mirror of https://github.com/open-mmlab/mmocr.git
3.4 KiB
3.4 KiB
PSENet
Introduction
[ALGORITHM]
@article{li2018shape,
title={Shape robust text detection with progressive scale expansion network},
author={Li, Xiang and Wang, Wenhai and Hou, Wenbo and Liu, Ruo-Ze and Lu, Tong and Yang, Jian},
journal={arXiv preprint arXiv:1806.02559},
year={2018}
}
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 |