MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding
| Autor: | Tsui Hin Lin, Jianyong Chen, Tong Gao, Xiaoyu Yue, Hongbin Sun, Kai Chen, Wayne Zhang, Huaqiang Wei, Wenwei Zhang, Zhanghui Kuang, Dahua Lin, Zhizhong Li, Yiqin Zhu |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Information retrieval Downstream (software development) Computer science Computer Vision and Pattern Recognition (cs.CV) Computer Science - Computer Vision and Pattern Recognition Text recognition Text detection computer.software_genre Pipeline (software) Toolbox Information extraction Named-entity recognition Key (cryptography) computer |
| Zdroj: | ACM Multimedia |
| DOI: | 10.48550/arxiv.2108.06543 |
| Popis: | We present MMOCR-an open-source toolbox which provides a comprehensive pipeline for text detection and recognition, as well as their downstream tasks such as named entity recognition and key information extraction. MMOCR implements 14 state-of-the-art algorithms, which is significantly more than all the existing open-source OCR projects we are aware of to date. To facilitate future research and industrial applications of text recognition-related problems, we also provide a large number of trained models and detailed benchmarks to give insights into the performance of text detection, recognition and understanding. MMOCR is publicly released at https://github.com/open-mmlab/mmocr. Comment: Accepted to ACM MM (Open Source Competition Track) |
| Databáze: | OpenAIRE |
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