ASTER: Attentional Scene Text Recognizer with Flexible Rectification

This repository implements the ASTER in pytorch. Origin software could be found in here.

ASTER is an accurate scene text recognizer with flexible rectification mechanism. The research paper can be found here.

Train

bash scripts/stn_att_rec.sh

Test

bash scripts/main_test_all.sh

Reproduced results

	IIIT5k	SVT	IC03	IC13	SVTP	CUTE
ASTER (L2R)	92.67	-	93.72	90.74	78.76	76.39
ASTER.Pytorch	93.2	89.2	92.2	91	81.2	81.9

At present, the bidirectional attention decoder proposed in ASTER is not included in my implementation.

You can use the codes to bootstrap for your next text recognition research project.

Data preparation

We give an example to construct your own datasets. Details please refer to tools/create_svtp_lmdb.py.

Citation

If you find this project helpful for your research, please cite the following papers:

@article{bshi2018aster,
  author  = {Baoguang Shi and
               Mingkun Yang and
               Xinggang Wang and
               Pengyuan Lyu and
               Cong Yao and
               Xiang Bai},
  title   = {ASTER: An Attentional Scene Text Recognizer with Flexible Rectification},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  volume  = {}, 
  number  = {}, 
  pages   = {1-1},
  year    = {2018}, 
}

@inproceedings{ShiWLYB16,
  author    = {Baoguang Shi and
               Xinggang Wang and
               Pengyuan Lyu and
               Cong Yao and
               Xiang Bai},
  title     = {Robust Scene Text Recognition with Automatic Rectification},
  booktitle = {2016 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016},
  pages     = {4168--4176},
  year      = {2016}
}