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PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text

Introduction

@article{wang2021pan++,
  title={PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text},
  author={Wang, Wenhai and Xie, Enze and Li, Xiang and Liu, Xuebo and Liang, Ding and Yang, Zhibo and Lu, Tong and Shen, Chunhua},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2021},
  publisher={IEEE}
}

Results and Models

Text Detection

  • ICDAR 2015
Method Backbone Finetune Precision (%) Recall (%) F-measure (%) Config Download
PAN++ detection only ResNet18 N 84.4 78.5 81.3 config model

End-to-End Text Spotting

  • ICDAR 2015
Method Backbone Finetune Vocabulary Precision (%) Recall (%) F-measure (%) Config Download
PAN++ 736 joint train ResNet18 N N 83.6 54.0 65.6 config model
PAN++ 736 joint train ResNet18 N G 82.3 55.8 66.5 config model
PAN++ 736 joint train ResNet18 N W 90.1 63.9 74.8 config model
PAN++ 736 joint train ResNet18 N S 92.2 70.3 79.8 config model
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PAN++ 896 joint train ResNet18 N N 82.0 56.0 66.6 config model
PAN++ 896 joint train ResNet18 N G 81.5 57.6 67.5 config model
PAN++ 896 joint train ResNet18 N W 90.1 63.9 74.8 config model
PAN++ 896 joint train ResNet18 N S 92.2 70.3 79.8 config model

Todo:

  • Models and configs on other datasets.