diff --git a/README_CN.md b/README_CN.md
index bcbd4a83cc..7ddb91fd2a 100644
--- a/README_CN.md
+++ b/README_CN.md
@@ -21,11 +21,13 @@
 </div>
 
 ## <img src="./docs/images/seg_news_icon.png" width="20"/> 最新动态
-* [2023-02-27] :fire:  PaddleSeg集成高性能、全场景模型部署方案FastDeploy，欢迎参考[指南](./deploy/fastdeploy)试用（注意切换成develop分支）。
-* [2022-11-30] :fire:  PaddleSeg 2.7版本发布！详细发版信息请参考[Release Note](https://github.com/PaddlePaddle/PaddleSeg/releases)。
-  * 发布实时人像抠图模型[PP-MattingV2](./Matting/)：推理速度提升44.6%，平均误差减小17.91%，完美超越此前SOTA模型，支持零成本开箱即用。
-  * 发布3D医疗影像分割方案[MedicalSegV2](./contrib/MedicalSeg/)：涵盖3D医疗影像交互式标注工具EISeg-Med3D、3个高精分割模型，集成并优化前沿分割方案nnUNet-D。
-  * 官方发布轻量级语义分割模型[RTFormer](./configs/rtformer/)：由百度提出并发表于NeurIPS 2022，在公开数据集上实现SOTA性能。
+
+* [2023-04-11] :fire:  PaddleSeg 2.8版本发布！详细发版信息请参考[Release Note](https://github.com/PaddlePaddle/PaddleSeg/releases)。
+  * 开源飞桨版本视觉大模型[Segment Anything Model](./contrib/SegmentAnything)，提供演示Demo，支持全图分割的功能、使用提示输入分割的功能。
+  * 发布超轻量级语义分割SOTA模型[PP-MobileSeg](./configs/pp_mobileseg)：在ADE20K数据集上，PP-MobileSeg对比此前最优模型，精度提升1.5%、速度提升42.3%、参数量减少34.9%。
+  * 发布工业质检全流程解决方案[QualityInspector v0.5](./contrib/QualityInspector)：提供统一可配置的算法Pipeline，集成检测和分割模型库，支持3种无监督异常检测算法，支持工业级指标评测、分析、调优等功能。
+  * 发布通用的全景分割解决方案[PanopticSeg v0.5](./contrib/PanopticSeg)：提供全景分割的全流程开发功能，集成2个前沿高精模型，具备灵活的二次开发能力。
+* [2022-11-30] PaddleSeg 2.7版本发布实时人像抠图模型[PP-MattingV2](./Matting/)、3D医疗影像分割方案[MedicalSegV2](./contrib/MedicalSeg/)、轻量级语义分割模型[RTFormer](./configs/rtformer/)。
 * [2022-07-20] PaddleSeg 2.6版本发布实时人像分割SOTA方案[PP-HumanSegV2](./contrib/PP-HumanSeg)、高性能智能标注工具[EISeg v1.0](./EISeg)正式版、ImageNet分割伪标签数据预训练方法PSSL，开源PP-MattingV1代码和预训练模型。
 * [2022-04-20] PaddleSeg 2.5版本发布超轻量级语义分割模型[PP-LiteSeg](./configs/pp_liteseg)，高精度抠图模型PP-MattingV1，3D医疗影像开发套件MedicalSegV1，交互式分割工具EISeg v0.5。
 * [2022-01-20] PaddleSeg 2.4版本发布交互式分割工具EISeg v0.4，超轻量级人像分割方案PP-HumanSegV1，以及大规模视频会议数据集[PP-HumanSeg14K](./contrib/PP-HumanSeg/paper.md#pp-humanseg14k-a-large-scale-teleconferencing-video-dataset)。
@@ -89,6 +91,7 @@
         <details><summary><b>语义分割模型</b></summary>
           <ul>
             <li><a href="./configs/pp_liteseg">PP-LiteSeg</a> </li>
+            <li><a href="./configs/pp_mobileseg">PP-MobileSeg</a> </li>
             <li><a href="./configs/deeplabv3p">DeepLabV3P</a> </li>
             <li><a href="./configs/ocrnet">OCRNet</a> </li>
             <li><a href="./configs/mobileseg">MobileSeg</a> </li>
diff --git a/README_EN.md b/README_EN.md
index d4e1412e6a..aaeabc9004 100644
--- a/README_EN.md
+++ b/README_EN.md
@@ -23,12 +23,14 @@ English | [简体中文](README_CN.md)
 
 ## <img src="./docs/images/seg_news_icon.png" width="20"/> News
 <ul class="nobull">
-  <li>[2022-11-30] :fire: PaddleSeg v2.7 is released! Check more details in <a href="https://github.com/PaddlePaddle/PaddleSeg/releases">Release Notes</a>.</li>
+  <li>[2023-04-11] :fire: PaddleSeg v2.8 is released! Check more details in <a href="https://github.com/PaddlePaddle/PaddleSeg/releases">Release Notes</a>.</li>
     <ul>
