SceneTextPapers

Tracking the latest progress in Scene Text Detection and Recognition: must-read papers well organized

Information about this repository

This repo serves as a complement to our IJCV paper:

• Scene Text Detection and Recognition: The Deep Learning Era. Shangbang Long, Xin He, Cong Yao. [arxiv preprint] [IJCV version]

Citing this work

If you find this paper helpful in understanding the latest history of scene text detection&recognition algorithms as well as designing new ones , you are highly encouraged (though not required) to cite our paper

@article{long2020scene,
  title={Scene text detection and recognition: The deep learning era},
  author={Long, Shangbang and He, Xin and Yao, Cong},
  journal={International Journal of Computer Vision},
  pages={1--24},
  year={2020},
  publisher={Springer}
}

Papers

I. Other Survey Papers:

1. Scene text detection and recognition: Recent advances and future trends. Zhu, Yingying and Yao, Cong and Bai, Xiang. Frontiers of Computer Science, 2016[paper]
2. Text detection, tracking and recognition in video: A comprehensive survey. Yin, Xu-Cheng and Zuo, Ze-Yu and Tian, Shu and Liu, Cheng-Lin. TIP, 2016 [paper]
3. Text detection and recognition in imagery: A survey. Ye, Qixiang and Doermann, David. TPAMI, 2015 [paper]
4. Text localization and recognition in images and video. Uchida, Seiichi. 2014 [paper]

II. Main: Scene Text Detection and Recognition

2.1 Detection

2.1.1 Pipeline Simplification

Anchor-based methods

1. Single Shot Text Detector With Regional Attention. He, Pan and Huang, Weilin and He, Tong and Zhu, Qile and Qiao, Yu and Li, Xiaolin. ICCV, 2017 [paper] [code]
2. TextBoxes: A Fast Text Detector with a Single Deep Neural Network. Liao, Minghui and Shi, Baoguang and Bai, Xiang and Wang, Xinggang and Liu, Wenyu. AAAI, 2017 [paper] [code]
3. Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection. Liu, Yuliang and Jin, Lianwen. CVPR, 2017 [paper]
4. Detecting Oriented Text in Natural Images by Linking Segments. Shi, Baoguang and Bai, Xiang and Belongie, Serge. CVPR, 2017 [paper] [code]
5. EAST: An Efficient and Accurate Scene Text Detector. Zhou, Xinyu and Yao, Cong and Wen, He and Wang, Yuzhi and Zhou, Shuchang and He, Weiran and Liang, Jiajun. CVPR, 2017 [paper] [code]

Region proposal methods

1. Detecting Curve Text in the Wild: New Dataset and New Solution. Yuliang, Liu and Lianwen, Jin and Shuaitao, Zhang and Sheng, Zhang. 2017 [paper] [code]
2. R2CNN: rotational region CNN for orientation robust scene text detection. Jiang, Yingying and Zhu, Xiangyu and Wang, Xiaobing and Yang, Shuli and Li, Wei and Wang, Hua and Fu, Pei and Luo, Zhenbo. 2017 [paper]
3. Arbitrary-Oriented Scene Text Detection via Rotation Proposals. Ma, Jianqi and Shao, Weiyuan and Ye, Hao and Wang, Li and Wang, Hong and Zheng, Yingbin and Xue, Xiangyang. T MULTIMEDIA, 2017 [paper] [code]
4. weakly supervised text attention network for generating text proposals in scene images. Rong, Li and MengYi, En and JianQiang, Li and HaiBin, Zhang. ICDAR, 2017 [paper]
5. Rotation-Sensitive Regression for Oriented Scene Text Detection. Liao, Minghui and Zhu, Zhen and Shi, Baoguang and Xia, Gui-song and Bai, Xiang. CVPR, 2018 [paper] [code]
6. Feature Enhancement Network: A Refined Scene Text Detector. Sheng, Zhang and Yuliang, Liu and Lianwen, Jin and Canjie, Luo. AAAI, 2017 [paper]

