Synthetic Data for Text Localisation in Natural Images
Ankush Gupta and Andrea Vedaldi and Andrew Zisserman

@inproceedings{gupta16,
author= {Ankush Gupta and Andrea Vedaldi and Andrew Zisserman},
title= {Synthetic Data for Text Localisation in Natural Images},
booktitle= {IEEE Conference on Computer Vision and Pattern Recognition},
year= {2016},
abstract= {This is a synthetically generated dataset, in which word instances are placed in natural scene images, while taking into account the scene layout.

The dataset consists of *800 thousand* images with approximately *8 million* synthetic word instances. Each text instance is annotated with its text-string, word-level and character-level bounding-boxes.},
keywords= {},
terms= {You (the "Researcher"), have requested permission to use the SynthText in the Wild database (the "Database") at the University of Oxford. In exchange for such permission, the Researcher hereby agrees to the following terms and conditions:

1. Researcher shall use the Database only for non-commercial* research and educational purposes.

2. University of Oxford makes no representations or warranties regarding the Database, including but not limited to warranties of non-infringement or fitness for a particular purpose.

3. Researcher accepts full responsibility for his or her use of the Database and shall defend and indemnify University of Oxford, including their employees, Trustees, officers and agents, against any and all claims arising from Researcher's use of the Database, including but not limited to Researcher's use of any copies of copyrighted images that he or she may create from the Database.

4. Researcher may provide research associates and colleagues with access to the Database provided that they first agree to be bound by these terms and conditions.

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*  For commercial applications and licensing, contact Roy Azoulay at roy.azoulay@innovation.ox.ac.uk},
license= {},
superseded= {},
url= {https://www.robots.ox.ac.uk/~vgg/data/scenetext/}
}