Merge pull request luanshiyinyang#11 from Yulv-git/patch-1

Add code for TransCenter, GSDT, etc.

Author: luanshiyinyang

README-zh.md

@@ -126,7 +126,7 @@ Simple Cues Lead to a Strong Multi-Object Tracker [[code]()] [[paper](https://ar
 
 **TransMOT**：Spatial-Temporal Graph Transformer for Multiple Object Tracking [code] [[paper](https://arxiv.org/pdf/2104.00194v2.pdf)]
 
-**TransCenter**: TransCenter: Transformers with Dense Queries for Multiple-Object Tracking [code] [[paper](https://arxiv.org/pdf/2103.15145.pdf)]
+**TransCenter**: TransCenter: Transformers with Dense Queries for Multiple-Object Tracking [[code](https://github.com/yihongXU/TransCenter)] [[paper](https://arxiv.org/pdf/2103.15145.pdf)]
 
 **GCNet**: Global Correlation Network: End-to-End Joint Multi-Object Detection and Tracking [code] [[paper](https://arxiv.org/pdf/2103.12511.pdf)]
 
@@ -147,7 +147,7 @@ Simple Cues Lead to a Strong Multi-Object Tracker [[code]()] [[paper](https://ar
 
 **MLT**: Multiplex Labeling Graph for Near-Online Tracking in Crowded Scenes [[paper](https://ieeexplore.ieee.org/document/9098857)]
 
-**GSDT**: Joint Object Detection and Multi-Object Tracking with Graph Neural Networks [[paper](http://arxiv.org/pdf/2006.13164)]
+**GSDT**: Joint Object Detection and Multi-Object Tracking with Graph Neural Networks [[code](https://github.com/yongxinw/GSDT)] [[paper](http://arxiv.org/pdf/2006.13164)]
 
 **SMOT**: SMOT: Single-Shot Multi Object Tracking [[paper](http://arxiv.org/pdf/2010.16031)]
 
@@ -708,7 +708,7 @@ MOT领域大部分Benchmark都可以在MOT Challenge官网找到，下文的表
 
 **mmtracking**: OpenMMLab开发的视频感知工具箱，支持单目标跟踪、多目标跟踪和视频目标检测的统一框架。
 
-[Github地址](https://github.com/open-mmlab/mmtracking)  [官方文档](https://mmtracking.readthedocs.io/en/latest/)
+[Github地址](https://github.com/open-mmlab/mmtracking)  [官方文档](https://mmtracking.readthedocs.io/zh_CN/latest/)
 
 <a id="markdown-课程" name="课程"></a>
 ## 课程

README.md

@@ -109,7 +109,7 @@ Simple Cues Lead to a Strong Multi-Object Tracker [[code]()] [[paper](https://ar
 
 **TransMOT**：Spatial-Temporal Graph Transformer for Multiple Object Tracking [code] [[paper](https://arxiv.org/pdf/2104.00194v2.pdf)]
 
-**TransCenter**: TransCenter: Transformers with Dense Queries for Multiple-Object Tracking [code] [[paper](https://arxiv.org/pdf/2103.15145.pdf)]
+**TransCenter**: TransCenter: Transformers with Dense Queries for Multiple-Object Tracking [[code](https://github.com/yihongXU/TransCenter)] [[paper](https://arxiv.org/pdf/2103.15145.pdf)]
 
 **GCNet**: Global Correlation Network: End-to-End Joint Multi-Object Detection and Tracking [code] [[paper](https://arxiv.org/pdf/2103.12511.pdf)]
 
@@ -131,7 +131,7 @@ Simple Cues Lead to a Strong Multi-Object Tracker [[code]()] [[paper](https://ar
 
 **MLT**: Multiplex Labeling Graph for Near-Online Tracking in Crowded Scenes [[paper](https://ieeexplore.ieee.org/document/9098857)]
 
-**GSDT**: Joint Object Detection and Multi-Object Tracking with Graph Neural Networks [[paper](http://arxiv.org/pdf/2006.13164)]
+**GSDT**: Joint Object Detection and Multi-Object Tracking with Graph Neural Networks [[code](https://github.com/yongxinw/GSDT)] [[paper](http://arxiv.org/pdf/2006.13164)]
 
 **SMOT**: SMOT: Single-Shot Multi Object Tracking [[paper](http://arxiv.org/pdf/2010.16031)]