Total-Text: A Comprehensive Dataset for Scene Text Detection and Recognition

28 Oct 2017  ·  Chee Kheng Chng, Chee Seng Chan ·

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

PDF Abstract

Datasets


Introduced in the Paper:

Total-Text

Used in the Paper:

ICDAR 2013 MSRA-TD500

Results from the Paper


Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Scene Text Detection Total-Text Ch,ng et al. F-Measure 36.0% # 27
Precision 40.0 # 24
Recall 33.0 # 24

Methods


No methods listed for this paper. Add relevant methods here