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MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding

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arxiv 2108.06543 v1 pith:POMKULAK submitted 2021-08-14 cs.CV

MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding

Zhanghui Kuang , Hongbin Sun , Zhizhong Li , Xiaoyu Yue , Tsui Hin Lin , Jianyong Chen , Huaqiang Wei , Yiqin Zhu
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Tong Gao Wenwei Zhang Kai Chen Wayne Zhang Dahua Lin
This is my paper
classification cs.CV
keywords mmocrrecognitiontextdetectioncomprehensiveopen-sourcetoolboxunderstanding
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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Cited by 1 Pith paper

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  1. E-ARMOR: Edge case Assessment and Review of Multilingual Optical Character Recognition

    cs.CL 2025-09 reject novelty 4.0

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