2.1.2 Differnt Prediction Units

Text instance level

1. Detecting Curve Text in the Wild: New Dataset and New Solution. Yuliang, Liu and Lianwen, Jin and Shuaitao, Zhang and Sheng, Zhang. 2017 [paper] [code]
2. TextBoxes: A Fast Text Detector with a Single Deep Neural Network. Liao, Minghui and Shi, Baoguang and Bai, Xiang and Wang, Xinggang and Liu, Wenyu. AAAI, 2017 [paper] [code]
3. EAST: An Efficient and Accurate Scene Text Detector. Zhou, Xinyu and Yao, Cong and Wen, He and Wang, Yuzhi and Zhou, Shuchang and He, Weiran and Liang, Jiajun. CVPR, 2017 [paper] [code]
4. R2CNN: rotational region CNN for orientation robust scene text detection. Jiang, Yingying and Zhu, Xiangyu and Wang, Xiaobing and Yang, Shuli and Li, Wei and Wang, Hua and Fu, Pei and Luo, Zhenbo. 2017 [paper]
5. Arbitrary-Oriented Scene Text Detection via Rotation Proposals. Ma, Jianqi and Shao, Weiyuan and Ye, Hao and Wang, Li and Wang, Hong and Zheng, Yingbin and Xue, Xiangyang. T MULTIMEDIA, 2017 [paper] [code]
6. Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection. Liu, Yuliang and Jin, Lianwen. CVPR, 2017 [paper]
7. Deep Direct Regression for Multi-Oriented Scene Text Detection. He, Wenhao and Zhang, Xu-Yao and Yin, Fei and Liu, Cheng-Lin. ICCV, 2017 [paper]
8. Fused Text Segmentation Networks for Multi-oriented Scene Text Detection. Dai, Yuchen and Huang, Zheng and Gao, Yuting and Chen, Kai. 2017 [paper]
9. Feature Enhancement Network: A Refined Scene Text Detector. Sheng, Zhang and Yuliang, Liu and Lianwen, Jin and Canjie, Luo. AAAI, 2017 [paper]
10. Rotation-Sensitive Regression for Oriented Scene Text Detection. Liao, Minghui and Zhu, Zhen and Shi, Baoguang and Xia, Gui-song and Bai, Xiang. CVPR, 2018 [paper] [code]

Bottom-up (Pixel)

1. Scene text detection via holistic, multi-channel prediction. Yao, Cong and Bai, Xiang and Sang, Nong and Zhou, Xinyu and Zhou, Shuchang and Cao, Zhimin. 2016 [paper]
2. Multi-oriented text detection with fully convolutional networks. Zhang, Zheng and Zhang, Chengquan and Shen, Wei and Yao, Cong and Liu, Wenyu and Bai, Xiang. CVPR, 2016 [paper] [code]
3. Self-organized Text Detection with Minimal Post-processing via Border Learning. Wu, Yue and Natarajan, Prem. CVPR, 2017 [paper]
4. Multi-scale FCN with Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting in the Wild. He, Dafang and Yang, Xiao and Liang, Chen and Zhou, Zihan and Ororbia, Alexander G and Kifer, Daniel and Giles, C Lee. CVPR, 2017 [paper]
5. Single Shot Text Detector With Regional Attention. He, Pan and Huang, Weilin and He, Tong and Zhu, Qile and Qiao, Yu and Li, Xiaolin. ICCV, 2017 [paper] [code]
6. PixelLink: Detecting Scene Text via Instance Segmentation. Dan, Deng and Haifeng, Liu and Xuelong, Li and Deng, Cai. AAAI, 2018 [paper] [code]

Bottom-up (Components)

1. Detecting text in natural image with connectionist text proposal network. Tian, Zhi and Huang, Weilin and He, Tong and He, Pan and Qiao, Yu. ECCV, 2016 [paper] [code]
2. __Aggregating local context for accurate