[Doc]: introduce 3.x in 2.x readme (#8677)

* introduce 3.x in 2.x readme

* introduce 3.x in 2.x readme

* update

README.md

@@ -75,6 +75,8 @@ Apart from MMDetection, we also released a library [mmcv](https://github.com/ope
 
 ## What's New
 
+### 💎 Stable version
+
 **2.25.0** was released in 1/6/2022:
 
 - Support dedicated `MMDetWandbHook` hook
@@ -86,6 +88,18 @@ Please refer to [changelog.md](docs/en/changelog.md) for details and release his
 
 For compatibility changes between different versions of MMDetection, please refer to [compatibility.md](docs/en/compatibility.md).
 
+### 🌟 Preview of 3.x version
+
+A brand new version of **MMDetection v3.0.0rc0** was released in 31/8/2022:
+
+- Unifies interfaces of all components based on [MMEngine](https://github.com/open-mmlab/mmengine).
+- Faster training and testing speed with complete support of mixed precision training.
+- Refactored and more flexible [architecture](https://mmdetection.readthedocs.io/en/v3.0.0rc0/overview.html).
+- Provides more strong baselines and a general semi-supervised object detection framework. See [tutorial of semi-supervised detection](https://mmdetection.readthedocs.io/en/v3.0.0rc0/user_guides/semi_det.html).
+- Allows any kind of single-stage model as an RPN in a two-stage model. See [tutorial](https://mmdetection.readthedocs.io/en/v3.0.0rc0/user_guides/single_stage_as_rpn.html).
+
+Find more new features in [3.x branch](https://github.com/open-mmlab/mmdetection/tree/3.x). Issues and PRs are welcome!
+
 ## Installation
 
 Please refer to [Installation](docs/en/get_started.md/#Installation) for installation instructions.

README_zh-CN.md

@@ -74,6 +74,8 @@ MMDetection 是一个基于 PyTorch 的目标检测开源工具箱。它是 [Ope
 
 ## 最新进展
 
+### 💎 稳定版本
+
 最新的 **2.25.0** 版本已经在 2022.06.01 发布:
 
 - 支持功能更丰富的 `MMDetWandbHook`
@@ -85,6 +87,15 @@ MMDetection 是一个基于 PyTorch 的目标检测开源工具箱。它是 [Ope
 
 如果想了解 MMDetection 不同版本之间的兼容性, 请参考[兼容性说明文档](docs/zh_cn/compatibility.md)。
 
+### 🌟 3.x 预览版本
+
+全新的 **v3.0.0rc0** 版本已经在 2022.8.31 发布：
+
+- 基于 [MMEngine](https://github.com/open-mmlab/mmengine) 统一了各组件接口。
+- 全面支持混合精度，训练测试速度更快。
+- 提供了更强的基线模型，并支持了通用的半监督目标检测框架，详见[半监督目标检测教程](https://mmdetection.readthedocs.io/zh_CN/v3.0.0rc0/user_guides/semi_det.html)。
+- 支持使用任意单阶段检测器作为二阶段模型的 RPN，详见[教程](https://mmdetection.readthedocs.io/en/v3.0.0rc0/user_guides/single_stage_as_rpn.html)。
+
 ## 安装
 
 请参考[安装指令](docs/zh_cn/get_started.md/#Installation)进行安装。