A Feasible Framework for Arbitrary-Shaped Scene Text Recognition

December 10, 2019 · Entered Twilight · 🏛 arXiv.org

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Repo contents: .gitignore, README.md, common.py, config.py, dataset.py, eval.py, export.py, fonts, imgs, label_dict, model, parse_dict.py, reference, test.py, text_dataflow.py, train.py

Authors Jinjin Zhang, Wei Wang, Di Huang, Qingjie Liu, Yunhong Wang arXiv ID 1912.04561 Category cs.CV: Computer Vision Citations 4 Venue arXiv.org Repository https://github.com/zhang0jhon/AttentionOCR ⭐ 839 Last Checked 2 months ago

Abstract

Deep learning based methods have achieved surprising progress in Scene Text Recognition (STR), one of classic problems in computer vision. In this paper, we propose a feasible framework for multi-lingual arbitrary-shaped STR, including instance segmentation based text detection and language model based attention mechanism for text recognition. Our STR algorithm not only recognizes Latin and Non-Latin characters, but also supports arbitrary-shaped text recognition. Our method wins the championship on Scene Text Spotting Task (Latin Only, Latin and Chinese) of ICDAR2019 Robust Reading Challenge on ArbitraryShaped Text Competition. Code is available at https://github.com/zhang0jhon/AttentionOCR.