计算机组成原理

1. 本地部署ShareLatex

本地部署ShareLatex

假设从裸机Ubuntu开始

ssr

1. 操作系统

grep

Linux

参考资料

• 尚硅谷
• 笔记完整版(转载)
• https://docker.com
• https://docker-cn.com
• https://hub.docker.com/
• 阿里云

目标检测：

https://blog.csdn.net/electech6/article/details/95240278

RPN：

https://blog.csdn.net/shiheyingzhe/article/details/83713352

YOLO
https://blog.csdn.net/shuiyixin/article/details/82533849
https://luckmoonlight.github.io/2018/11/28/yoloV1yolov2yoloV3/

YOLO v2
https://blog.csdn.net/weixin_40092412/article/details/91547836

refinet
https://blog.csdn.net/zhangjunhit/article/details/72844862
https://github.com/DrSleep/refinenet-pytorch/blob/master/models/resnet.py

1. 前言

CVPR2019 看到好几篇都使用了 memory 的结构来进行 person re-id，所以对这几篇论文总结一下。具体的论文分析在我之前的博客已经有，这里主要介绍这几篇论文对 memory 的使用方法和效果。

• OIM: CVPR2017_Joint Detection and Identification Feature Learning for Person Search
• DIMN: CVPR2019_Generalizable Person Re-identification by Domain-Invariant Mapping Network
• MAR: CVPR2019 Unsupervised Person Re-identification by Soft Multilabel Learning
• ECN: CVPR2019_Invariance Matters Exemplar Memory for Domain Adaptive Person Re-identification

1. Introduction

• paper: CVPR2017_Joint Detection and Identification Feature Learning for Person Search
• code: caffe, [pytorch][https://github.com/Cysu/open-reid]
• project: End-to-End Deep Learning for Person Search
• memory: OIM, DIMN, MAR, ECN