most citedLarge Scale Genealogical Information Extraction From Handwritten Quebec Parish Records

14 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

How to Choose Pretrained Handwriting Recognition Models for Single Writer Fine-Tuning

Vittorio Pippi, Silvia Cascianelli, Christopher Kermorvant +1

Recent advancements in Deep Learning-based Handwritten Text Recognition (HTR) have led to models with remarkable performance on both modern and historical manuscripts in large benc…

cs.CV202314 cited

Large Scale Genealogical Information Extraction From Handwritten Quebec Parish Records

Solène Tarride, Martin Maarand, Mélodie Boillet +4

This paper presents a complete workflow designed for extracting information from Quebec handwritten parish registers. The acts in these documents contain individual and family info…

cs.CV2023

SIMARA: a database for key-value information extraction from full pages

Solène Tarride, Mélodie Boillet, Jean-François Moufflet +1

We propose a new database for information extraction from historical handwritten documents. The corpus includes 5,393 finding aids from six different series, dating from the 18th-2…

cs.CV2023

Key-value information extraction from full handwritten pages

Solène Tarride, Mélodie Boillet, Christopher Kermorvant

We propose a Transformer-based approach for information extraction from digitized handwritten documents. Our approach combines, in a single model, the different steps that were so…

cs.CV2022

Confidence Estimation for Object Detection in Document Images

Mélodie Boillet, Christopher Kermorvant, Thierry Paquet

Deep neural networks are becoming increasingly powerful and large and always require more labelled data to be trained. However, since annotating data is time-consuming, it is now n…

cs.CV2022

The LAM Dataset: A Novel Benchmark for Line-Level Handwritten Text Recognition

Silvia Cascianelli, Vittorio Pippi, Martin Maarand +4

Handwritten Text Recognition (HTR) is an open problem at the intersection of Computer Vision and Natural Language Processing. The main challenges, when dealing with historical manu…