diff --git a/deploy/pphuman/README.md b/deploy/pphuman/README.md
index af61b3a253670dbe3a03b7b2ebeb54b5b9668946..ee37c9ad9c4c8abe833c72696d21fb470a1e01c8 100644
--- a/deploy/pphuman/README.md
+++ b/deploy/pphuman/README.md
@@ -44,7 +44,7 @@ PP-Human提供了目标检测、属性识别、行为识别、ReID预训练模
 | 属性识别    | 图片/视频输入 属性识别  | mA: 94.86 |  单人2ms     | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/strongbaseline_r50_30e_pa100k.zip) |
 | 关键点检测    | 视频输入 行为识别 | AP: 87.1 | 单人2.9ms        | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip)
 | 行为识别   |  视频输入 行为识别  | 准确率: 96.43 |  单人2.7ms      | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/STGCN.zip) |
-| ReID         | 视频输入 跨镜跟踪   | mAP: 99.7 | -        | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip) |
+| ReID         | 视频输入 跨镜跟踪   | mAP: 98.8 | 单人1.5ms        | [下载链接](https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip) |
 
 下载模型后，解压至`./output_inference`文件夹
 
diff --git a/deploy/pphuman/README_en.md b/deploy/pphuman/README_en.md
index 44c6f78632ab6966b6c38f003e0657e499f87c87..47f0f9df9e56a8a7a546b6fbc97576621541f0c2 100644
--- a/deploy/pphuman/README_en.md
+++ b/deploy/pphuman/README_en.md
@@ -42,7 +42,7 @@ To make users have access to models of different scenarios, PP-Human provides pr
 | Attribute Recognition    | Image/Video Input  Attribute Recognition | MOTA: 72.0 |  33.1ms       | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/strongbaseline_r50_30e_pa100k.zip) |
 | Keypoint Detection    | Video Input  Action Recognition | mA: 94.86 | 2ms per person        | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip)
 | Behavior Recognition   |  Video Input  Bheavior Recognition  | Precision 96.43 |  2.7ms per person          | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/STGCN.zip) |
-| ReID         | Multi-Target Multi-Camera Tracking   | mAP: 99.7 | -        | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip) |
+| ReID         | Multi-Target Multi-Camera Tracking   | mAP: 98.8 | 1.5ms per person    | [Link](https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip) |
 
 Then, unzip the downloaded model to the folder `./output_inference`.