-        <li>Release <a href="./Matting/">PP-MattingV2</a>, a real-time human matting model with SOTA performance. Compared to previous models, the mean error is reduced by 17.91%, the inference speed is improved by 44.6% on GPU. </li>
-        <li>Release <a href="./contrib/MedicalSeg/">MedicalSegV2</a>, a superior 3D medical image segmentation solution, including an intelligent annotation toolkit called EISeg-Med3D, several state-of-the-art models, and an optimized nnUNet-D with high performance.</li>
-        <li>Release <a href="./configs/rtformer/">RTFormer</a>, a real-time semantic segmentation model (the paper has been accepted by NeurIPS 2022). RTFormer combines the advantages of CNN and Transformer modules, and it achieves SOTA trade-off between performance and efficiency on several datasets.</li>
+        <li>Release <a href="./contrib/SegmentAnything">Segment Anything Model</a> based on PaddlePaddle. Demos are provided to demonstrate the function of automatic full-image segmentation and specified object segmentation with prompt input.</li>
+        <li>Release <a href="./configs/pp_mobileseg">PP-MobileSeg</a>, a lightweight semantic segmentation model for mobile devices. Comparing PP-MobileSeg with other models on the ADE20K dataset, the segmentation accuracy is improved by 1.5%, the inference speed is accelerated by 42.3%, and the number of parameters is decreased by 34.9%. </li>
+        <li>Release <a href="./contrib/QualityInspector">QualityInspector v0.5</a>, a full-process solution for industrial quality inspection. It provides a unified and configurable pipeline for single-task and multi-task models, integrates detection and segmentation model libraries, and supports three unsupervised quality inspection methods. </li>
+        <li>Release <a href="./contrib/PanopticSeg">PanopticSeg v0.5</a>, a universal panoptic segmentation solution. It provides the full-process capabilities of panoptic segmentation, integrates two models, and has flexible secondary development capabilities. </li>
     </ul>
+  <li>[2022-11-30] PaddleSeg v2.7 released a real-time human matting model <a href="./Matting/">PP-MattingV2</a>, a 3D medical image segmentation solution <a href="./contrib/MedicalSeg/">MedicalSegV2</a>, and a real-time semantic segmentation model <a href="./configs/rtformer/">RTFormer</a>.
   <li>[2022-07-20] PaddleSeg v2.6 released a real-time human segmentation SOTA solution <a href="./contrib/PP-HumanSeg">PP-HumanSegV2</a>, a stable-version semi-automatic segmentation annotation tool <a href="./EISeg">EISeg v1.0</a>, a pseudo label pre-training method PSSL, and the source code of PP-MattingV1. </li>
   <li>[2022-04-20] PaddleSeg v2.5 released a real-time semantic segmentation model <a href="./configs/pp_liteseg">PP-LiteSeg</a>, a trimap-free image matting model PP-MattingV1, and an easy-to-use solution for 3D medical image segmentation MedicalSegV1.</li>
   <li>[2022-01-20] We release PaddleSeg v2.4 with EISeg v0.4, and PP-HumanSegV1 including an open-sourced dataset <a href="./contrib/PP-HumanSeg/paper.md#pp-humanseg14k-a-large-scale-teleconferencing-video-dataset">PP-HumanSeg14K</a>. </li>