This paper presents an end-to-end trainable fast scene text detector, named
TextBoxes, which detects scene text with both high accuracy and efficiency in a
single network forward pass, involving no post-process except for a standard
non-maximum suppression. TextBoxes outperforms competing methods in terms of
text localization accuracy and is much faster, taking only 0.09s per image in a
fast implementation. Furthermore, combined with a text recognizer, TextBoxes
significantly outperforms state-of-the-art approaches on word spotting and
end-to-end text recognition tasks.
Beschreibung
[1611.06779] TextBoxes: A Fast Text Detector with a Single Deep Neural Network
%0 Generic
%1 liao2016textboxes
%A Liao, Minghui
%A Shi, Baoguang
%A Bai, Xiang
%A Wang, Xinggang
%A Liu, Wenyu
%D 2016
%K 2016 aaai computer-vision ocr paper
%T TextBoxes: A Fast Text Detector with a Single Deep Neural Network
%U http://arxiv.org/abs/1611.06779
%X This paper presents an end-to-end trainable fast scene text detector, named
TextBoxes, which detects scene text with both high accuracy and efficiency in a
single network forward pass, involving no post-process except for a standard
non-maximum suppression. TextBoxes outperforms competing methods in terms of
text localization accuracy and is much faster, taking only 0.09s per image in a
fast implementation. Furthermore, combined with a text recognizer, TextBoxes
significantly outperforms state-of-the-art approaches on word spotting and
end-to-end text recognition tasks.
@misc{liao2016textboxes,
abstract = {This paper presents an end-to-end trainable fast scene text detector, named
TextBoxes, which detects scene text with both high accuracy and efficiency in a
single network forward pass, involving no post-process except for a standard
non-maximum suppression. TextBoxes outperforms competing methods in terms of
text localization accuracy and is much faster, taking only 0.09s per image in a
fast implementation. Furthermore, combined with a text recognizer, TextBoxes
significantly outperforms state-of-the-art approaches on word spotting and
end-to-end text recognition tasks.},
added-at = {2018-10-11T19:32:33.000+0200},
author = {Liao, Minghui and Shi, Baoguang and Bai, Xiang and Wang, Xinggang and Liu, Wenyu},
biburl = {https://www.bibsonomy.org/bibtex/2d69747a69681784abdb06528126ca441/analyst},
description = {[1611.06779] TextBoxes: A Fast Text Detector with a Single Deep Neural Network},
interhash = {18485517d067769322b166871be8ffa6},
intrahash = {d69747a69681784abdb06528126ca441},
keywords = {2016 aaai computer-vision ocr paper},
note = {cite arxiv:1611.06779Comment: Accepted by AAAI2017},
timestamp = {2018-10-11T19:32:33.000+0200},
title = {TextBoxes: A Fast Text Detector with a Single Deep Neural Network},
url = {http://arxiv.org/abs/1611.06779},
year = 2016
}