diff --git a/README.md b/README.md
index 0a0d640cbd..b673fef90f 100644
--- a/README.md
+++ b/README.md
@@ -123,6 +123,48 @@ https://user-images.githubusercontent.com/15977946/124654387-0fd3c500-ded1-11eb-
Please refer to the [release notes](https://github.com/open-mmlab/mmpose/releases/tag/v1.0.0) for more updates brought by MMPose v1.0.0!
+## 0.x -> 1.x 迁移进度
+
+MMPose v1.0.0 is a major update, including many API and config file changes. Currently, a part of the algorithms have been migrated to v1.0.0, and the remaining algorithms will be completed in subsequent versions. We will show the migration progress in the following list.
+
+
+Migration Progress
+
+| Algorithm | Status |
+| :--- | :---: |
+| MTUT (CVPR 2019) | |
+| MSPN (ArXiv 2019)| done |
+| InterNet (ECCV 2020) | |
+| DEKR (CVPR 2021) | done |
+| HigherHRNet (CVPR 2020) | |
+| DeepPose (CVPR 2014) | done |
+| RLE (ICCV 2021) | done |
+| SoftWingloss (TIP 2021) | |
+| VideoPose3D (CVPR 2019) | |
+| Hourglass (ECCV 2016) | done |
+| LiteHRNet (CVPR 2021) | done |
+| AdaptiveWingloss (ICCV 2019) | done |
+| SimpleBaseline2D (ECCV 2018) | done |
+| PoseWarper (NeurIPS 2019) | |
+| SimpleBaseline3D (ICCV 2017) | |
+| HMR (CVPR 2018) | |
+| UDP (CVPR 2020) | done |
+| VIPNAS (CVPR 2021) | done |
+| Wingloss (CVPR 2018) | |
+| DarkPose (CVPR 2020) | done |
+| Associative Embedding (NIPS 2017) | in progress |
+| VoxelPose (ECCV 2020) | |
+| RSN (ECCV 2020) | done |
+| CID (CVPR 2022) | done |
+| CPM (CVPR 2016) | done |
+| HRNet (CVPR 2019) | done |
+| HRNetv2 (TPAMI 2019) | done |
+| SCNet (CVPR 2020) | done |
+
+
+
+If your algorithm has not been migrated, you can continue to use the [0.x branch](https://github.com/open-mmlab/mmpose/tree/0.x) and [old documentation](https://mmpose.readthedocs.io/en/0.x/).
+
## Installation
Please refer to [installation.md](https://mmpose.readthedocs.io/en/latest/installation.html) for more detailed installation and dataset preparation.
diff --git a/README_CN.md b/README_CN.md
index c1c4898ca2..7e28ced6e6 100644
--- a/README_CN.md
+++ b/README_CN.md
@@ -121,6 +121,47 @@ https://user-images.githubusercontent.com/15977946/124654387-0fd3c500-ded1-11eb-
请查看完整的 [版本说明](https://github.com/open-mmlab/mmpose/releases/tag/v1.0.0) 以了解更多 MMPose v1.0.0 带来的更新!
+## 0.x / 1.x 迁移
+
+MMPose v1.0.0 是一个重大更新，包括了大量的 API 和配置文件的变化。目前 v1.0.0 中已经完成了一部分算法的迁移工作，剩余的算法将在后续的版本中陆续完成，我们将在下面的列表中展示迁移进度。
+
+
+迁移进度
+
+| 算法名称 | 迁移进度 |
+| :--- | :---: |
+| MTUT (CVPR 2019) | |
+| MSPN (ArXiv 2019)| done |
+| InterNet (ECCV 2020) | |
+| DEKR (CVPR 2021) | done |
+| HigherHRNet (CVPR 2020) | |
+| DeepPose (CVPR 2014) | done |
+| RLE (ICCV 2021) | done |
+| SoftWingloss (TIP 2021) | |
+| VideoPose3D (CVPR 2019) | |
+| Hourglass (ECCV 2016) | done |
+| LiteHRNet (CVPR 2021) | done |
+| AdaptiveWingloss (ICCV 2019) | done |
+| SimpleBaseline2D (ECCV 2018) | done |
+| PoseWarper (NeurIPS 2019) | |
+| SimpleBaseline3D (ICCV 2017) | |
+| HMR (CVPR 2018) | |
+| UDP (CVPR 2020) | done |
+| VIPNAS (CVPR 2021) | done |
+| Wingloss (CVPR 2018) | |
+| DarkPose (CVPR 2020) | done |
+| Associative Embedding (NIPS 2017) | in progress |
+| VoxelPose (ECCV 2020) | |
+| RSN (ECCV 2020) | done |
+| CID (CVPR 2022) | done |
+| CPM (CVPR 2016) | done |
+| HRNet (CVPR 2019) | done |
+| HRNetv2 (TPAMI 2019) | done |
+| SCNet (CVPR 2020) | done |
+
+
+
+如果您使用的算法还没有完成迁移，您也可以继续使用访问 [0.x 分支](https://github.com/open-mmlab/mmpose/tree/0.x) 和 [旧版文档](https://mmpose.readthedocs.io/zh_CN/0.x/)
## 安装
关于安装的详细说明请参考[安装文档](https://mmpose.readthedocs.io/zh_CN/latest/installation.html)。
@@ -321,8 +362,7 @@ MMPose 是一款由不同学校和公司共同贡献的开源项目。我们感
扫描下方的二维码可关注 OpenMMLab 团队的 [知乎官方账号](https://www.zhihu.com/people/openmmlab)，联络 OpenMMLab [官方微信小助手](https://user-images.githubusercontent.com/25839884/205872898-e2e6009d-c6bb-4d27-8d07-117e697a3da8.jpg)或加入 OpenMMLab 团队的 [官方交流 QQ 群](https://jq.qq.com/?_wv=1027&k=K0QI8ByU)
我们会在 OpenMMLab 社区为大家
diff --git a/docs/en/installation.md b/docs/en/installation.md
index 0f8707b77d..dc4a0ab386 100644
--- a/docs/en/installation.md
+++ b/docs/en/installation.md
@@ -59,13 +59,13 @@ conda install pytorch torchvision cpuonly -c pytorch
```shell
pip install -U openmim
mim install mmengine
-mim install "mmcv>=2.0.0rc4"
+mim install "mmcv>=2.0.0"
```
Note that some of the demo scripts in MMPose require [MMDetection](https://github.com/open-mmlab/mmdetection) (mmdet) for human detection. If you want to run these demo scripts with mmdet, you can easily install mmdet as a dependency by running:
```shell
-mim install "mmdet>=3.0.0rc6"
+mim install "mmdet>=3.0.0"
```
## Best Practices
@@ -89,7 +89,7 @@ pip install -v -e .
