Update readme & changlog (#4395)

* update README for release/2.3

README_cn.md

@@ -2,29 +2,26 @@
 
 # PaddleDetection
 
-### PaddleDetection 2.0全面升级！目前默认使用动态图版本，静态图版本位于[static](./static)中
-### 全新发布[关键点检测](configs/keypoint)和[多目标跟踪](configs/mot)能力！欢迎使用
-### 超高性价比PPYOLO v2和1.3M超轻量PPYOLO tiny全新出炉！[欢迎使用](configs/ppyolo/README_cn.md)
-### Anchor Free SOTA模型PAFNet发布！[欢迎使用](configs/ttfnet/README.md)
-
+# 产品动态
+- 2021.11.03: 发布[release/2.3版本](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3)，发布**轻量级检测特色模型**⚡[PP-PicoDet](configs/picodet)，发布**轻量级关键点特色模型**⚡[PP-TinyPose](configs/keypoint/tiny_pose)。新增[Swin Transformer](configs/faster_rcnn)，[TOOD](configs/tood)，[GFL](configs/gfl)目标检测模型。发布[Sniper](configs/sniper)小目标检测优化模型，发布针对EdgeBoard优化[PP-YOLO-EB](configs/ppyolo)模型。新增轻量化关键点模型[Lite HRNet](configs/keypoint)关键点模型并支持Paddle Lite部署。
+- 2021.08.10: 发布[release/2.2版本]((https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2))，发布Transformer检测系列模型，包括[DETR](configs/detr), [Deformable DETR](configs/deformable_detr), [Sparse RCNN](configs/sparse_rcnn)。新增Dark HRNet关键点模型和MPII数据集[关键点模型](configs/keypoint)，新增[人头](configs/mot/headtracking21)、[车辆](configs/mot/vehicle)跟踪垂类模型。
+- 2021.05.20: 发布[release/2.1版本](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1)，新增[关键点检测](configs/keypoint)，模型包括HigherHRNet，HRNet。新增[多目标跟踪](configs/mot)能力，模型包括DeepSORT，JDE，FairMOT。发布PPYOLO系列模型压缩模型，新增[ONNX模型导出教程](deploy/EXPORT_ONNX_MODEL.md)。
 
 # 简介
 
-PaddleDetection飞桨目标检测开发套件，旨在帮助开发者更快更好地完成检测模型的组建、训练、优化及部署等全开发流程。
-
-PaddleDetection模块化地实现了多种主流目标检测算法，提供了丰富的数据增强策略、网络模块组件（如骨干网络）、损失函数等，并集成了模型压缩和跨平台高性能部署能力。
+PaddleDetection为基于飞桨PaddlePaddle的端到端目标检测套件，提供多种主流目标检测、实例分割、跟踪、关键点检测算法，配置化的网络模块组件、数据增强策略、损失函数等，推出多种服务器端和移动端工业级SOTA模型，并集成了模型压缩和跨平台高性能部署能力,帮助开发者更快更好完成端到端全开发流程。
 
-经过长时间产业实践打磨，PaddleDetection已拥有顺畅、卓越的使用体验，被工业质检、遥感图像检测、无人巡检、新零售、互联网、科研等十多个行业的开发者广泛应用。
+### PaddleDetection提供了目标检测、实例分割、多目标跟踪、关键点检测等多种能力
 
-<div align="center">
-  <img src="static/docs/images/football.gif" width='800'/>
-  <img src="docs/images/mot_pose_demo_640x360.gif" width='800'/>
+<div width="900" align="center">
+  <img src="docs/images/det.jpg" width="400" height="300" title="目标检测"/>
+  <img src="docs/images/ins.jpg" width="400" height="300" title="实例分割"/>
+</div>
+<div width="900" align="center">
+  <img src="docs/images/mot.gif" width="400" height="300" title="多目标跟踪"/>
+  <img src="docs/images/pose.gif" width="400" height="300" title="关键点检测"/>
 </div>
 
-### 产品动态
-- 2021.05.20: 发布release/2.1版本，新增[关键点检测](configs/keypoint)，模型包括HigherHRNet，HRNet。新增[多目标跟踪](configs/mot)能力，模型包括DeepSORT，JDE，FairMOT。发布PPYOLO系列模型压缩模型，新增[ONNX模型导出教程](deploy/EXPORT_ONNX_MODEL.md)，详情参考[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1)
-- 2021.04.14: 发布release/2.0版本，PaddleDetection全面支持动态图，覆盖静态图模型算法，全面升级模型效果，同时发布[PP-YOLO v2, PPYOLO tiny](configs/ppyolo/README_cn.md)模型，增强版anchor free模型[PAFNet](configs/ttfnet/README.md)，新增旋转框检测[S2ANet](configs/dota/README.md)模型，详情参考[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0)
-- 2021.02.07: 发布release/2.0-rc版本，PaddleDetection动态图试用版本，详情参考[PaddleDetection动态图](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0-rc)。
 
 ### 特性
 

README_en.md

 English | [简体中文](README_cn.md)
 
-### PaddleDetection 2.0 is ready! Dygraph mode is set by default and static graph code base is [here](static)
 
-### [Keypoint detection](configs/keypoint) and [Multi-Object Tracking](configs/mot) are released!
+# Product news
 
