Update README.md

README.md

@@ -14,7 +14,10 @@ size_categories:
 ---
 # UnionST: A Strong Synthetic Engine for Scene Text Recognition
 
-Official data synthesis code of the paper *"What’s Wrong with Synthetic Data for Scene Text Recognition? A Strong Synthetic Engine with Diverse Simulations and Self-Evolution"*.
+<a href='https://arxiv.org/abs/2602.06450'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a>
+<a href='https://huggingface.co/Yesianrohn/UnionST-Models'><img src='https://img.shields.io/badge/Ckpt-Huggingface-yellow'></a> 
+
+Official data of the paper *"What’s Wrong with Synthetic Data for Scene Text Recognition? A Strong Synthetic Engine with Diverse Simulations and Self-Evolution"*.
 
 
 ## Introduction
@@ -28,10 +31,10 @@ Scene Text Recognition (STR) relies critically on large-scale, high-quality trai
 
 ## Dataset
 
-UnionST-S, UnionST-P, and UnionST-R datasets (each containing 5M samples) can be downloaded here. We use the lmdb file format adopted by the mainstream STR protocol.
+UnionST-S, UnionST-P, and UnionST-R datasets are here. We use the lmdb file format adopted by the mainstream STR protocol. In addition, we have  summarized the other STR synthetic datasets compared in the paper, which are available [here](https://huggingface.co/datasets/Yesianrohn/STR-Synth).
 
 ## Training Model
-[OpenOCR](https://github.com/Topdu/OpenOCR)
+The configuration and implementation of the SVTRv2-AR model have been completed in [OpenOCR](https://github.com/Topdu/OpenOCR/blob/main/configs/rec/nrtr/svtrv2_nrtr.yml).
 
 ```bash
 cd OpenOCR
@@ -41,7 +44,12 @@ Some of our trained models can be found at [Huggingface](https://huggingface.co/
 
 ## Citation
    ```bash
-TBD
+@inproceedings{ye2026wrong,
+  title={What's Wrong with Synthetic Data for Scene Text Recognition? A Strong Synthetic Engine with Diverse Simulations and Self-Evolution},
+  author={Ye, Xingsong and Du, Yongkun and Zhang, JiaXin and Li, Chen and LYU, Jing and Chen, Zhineng},
+  booktitle={CVPR},
+  year={2026}
+}
    ```
 
 ## License