activity
20152026
most citedBeyond Visual Semantics: Exploring the Role of Scene Text in Image Understanding

37 citations · 115 across the 25 of their papers we have counts for

collaborators
Showing 2024Show all

6 papers · 1 filter

cs.LG2024

NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA

Marlon Tobaben, Mohamed Ali Souibgui, Rubèn Tito +24

The Privacy Preserving Federated Learning Document VQA (PFL-DocVQA) competition challenged the community to develop provably private and communication-efficient solutions in a fede…

cs.CV2024

GRIF-DM: Generation of Rich Impression Fonts using Diffusion Models

Lei Kang, Fei Yang, Kai Wang +5

Fonts are integral to creative endeavors, design processes, and artistic productions. The appropriate selection of a font can significantly enhance artwork and endow advertisements…

cs.CV2024

Image-text matching for large-scale book collections

Artemis Llabrés, Arka Ujjal Dey, Dimosthenis Karatzas +1

We address the problem of detecting and mapping all books in a collection of images to entries in a given book catalogue. Instead of performing independent retrieval for each book…

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

Machine Unlearning for Document Classification

Lei Kang, Mohamed Ali Souibgui, Fei Yang +3

Document understanding models have recently demonstrated remarkable performance by leveraging extensive collections of user documents. However, since documents often contain large…

cs.CV2024

Multi-Page Document Visual Question Answering using Self-Attention Scoring Mechanism

Lei Kang, Rubèn Tito, Ernest Valveny +1

Documents are 2-dimensional carriers of written communication, and as such their interpretation requires a multi-modal approach where textual and visual information are efficiently…