-### Highly effective PPYOLO v2 and ultra lightweight PPYOLO tiny are released! [link](configs/ppyolo/README.md)
+- 2021.11.03: Release [release/2.3]((https://github.com/PaddlePaddle/Paddleetection/tree/release/2.3) version. Release mobile object detection model ⚡[PP-PicoDet](configs/picodet), mobile keypoint detection model ⚡[PP-TinyPose](configs/keypoint/tiny_pose). Release object detection models, including [Swin-Transformer](configs/faster_rcnn), [TOOD](configs/tood), [GFL](configs/gfl), release [Sniper](configs/sniper) tiny object detection models and optimized [PP-YOLO-EB](configs/ppyolo) model for EdgeBoard. Release mobile keypoint detection model [Lite HRNet](configs/keypoint).
+- 2021.08.10: Release [release/2.2]((https://github.com/PaddlePaddle/Paddleetection/tree/release/2.2) version. Release Transformer object detection models, including [DETR](configs/detr), [Deformable DETR](configs/deformable_detr), [Sparse RCNN](configs/sparse_rcnn). Release [keypoint detection](configs/keypoint) models, including DarkHRNet and model trained on MPII dataset. Release [head-tracking](configs/mot/headtracking21) and [vehicle-tracking](configs/mot/vehicle) multi-object tracking models.
+- 2021.05.20: Release [release/2.1]((https://github.com/PaddlePaddle/Paddleetection/tree/release/2.1) version. Release [Keypoint Detection](configs/keypoint), including HigherHRNet and HRNet, [Multi-Object Tracking](configs/mot), including DeepSORT，JDE and FairMOT. Release model compression for PPYOLO series models.Update documents such as [EXPORT ONNX MODEL](deploy/EXPORT_ONNX_MODEL.md).
 
-### SOTA Anchor Free model -- PAFNet is released! [link](configs/ttfnet/README.md)
 
 # Introduction
 
-PaddleDetection is an end-to-end object detection development kit based on PaddlePaddle, which aims to help developers in the whole development of constructing, training, optimizing and deploying detection models in a faster and better way.
+PaddleDetection is an end-to-end object detection development kit based on PaddlePaddle, which implements varied mainstream object detection, instance segmentation, tracking and keypoint detection algorithms in modular designwhich with configurable modules such as network components, data augmentations and losses, and release many kinds SOTA industry practice models, integrates abilities of model compression and cross-platform high-performance deployment, aims to help developers in the whole end-to-end development in a faster and better way.
 
-PaddleDetection implements varied mainstream object detection algorithms in modular design, and provides wealthy data augmentation methods, network components(such as backbones), loss functions, etc., and integrates abilities of model compression and cross-platform high-performance deployment.
+### PaddleDetection provides image processing capabilities such as object detection, instance segmentation, multi-object tracking, keypoint detection and etc.
 
-After a long time of industry practice polishing, PaddleDetection has had smooth and excellent user experience, it has been widely used by developers in more than ten industries such as industrial quality inspection, remote sensing image object detection, automatic inspection, new retail, Internet, and scientific research.
-
-<div align="center">
-  <img src="static/docs/images/football.gif" width='800'/>
-  <img src="docs/images/mot_pose_demo_640x360.gif" width='800'/>
+<div width="900" align="center">
+  <img src="docs/images/det.jpg" width="400" height="300" title="目标检测"/>
+  <img src="docs/images/ins.jpg" width="400" height="300" title="实例分割"/>
+</div>
+<div width="900" align="center">
+  <img src="docs/images/mot.gif" width="400" height="300" title="多目标跟踪"/>
+  <img src="docs/images/pose.gif" width="400" height="300" title="关键点检测"/>
 </div>
-
-### Product news
-
-- 2021.05.20: Release `release/2.1` version. Release [Keypoint Detection](configs/keypoint), including HigherHRNet and HRNet, [Multi-Object Tracking](configs/mot), including DeepSORT，JDE and FairMOT. Release model compression for PPYOLO series models.Update documents such as [EXPORT ONNX MODEL](deploy/EXPORT_ONNX_MODEL.md). Please refer to [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1) for details.
-- 2021.04.14: Release `release/2.0` version. Dygraph mode in PaddleDetection is fully supported. Cover all the algorithm of static graph and update the performance of mainstream detection models. Release [`PP-YOLO v2` and `PP-YOLO tiny`](configs/ppyolo/README.md), enhanced anchor free model [PAFNet](configs/ttfnet/README.md) and [`S2ANet`](configs/dota/README.md) which is aimed at rotation object detection.Please refer to [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0) for details.
-- 2020.02.07: Release `release/2.0-rc` version, Please refer to [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0-rc) for details.
 
 
 ### Features

docs/CHANGELOG.md

@@ -2,6 +2,36 @@
 
 ## 最新版本信息
 
+### 2.3(11.03/2021)
+
+- 特色模型:
+  - 检测: 轻量级移动端检测模型PP-PicoDet，精度速度达到移动端SOTA
+  - 关键点: 轻量级移动端关键点模型PP-TinyPose
+
+- 模型丰富度:
+  - 检测：
+    - 新增Swin-Transformer目标检测模型
+    - 新增TOOD(Task-aligned One-stage Object Detection)模型
+    - 新增GFL(Generalized Focal Loss)目标检测模型
+    - 发布Sniper小目标检测优化方法，支持Faster RCNN及PP-YOLO系列模型
+    - 发布针对EdgeBoard优化的PP-YOLO-EB模型
+
+  - 跟踪
+    - 发布fairmot 高精度模型、小尺度模型和轻量级模型
+    - 发布行人、人头和车辆实跟踪垂类模型库，覆盖航拍监控、自动驾驶、密集人群、极小目标等场景
+    - DeepSORT模型适配PP-YOLO, PP-PicoDet等更多检测器
+
+  - 关键点
+    - 新增Lite HRNet模型
+
+- 预测部署:
+  - YOLOv3系列模型支持NPU预测部署
+  - FairMot模型C++预测部署打通
+  - 关键点系列模型C++预测部署打通, Paddle Lite预测部署打通
+
+- 文档:
+  - 新增各系列模型英文文档
+
 ### 2.2(08.10/2021)
 
 - 模型丰富度：