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PSENet

Introduction

[ALGORITHM]

@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/CVF Conference on Computer Vision and Pattern Recognition},
  pages={9336--9345},
  year={2019}
}

Results and models

CTW1500

Method Backbone Extra Data Training set Test set #epochs Test size Recall Precision Hmean Download
PSENet-4s ResNet50 - CTW1500 Train CTW1500 Test 600 1280 0.728 (0.717) 0.849 (0.852) 0.784 (0.779) model | log

ICDAR2015

Method Backbone Extra Data Training set Test set #epochs Test size Recall Precision Hmean Download
PSENet-4s ResNet50 - IC15 Train IC15 Test 600 2240 0.784 (0.753) 0.831 (0.867) 0.807 (0.806) model | log
PSENet-4s ResNet50 pretrain on IC17 MLT model IC15 Train IC15 Test 600 2240 0.834 0.861 0.847 model | log

Note: We've upgraded our IoU backend from Polygon3 to shapely. There are some performance differences for some models due to the backends' different logics to handle invalid polygons (more info here). New evaluation result is presented in brackets and new logs will be uploaded soon.