To use mmpose as a dependency or third-party package, install it with pip:
```shell
-mim install "mmpose>=1.0.0rc1"
+mim install "mmpose>=1.0.0"
```
## Verify the installation
@@ -173,7 +173,7 @@ To install MMCV with pip instead of MIM, please follow [MMCV installation guides
For example, the following command install mmcv built for PyTorch 1.10.x and CUDA 11.3.
```shell
-pip install 'mmcv>=2.0.0rc1' -f https://download.openmmlab.com/mmcv/dist/cu113/torch1.10/index.html
+pip install 'mmcv>=2.0.0' -f https://download.openmmlab.com/mmcv/dist/cu113/torch1.10/index.html
```
### Install on CPU-only platforms
@@ -192,7 +192,7 @@ thus we only need to install MMEngine, MMCV and MMPose with the following comman
```shell
!pip3 install openmim
!mim install mmengine
-!mim install "mmcv>=2.0.0rc1"
+!mim install "mmcv>=2.0.0"
```
**Step 2.** Install MMPose from the source.
@@ -208,7 +208,7 @@ thus we only need to install MMEngine, MMCV and MMPose with the following comman
```python
import mmpose
print(mmpose.__version__)
-# Example output: 1.0.0rc0
+# Example output: 1.0.0
```
```{note}
diff --git a/docs/zh_cn/installation.md b/docs/zh_cn/installation.md
index e0917a2e3c..1ec42fe78a 100644
--- a/docs/zh_cn/installation.md
+++ b/docs/zh_cn/installation.md
@@ -57,13 +57,13 @@ conda install pytorch torchvision cpuonly -c pytorch
```shell
pip install -U openmim
mim install mmengine
-mim install "mmcv>=2.0.0rc1"
+mim install "mmcv>=2.0.0"
```
请注意，MMPose 中的一些推理示例脚本需要使用 [MMDetection](https://github.com/open-mmlab/mmdetection) (mmdet) 检测人体。如果您想运行这些示例脚本，可以通过运行以下命令安装 mmdet:
```shell
-mim install "mmdet>=3.0.0rc0"
+mim install "mmdet>=3.0.0"
```
## 最佳实践
@@ -88,7 +88,7 @@ pip install -v -e .
如果只是希望调用 MMPose 的接口，或者在自己的项目中导入 MMPose 中的模块。直接使用 mim 安装即可。
```shell
-mim install "mmpose>=1.0.0rc0"
+mim install "mmpose>=1.0.0"
```
## 验证安装
@@ -180,7 +180,7 @@ MMCV 包含 C++ 和 CUDA 扩展，因此其对 PyTorch 的依赖比较复杂。M
举个例子，如下命令将会安装基于 PyTorch 1.10.x 和 CUDA 11.3 编译的 mmcv。
```shell
-pip install 'mmcv>=2.0.0rc1' -f https://download.openmmlab.com/mmcv/dist/cu113/torch1.10/index.html
+pip install 'mmcv>=2.0.0' -f https://download.openmmlab.com/mmcv/dist/cu113/torch1.10/index.html
```
### 在 CPU 环境中安装
@@ -198,7 +198,7 @@ MMPose 可以仅在 CPU 环境中安装，在 CPU 模式下，您可以完成训
```shell
!pip3 install openmim
!mim install mmengine
-!mim install "mmcv>=2.0.0rc1"
+!mim install "mmcv>=2.0.0"
```
**第 2 步** 从源码安装 mmpose
@@ -214,7 +214,7 @@ MMPose 可以仅在 CPU 环境中安装，在 CPU 模式下，您可以完成训
```python
import mmpose
print(mmpose.__version__)
-# 预期输出： 1.0.0rc0
+# 预期输出： 1.0.0
```
```{note}
+