From 25820aae43216fbb1ed94d520641470cd62fba9a Mon Sep 17 00:00:00 2001
From: Topdu <784990967@qq.com>
Date: Tue, 3 May 2022 06:58:42 +0000
Subject: [PATCH] [doc] add svtr cite link

---
 doc/doc_ch/algorithm_rec_svtr.md    | 15 ++++++++++++++-
 doc/doc_en/algorithm_rec_svtr_en.md | 14 +++++++++++++-
 2 files changed, 27 insertions(+), 2 deletions(-)

diff --git a/doc/doc_ch/algorithm_rec_svtr.md b/doc/doc_ch/algorithm_rec_svtr.md
index c914784a..325a2076 100644
--- a/doc/doc_ch/algorithm_rec_svtr.md
+++ b/doc/doc_ch/algorithm_rec_svtr.md
@@ -17,7 +17,7 @@
 ## 1. 算法简介
 
 论文信息：
-> [SVTR: Scene Text Recognition with a Single Visual Model]()
+> [SVTR: Scene Text Recognition with a Single Visual Model](https://arxiv.org/abs/2205.00159)
 > Yongkun Du and Zhineng Chen and Caiyan Jia Xiaoting Yin and Tianlun Zheng and Chenxia Li and Yuning Du and Yu-Gang Jiang
 > IJCAI, 2022
 
@@ -159,3 +159,16 @@ Predicts of ./doc/imgs_words_en/word_10.png:('pain', 0.9999998807907104)
 ## 5. FAQ
 
 1. 由于`SVTR`使用的算子大多为矩阵相乘，在GPU环境下，速度具有优势，但在CPU开启mkldnn加速环境下，`SVTR`相比于被优化的卷积网络没有优势。
+
+
+## 引用
+
+```bibtex
+@article{Du2022SVTR,
+  author = {Du, Yongkun and Chen, Zhineng and Jia, Caiyan and Yin, Xiaoting and Zheng, Tianlun and Li, Chenxia and Du, Yuning and Jiang, Yu-Gang},
+  title = {SVTR: Scene Text Recognition with a Single Visual Model},
+  publisher = {IJCAI},
+  year = {2022},
+  url = {https://arxiv.org/abs/2205.00159}
+}
+```
diff --git a/doc/doc_en/algorithm_rec_svtr_en.md b/doc/doc_en/algorithm_rec_svtr_en.md
index 46d10450..f7e215ff 100644
--- a/doc/doc_en/algorithm_rec_svtr_en.md
+++ b/doc/doc_en/algorithm_rec_svtr_en.md
@@ -17,7 +17,7 @@
 ## 1. Introduction
 
 Paper:
-> [SVTR: Scene Text Recognition with a Single Visual Model]()
+> [SVTR: Scene Text Recognition with a Single Visual Model](https://arxiv.org/abs/2205.00159)
 > Yongkun Du and Zhineng Chen and Caiyan Jia Xiaoting Yin and Tianlun Zheng and Chenxia Li and Yuning Du and Yu-Gang Jiang
 > IJCAI, 2022
 
@@ -131,3 +131,15 @@ Not supported
 ## 5. FAQ
 
 1. Since most of the op operators used by `SVTR` are matrix multiplication, in the GPU environment, the speed has an advantage, but in the environment where mkldnn is enabled on the CPU, `SVTR` has no advantage over the optimized convolutional network.
+
+## Citation
+
+```bibtex
+@article{Du2022SVTR,
+  author = {Du, Yongkun and Chen, Zhineng and Jia, Caiyan and Yin, Xiaoting and Zheng, Tianlun and Li, Chenxia and Du, Yuning and Jiang, Yu-Gang},
+  title = {SVTR: Scene Text Recognition with a Single Visual Model},
+  publisher = {IJCAI},
+  year = {2022},
+  url = {https://arxiv.org/abs/2205.00159}
+}
+```
-- 
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