most citedDocSynthv2: A Practical Autoregressive Modeling for Document Generation

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

The OCR Quest for Generalization: Learning to recognize low-resource alphabets with model editing

Adrià Molina Rodríguez, Oriol Ramos Terrades, Josep Lladós

Achieving robustness in recognition systems across diverse domains is crucial for their practical utility. While ample data availability is usually assumed, low-resource languages,…

cs.CV2024★ 1 cited

Towards Generative Class Prompt Learning for Fine-grained Visual Recognition

Soumitri Chattopadhyay, Sanket Biswas, Emanuele Vivoli +1

Although foundational vision-language models (VLMs) have proven to be very successful for various semantic discrimination tasks, they still struggle to perform faithfully for fine-…

cs.CV2024

FastTextSpotter: A High-Efficiency Transformer for Multilingual Scene Text Spotting

Alloy Das, Sanket Biswas, Umapada Pal +2

The proliferation of scene text in both structured and unstructured environments presents significant challenges in optical character recognition (OCR), necessitating more efficien…

cs.IR2024

Fetch-A-Set: A Large-Scale OCR-Free Benchmark for Historical Document Retrieval

Adrià Molina, Oriol Ramos Terrades, Josep Lladós

This paper introduces Fetch-A-Set (FAS), a comprehensive benchmark tailored for legislative historical document analysis systems, addressing the challenges of large-scale document…

cs.CV2024

LayeredDoc: Domain Adaptive Document Restoration with a Layer Separation Approach

Maria Pilligua, Nil Biescas, Javier Vazquez-Corral +3

The rapid evolution of intelligent document processing systems demands robust solutions that adapt to diverse domains without extensive retraining. Traditional methods often falter…

cs.CV2024★ 1 cited

DocSynthv2: A Practical Autoregressive Modeling for Document Generation

Sanket Biswas, Rajiv Jain, Vlad I. Morariu +5

While the generation of document layouts has been extensively explored, comprehensive document generation encompassing both layout and content presents a more complex challenge. Th…

cs.CV2024

DistilDoc: Knowledge Distillation for Visually-Rich Document Applications

Jordy Van Landeghem, Subhajit Maity, Ayan Banerjee +4

This work explores knowledge distillation (KD) for visually-rich document (VRD) applications such as document layout analysis (DLA) and document image classification (DIC). While V…