Total-Text: A Comprehensive Dataset for Scene Text Detection and
Recognition
release_y4pak5rzujgpngt34t65kcem7u
by
Chee Kheng Chng, Chee Seng Chan
2017
Abstract
Text in curve orientation, despite being one of the common text orientations
in real world environment, has close to zero existence in well received scene
text datasets such as ICDAR2013 and MSRA-TD500. The main motivation of
Total-Text is to fill this gap and facilitate a new research direction for the
scene text community. On top of the conventional horizontal and multi-oriented
texts, it features curved-oriented text. Total-Text is highly diversified in
orientations, more than half of its images have a combination of more than two
orientations. Recently, a new breed of solutions that casted text detection as
a segmentation problem has demonstrated their effectiveness against
multi-oriented text. In order to evaluate its robustness against curved text,
we fine-tuned DeconvNet and benchmark it on Total-Text. Total-Text with its
annotation is available at https://github.com/cs-chan/Total-Text-Dataset
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