enhancement Transformer
Mohamed Ali Souibgui, Sanket Biswas, Sana Khamekhem Jemni +4
Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for…
Transformer-Based Approach for Joint Handwriting and Named Entity Recognition in Historical documents
Ahmed Cheikh Rouhoua, Marwa Dhiaf, Yousri Kessentini +1
The extraction of relevant information carried out by named entities in handwriting documents is still a challenging task. Unlike traditional information extraction approaches that…
Few Shots Are All You Need: A Progressive Few Shot Learning Approach for Low Resource Handwritten Text Recognition
Mohamed Ali Souibgui, Alicia Fornés, Yousri Kessentini +1
Handwritten text recognition in low resource scenarios, such as manuscripts with rare alphabets, is a challenging problem. The main difficulty comes from the very few annotated dat…
Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement
Sana Khamekhem Jemni, Mohamed Ali Souibgui, Yousri Kessentini +1
Handwritten document images can be highly affected by degradation for different reasons: Paper ageing, daily-life scenarios (wrinkles, dust, etc.), bad scanning process and so on.…
One-shot Compositional Data Generation for Low Resource Handwritten Text Recognition
Mohamed Ali Souibgui, Ali Furkan Biten, Sounak Dey +5
Low resource Handwritten Text Recognition (HTR) is a hard problem due to the scarce annotated data and the very limited linguistic information (dictionaries and language models). F…
DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement
Mohamed Ali Souibgui, Yousri Kessentini
Documents often exhibit various forms of degradation, which make it hard to be read and substantially deteriorate the performance of an OCR system. In this paper, we propose an eff…
A Few-shot Learning Approach for Historical Ciphered Manuscript Recognition
Mohamed Ali Souibgui, Alicia Fornés, Yousri Kessentini +1
Encoded (or ciphered) manuscripts are a special type of historical documents that contain encrypted text. The automatic recognition of this kind of documents is challenging because…