参考文章：
资产一千万的人生活是什么样的？ - 知乎
https://www.zhihu.com/question/375479065/answer/1306396478
年薪百万是什么感觉？ - 知乎
https://www.zhihu.com/question/394637216/answer/1510752650
CVPR2020｜图像重建(超分辨率，图像恢复，去雨，去雾，去模糊，去噪等)相关论文汇总（附论文链接/开源代码/解析）【持续更新】 - Kobay - 博客园
https://www.cnblogs.com/kobaayyy/p/13163056.html
CVPR2020｜图像重建(超分辨率，图像恢复，去雨，去雾等)相关论文汇总（附论文链接/代码/解析）
https://zhuanlan.zhihu.com/p/149322505
CVPR2019 | 论文分类汇总（190611 更新） | 极市高质量视觉算法开发者社区
https://bbs.cvmart.net/topics/302/cvpr2019paper
CVPR2019 | 论文分类汇总
https://blog.csdn.net/happyday_d/article/details/100886456
CVPR 2020 全部论文 分类汇总和打包下载
https://blog.csdn.net/zhjm07054115/article/details/104788338
CVPR2020-深度图超分辨率DSR新方法| Channel Attention based Iterative Residual Learning for Depth Map SR
https://blog.csdn.net/weixin_42096202/article/details/106877635
CVPR 2020 论文大盘点-超分辨率篇
https://blog.csdn.net/moxibingdao/article/details/106726667
感知超分辨率, Challenge on Perceptual Image Restoration and Manipulation
https://github.com/roimehrez/PIRM2018
A Deep Journey into Super-resolution: A Survey, ACM Computing Surveys
https://github.com/saeed-anwar/SRsurvey
感知损失函数与感知超分
港中文-商汤联合实验室：ECCV2018 PIRM-SR 超分辨率比赛冠军：ESRGAN（已开源）
https://zhuanlan.zhihu.com/p/56385135
https://github.com/xinntao/ESRGAN
[解读] The relativistic discriminator: a key element missing from standard GAN, 感知生成对抗网络分辨器代码实现
https://blog.csdn.net/weipf8/article/details/106436583
Code for replication of the paper "The relativistic discriminator: a key element missing from standard GAN"
https://github.com/AlexiaJM/RelativisticGAN
LapSRN 超分辨率, Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
https://blog.csdn.net/wangkun1340378/article/details/74224356
https://github.com/phoenix104104/LapSRN
Small-Object Detection in Remote Sensing (satellite) Images, 端到端边缘增强GAN, 目标检测
https://github.com/Jakaria08/EESRGAN
SR图像上采样放大
PyTorch学习笔记(10)——上采样和PixelShuffle
https://blog.csdn.net/g11d111/article/details/82855946
PSNR与SSIM
图像的峰值信噪比（PSNR）的计算方法
https://blog.csdn.net/xrinosvip/article/details/88569111
SR数据集
超分辨率数据集集合
https://blog.csdn.net/weixin_40400177/article/details/103538376
超分辨率数据集
https://blog.csdn.net/weixin_40400177/article/details/103538352
DIV2K，NITRE18/17采用
https://data.vision.ee.ethz.ch/cvl/DIV2K/
DIV2K接口
https://tensorflow.google.cn/datasets/catalog/div2k?hl=zh-tw
SR常用卷积
https://blog.csdn.net/leviopku/article/details/84975282
CVPR与NTIRE比赛
https://data.vision.ee.ethz.ch/cvl/ntire20/
https://data.vision.ee.ethz.ch/cvl/ntire17//
谷歌非CNN-SR方案
RAISR(Rapid and Accurate Super Image Resolution)论文翻译
https://blog.csdn.net/u011961856/article/details/77113099
Code
https://github.com/MKFMIKU/RAISR
https://github.com/movehand/raisr
具体实现方案
NTIRE2020-RWSR双赛道冠军方案Real-SR
https://zhuanlan.zhihu.com/p/148176327
https://github.com/jixiaozhong/RealSR
Investigating Loss Functions for Extreme Super-Resolution，NTIRE2020亚军
https://github.com/kingsj0405/ciplab-NTIRE-2020
百度DRNSR_Closed-loop Matters_Dual Regression Networks for Single Image Super-Resolution
https://blog.csdn.net/csdnnews/article/details/105283512
WDSR(NTIRE2018超分辨率冠军)【深度解析】
https://muzhan.blog.csdn.net/article/details/85048846
小米开源FALSR算法：快速精确轻量级的超分辨率模型
https://blog.csdn.net/dqcfkyqdxym3f8rb0/article/details/86731824
CVPR 2019 | 旷视提出Meta-SR：单一模型实现超分辨率任意缩放因子
https://www.sohu.com/a/304758405_418390
最常参考的SR开源工程
Densely Residual Laplacian Super-resolution, IEEE 2020，DRLN，与RIDNet和IERD源码重叠度很高
https://github.com/saeed-anwar/DRLN
PyTorch 2018 "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"，RCAN
https://github.com/yulunzhang/RCAN
PyTorch 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)，EDSR，比赛官方实现
https://github.com/thstkdgus35/EDSR-PyTorch
https://github.com/LimBee/NTIRE2017
