145 citations · 329 across the 9 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
Object Detection in the DCT Domain: is Luminance the Solution?
Benjamin Deguerre, Clement Chatelain, Gilles Gasso
Object detection in images has reached unprecedented performances. The state-of-the-art methods rely on deep architectures that extract salient features and predict bounding boxes…
Fast object detection in compressed JPEG Images
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 ind…