145 citations · 326 across the 9 of their papers we have counts for
9 papers
Meta-DAN: towards an efficient prediction strategy for page-level handwritten text recognition
Denis Coquenet
Recent advances in text recognition led to a paradigm shift for page-level recognition, from multi-step segmentation-based approaches to end-to-end attention-based ones. However, t…
Leveraging Vision-Language Foundation Models for Fine-Grained Downstream Tasks
Denis Coquenet, Clément Rambour, Emanuele Dalsasso +1
Vision-language foundation models such as CLIP have shown impressive zero-shot performance on many tasks and datasets, especially thanks to their free-text inputs. However, they st…
Faster DAN: Multi-target Queries with Document Positional Encoding for End-to-end Handwritten Document Recognition
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…
Towards End-to-end Handwritten Document Recognition
Denis Coquenet
Handwritten text recognition has been widely studied in the last decades for its numerous applications. Nowadays, the state-of-the-art approach consists in a three-step process. Th…
DAN: a Segmentation-free Document Attention Network for Handwritten Document Recognition
Denis Coquenet, Clément Chatelain, Thierry Paquet
Unconstrained handwritten text recognition is a challenging computer vision task. It is traditionally handled by a two-step approach, combining line segmentation followed by text l…
SPAN: a Simple Predict & Align Network for Handwritten Paragraph Recognition
Denis Coquenet, Clément Chatelain, Thierry Paquet
Unconstrained handwriting recognition is an essential task in document analysis. It is usually carried out in two steps. First, the document is segmented into text lines. Second, a…
Recurrence-free unconstrained handwritten text recognition using gated fully convolutional network
Denis Coquenet, Clément Chatelain, Thierry Paquet
Unconstrained handwritten text recognition is a major step in most document analysis tasks. This is generally processed by deep recurrent neural networks and more specifically with…
Have convolutions already made recurrence obsolete for unconstrained handwritten text recognition ?
Denis Coquenet, Yann Soullard, Clément Chatelain +1
Unconstrained handwritten text recognition remains an important challenge for deep neural networks. These last years, recurrent networks and more specifically Long Short-Term Memor…
End-to-end Handwritten Paragraph Text Recognition Using a Vertical Attention Network
Denis Coquenet, Clément Chatelain, Thierry Paquet
Unconstrained handwritten text recognition remains challenging for computer vision systems. Paragraph text recognition is traditionally achieved by two models: the first one for li…