mirror of https://github.com/open-mmlab/mmocr.git
3.5 KiB
3.5 KiB
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 | 0.849 | 0.784 | 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 | 0.831 | 0.807 | model | log |
| PSENet-4s | ResNet50 | pretrain on IC17 MLT model | IC15 Train | IC15 Test | 600 | 2240 | 0.834 | 0.861 | 0.847 | model | log |