Winning NTIRE19-Video Restoration with Enhanced Deformable Convolutional Networks. EDVR
https://github.com/xinntao/EDVR
EDVR：基于可形变卷积的视频恢复、去模糊、超分网络
https://blog.csdn.net/weixin_45250844/article/details/103674901
CVPR18 - Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform，SFTGAN，场景估计SR
https://github.com/xinntao/SFTGAN
Non-Local Recurrent Network for Image Restoration (NeurIPS 2018)，NLRN，利用空间注意力机制
https://github.com/Ding-Liu/NLRN
图像重建最新Tricks，小波变换
Seven ways to improve example-based single image resolution 笔记
https://www.jianshu.com/p/04de731f327e、
论文——《Loss Functions for Image Restoration With Neural Networks》
https://blog.csdn.net/zyr_freedom/article/details/90381577
Smooth L1 Loss（Huber）：pytorch中的计算原理及使用问题
https://blog.csdn.net/weixin_43915709/article/details/89430843
pytorch loss function 总结
https://blog.csdn.net/zhangxb35/article/details/72464152
论文阅读笔记之——《Multi-level Wavelet-CNN for Image Restoration》及基于pytorch的复现，MWCNN
https://blog.csdn.net/gwplovekimi/article/details/84851871
《Densely Self-guided Wavelet Network for Image Denoising》论文阅读
https://blog.csdn.net/liujiuxiaoshitou/article/details/107379441
《Progressive Training of Multi-level Wavelet Residual Networks for Image Denoising》阅读笔记
https://blog.csdn.net/liujiuxiaoshitou/article/details/109729121
小波变换Tricks的代码实现，在图像重建领域中的应用
数字图像处理与Python实现笔记之图像小波变换与多分辨率
https://blog.csdn.net/qq_40507857/article/details/107709431
（3）小波变换原理及应用
https://haowang.blog.csdn.net/article/details/82909332
Multi-level Wavelet-CNN for Image Restoration， matlab实现
Training Code for MWCNN in PyTorch environment
https://github.com/lpj0/MWCNN_PyTorch
Multi-level Wavelet Convolutional Neural Networks
https://github.com/lpj-github-io/MWCNNv2
Densely-Self-guided-Wavelet-Network-for-Image-Denoising，密集自导小波网络，用于denoise
https://github.com/liujikun/Densely-Self-guided-Wavelet-Network-for-Image-Denoising
Self-Guided-Network-for-Fast-Image-Denoising，自导网络，用于denoise
https://github.com/CurryYuan/Self-Guided-Network-for-Fast-Image-Denoising
Progressive Training of Multi-level Wavelet Residual Networks for Image Denoising，PT-MWRN，用于denoise
https://github.com/happycaoyue/PT-MWRN
小波变换工具库
pytorch-msssim安装
https://www.cnpython.com/pypi/pytorch-msssim
Fast and differentiable MS-SSIM and SSIM for pytorch，源码地址
https://github.com/VainF/pytorch-msssim
https://github.com/jorge-pessoa/pytorch-msssim
https://github.com/Po-Hsun-Su/pytorch-ssim
pytorch_wavelets包实现的小波变换和MWCNN中的小波变换的异同点 - 慢行厚积 - 博客园，安装
https://www.cnblogs.com/wanghui-garcia/p/12526298.html
2D Wavelet Transforms in Pytorch，CNN中的小波变换，官方文档
https://github.com/fbcotter/pytorch_wavelets
https://pytorch-wavelets.readthedocs.io/en/latest/dwt.html
PyWavelets - Wavelet Transforms in Python，小波变换代码
https://github.com/PyWavelets/pywt
小波变换基础
【Codecs系列】之视频编码中的块效应、振铃效应和呼吸效应分析
https://blog.csdn.net/m1379/article/details/101547121
图像处理-小波变换，用matlab函数做小波变换，参数和使用讲解
https://blog.csdn.net/qq_30815237/article/details/89704855
(转载)初识小波变换——傅里叶变换的局限性 - 固态二氧化碳 - 博客园，去掉了母小波、父小波的概念
https://www.cnblogs.com/dryice/p/13869407.html
小波变换（wavelet transform）的通俗解释（一），教完整的讲解
https://www.cnblogs.com/jfdwd/p/9249850.html
如何通俗地讲解傅立叶分析和小波分析间的关系？ - 知乎，通俗讲解最初来源
https://www.zhihu.com/question/22864189
形象易懂讲解算法I——小波变换，回答作者写成了专栏
https://zhuanlan.zhihu.com/p/22450818
形象易懂讲解算法II——压缩感知 - 知乎，作者又写了一篇
https://zhuanlan.zhihu.com/p/22445302
（3）小波变换原理及应用_hhaowang的博客-CSDN博客_小波变换，讲解不太直观，有大段的matlab代码，denoise效果不太好
https://blog.csdn.net/hhaowang/article/details/82909332
小波信号处理_深入理解数字信号处理-CSDN博客，知名小波变换英文博文的翻译
https://blog.csdn.net/deepdsp/category_1076499.html
其他非常规图像重建Tricks
语义分割(semantic segmentation)--DeepLabV3之ASPP(Atrous Spatial Pyramid Pooling)代码详解，类似dilate-conv