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Shape Robust Text Detection with Progressive Scale Expansion Network

Introduction

@inproceedings{wang2019shape,
  title={Shape Robust Text Detection with Progressive Scale Expansion Network},
  author={Wang, Wenhai and Xie, Enze and Li, Xiang and Hou, Wenbo and Lu, Tong and Yu, Gang and Shao, Shuai},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={9336--9345},
  year={2019}
}

Results and Models

  • Total-Text
Method Backbone Finetune Precision (%) Recall (%) F-measure (%) Config Download
PSENet ResNet50 N 87.3 77.9 82.3 config model
PSENet (paper) ResNet50 N 81.8 75.1 78.3 - -
PSENet ResNet50 Y 89.3 79.6 84.2 config model
PSENet (paper) ResNet50 Y 84.0 78.0 80.9 - -
  • CTW1500
Method Backbone Finetune Precision (%) Recall (%) F-measure (%) Config Download
PSENet ResNet50 N 82.6 76.4 79.4 config model
PSENet (paper) ResNet50 N 80.6 75.6 78.0 - -
PSENet ResNet50 Y 84.3 78.9 81.5 config model
PSENet (paper) ResNet50 Y 84.8 79.7 82.2 - -
  • ICDAR 2015
Method Backbone Finetune Scale Precision (%) Recall (%) F-measure (%) Config Download
PSENet ResNet50 N S: 736 83.6 74.0 78.5 config model
PSENet ResNet50 N S: 1024 84.4 76.3 80.2 config model
PSENet (paper) ResNet50 N L: 2240 81.5 79.7 80.6 - -
PSENet ResNet50 Y S: 736 85.3 76.8 80.9 config model
PSENet ResNet50 Y S: 1024 86.2 79.4 82.7 config model
PSENet (paper) ResNet50 Y L: 2240 86.9 84.5 85.7 - -
  • SynthText
Method Backbone Config Download
PSENet ResNet50 config model