171 citations · 377 across the 18 of their papers we have counts for
15 papers · 1 filter
Exploring In-Context Learning for Handwritten Text Recognition
Eric Ayllon, Abel Gandia, Jorge Calvo-Zaragoza
Handwritten Text Recognition (HTR) systems have become an indispensable tool for the digitization of historical documents. Not only do they cut down time and cost, but they also al…
Handwritten Text Recognition Lives in the High-Pixel Variance Subspace
Carlos Garrido-Munoz, Jorge Calvo-Zaragoza
In self-supervised pretraining for Handwritten Text Recognition (HTR), pixel reconstruction methods outperform contrastive methods, unlike in natural-image classification. We argue…
Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogies
Carlos Garrido-Munoz, Aniello Panariello, Silvia Cascianelli +4
Handwritten Text Recognition (HTR) models trained on synthetic handwriting often struggle to generalize to real text, and existing adaptation methods still require real samples fro…
Handwritten Text Recognition: A Survey
Carlos Garrido-Munoz, Antonio Rios-Vila, Jorge Calvo-Zaragoza
Handwritten Text Recognition (HTR) has become an essential field within pattern recognition and machine learning, with applications spanning historical document preservation to mod…
Maritime Search and Rescue Missions with Aerial Images: A Survey
Juan P. Martinez-Esteso, Francisco J. Castellanos, Jorge Calvo-Zaragoza +1
The speed of response by search and rescue teams at sea is of vital importance, as survival may depend on it. Recent technological advancements have led to the development of more…
Self-Supervised Learning for Text Recognition: A Critical Survey
Carlos Penarrubia, Jose J. Valero-Mas, Jorge Calvo-Zaragoza
Text Recognition (TR) refers to the research area that focuses on retrieving textual information from images, a topic that has seen significant advancements in the last decade due…
Align, Minimize and Diversify: A Source-Free Unsupervised Domain Adaptation Method for Handwritten Text Recognition
María Alfaro-Contreras, Jorge Calvo-Zaragoza
This paper serves to introduce the Align, Minimize and Diversify (AMD) method, a Source-Free Unsupervised Domain Adaptation approach for Handwritten Text Recognition (HTR). This fr…
SDFR: Synthetic Data for Face Recognition Competition
Hatef Otroshi Shahreza, Christophe Ecabert, Anjith George +25
Large-scale face recognition datasets are collected by crawling the Internet and without individuals' consent, raising legal, ethical, and privacy concerns. With the recent advance…
Image Transformation Sequence Retrieval with General Reinforcement Learning
Enrique Mas-Candela, Antonio Ríos-Vila, Jorge Calvo-Zaragoza
In this work, the novel Image Transformation Sequence Retrieval (ITSR) task is presented, in which a model must retrieve the sequence of transformations between two given images th…
End-to-End Page-Level Assessment of Handwritten Text Recognition
Enrique Vidal, Alejandro H. Toselli, Antonio Ríos-Vila +1
The evaluation of Handwritten Text Recognition (HTR) systems has traditionally used metrics based on the edit distance between HTR and ground truth (GT) transcripts, at both the ch…
Proceedings of the 4th International Workshop on Reading Music Systems
Jorge Calvo-Zaragoza, Alexander Pacha, Elona Shatri
The International Workshop on Reading Music Systems (WoRMS) is a workshop that tries to connect researchers who develop systems for reading music, such as in the field of Optical M…
Region-based Layout Analysis of Music Score Images
Francisco J. Castellanos, Carlos Garrido-Munoz, Antonio Ríos-Vila +1
The Layout Analysis (LA) stage is of vital importance to the correct performance of an Optical Music Recognition (OMR) system. It identifies the regions of interest, such as staves…
Unsupervised Neural Domain Adaptation for Document Image Binarization
Francisco J. Castellanos, Antonio-Javier Gallego, Jorge Calvo-Zaragoza
Binarization is a well-known image processing task, whose objective is to separate the foreground of an image from the background. One of the many tasks for which it is useful is t…
Understanding Optical Music Recognition
Jorge Calvo-Zaragoza, Jan Hajič, Alexander Pacha
For over 50 years, researchers have been trying to teach computers to read music notation, referred to as Optical Music Recognition (OMR). However, this field is still difficult to…
A selectional auto-encoder approach for document image binarization
Jorge Calvo-Zaragoza, Antonio-Javier Gallego
Binarization plays a key role in the automatic information retrieval from document images. This process is usually performed in the first stages of documents analysis systems, and…