Scene Text Recognition in Natural Scene Images
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Given an image patch with text information, a scene text recognition algorithm is expected to infer the text content in it. Being able to retrieve text information (which exists abundantly in our every day scene), has numerous real-life applications: text-aided autonomous driving system, mobile language translation apps, multimedia retrieval system, etc. Arbitrary-oriented text recognition is much more challenging than horizontal text recognition[1-2], yet it is part of the attributes in text in the wild. Being able to read text regardless of its orientation brings the robustness of scene text understanding algorithm to a new level.
 Lyu, Pengyuan, et al. "Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes." arXiv preprint arXiv:1807.02242 (2018).
 Shi, Baoguang, et al. "Robust scene text recognition with automatic rectification." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016.
The evaluation protocol for this task follows the proposal of . A word is considered correctly recognized if at least 80% and all letters are recognized correctly (case-sensitive). The expected output is a string of characters, in word level.
S. M. Lucas, A. Panaretos, L. Sosa, A. Tang, S. Wong, and R. Young. ICDAR 2003 robust reading competitions. ICDAR, 2003.
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