update the readme

Author: ayumiymk

.gitignore

@@ -233,7 +233,7 @@ venv.bak/
 
 # Project specific
 logs
-*.png
+# *.png
 *.jpg
 *.jpeg
 viz

README.md

@@ -2,12 +2,18 @@
 
 This repository implements the ASTER in pytorch. Origin software could be found in [here](https://github.com/bgshih/aster).
 
+ASTER is an accurate scene text recognizer with flexible rectification mechanism. The research paper can be found [here](https://ieeexplore.ieee.org/abstract/document/8395027/).
+
+![ASTER Overview](overview.png)
+
 ## Train
+
 ```
 bash scripts/stn_att_rec.sh
 ```
 
 ## Test
+
 ```
 bash scripts/main_test_all.sh
 ```
@@ -18,7 +24,6 @@ bash scripts/main_test_all.sh
 |:-------------:|:------:|:----:|:-----:|:-----:|:-----:|:-----:|
 |  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. 
 
@@ -29,5 +34,38 @@ You can use the codes to bootstrap for your next text recognition research proje
 
 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}
+}
+```
 
 IMPORTANT NOTICE: Although this software is licensed under MIT, our intention is to make it free for academic research purposes. If you are going to use it in a product, we suggest you [contact us]([email protected]) regarding possible patent issues.