1 code implementation • 17 Jul 2024 • Yannis Karmim, Leshanshui Yang, Raphaël Fournier S'Niehotta, Clément Chatelain, Sébastien Adam, Nicolas Thome
Dynamic link prediction is a critical task in the analysis of evolving networks, with applications ranging from recommender systems to economic exchanges.
no code implementations • 12 Apr 2023 • Leshanshui Yang, Sébastien Adam, Clément Chatelain
In this research area, Dynamic Graph Neural Network (DGNN) has became the state of the art approach and plethora of models have been proposed in the very recent years.
1 code implementation • 25 Jan 2023 • Denis Coquenet, Clément Chatelain, Thierry Paquet
Recent advances in handwritten text recognition enabled to recognize whole documents in an end-to-end way: the Document Attention Network (DAN) recognizes the characters one after the other through an attention-based prediction process until reaching the end of the document.
1 code implementation • 23 Mar 2022 • Denis Coquenet, Clément Chatelain, Thierry Paquet
For the first time, we propose an end-to-end segmentation-free architecture for the task of handwritten document recognition: the Document Attention Network.
Ranked #1 on Handwritten Text Recognition on READ 2016
1 code implementation • 17 Feb 2021 • Denis Coquenet, Clément Chatelain, Thierry Paquet
Unconstrained handwriting recognition is an essential task in document analysis.
Ranked #4 on Handwritten Text Recognition on READ2016(line-level)
1 code implementation • 9 Dec 2020 • Denis Coquenet, Clément Chatelain, Thierry Paquet
Unconstrained handwritten text recognition is a major step in most document analysis tasks.
Ranked #5 on Handwritten Text Recognition on IAM(line-level)
no code implementations • 9 Dec 2020 • Denis Coquenet, Yann Soullard, Clément Chatelain, Thierry Paquet
This has a direct influence on the training time of such architectures, with also a direct consequence on the time required to explore various architectures.
1 code implementation • 7 Dec 2020 • Denis Coquenet, Clément Chatelain, Thierry Paquet
For each text line features, a decoder module recognizes the character sequence associated, leading to the recognition of a whole paragraph.
Ranked #2 on Handwritten Text Recognition on READ2016(line-level)
2 code implementations • 16 Apr 2019 • Benjamin Deguerre, Clément Chatelain, Gilles Gasso
Object detection in still images has drawn a lot of attention over past few years, and with the advent of Deep Learning impressive performances have been achieved with numerous industrial applications.
1 code implementation • 6 Sep 2017 • Soufiane Belharbi, Clément Chatelain, Romain Hérault, Sébastien Adam
In this work, we tackle the issue of training neural networks for classification task when few training samples are available.
no code implementations • 24 Jul 2017 • Bruno Stuner, Clément Chatelain, Thierry Paquet
Offline handwritten text line recognition is a hard task that requires both an efficient optical character recognizer and language model.
no code implementations • 22 Dec 2016 • Bruno Stuner, Clément Chatelain, Thierry Paquet
State-of-the-art methods for handwriting recognition are based on Long Short Term Memory (LSTM) recurrent neural networks (RNN), which now provides very impressive character recognition performance.
1 code implementation • 28 Apr 2015 • Soufiane Belharbi, Romain Hérault, Clément Chatelain, Sébastien Adam
The motivation of this work is to learn the output dependencies that may lie in the output data in order to improve the prediction accuracy.