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Adversarial learning based attentional scene text recognizer
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DOI：10.1016/j.patrec.2020.07.027.png)
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Abstract
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In this paper, we propose an adversarial learning based attentional scene text recognizer to solve the distortion problem of scene text image. We choose a rectification module which can rectify images in both horizontal and vertical directions, and use a recognizer based on the attention mechanism. Through the adversarial learning of the rectification network and the recognition network, we iteratively improve the rectification effect and the recognition performance. The entire network is trained with weak supervision, so only images and corresponding text labels are needed. Our method achieves high performance for both regular and irregular scene text images, and the experimental results tested on multiple benchmarks prove that our method achieves the performance of state-of-the-art. (C) 2020 Elsevier B.V. All rights reserved.
Keywords:
Scene text recognition
Generative adversarial network
Image rectification
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