基于深度學習的圖像超分辨率文獻和常用資料

文章目錄

• 文獻
• 常用資料

未完成

文獻

論文簡稱	論文名稱	文章位址	源碼位址
SRCNN	Image Super-Resolution Using Deep Convolutional Networks	https://arxiv.org/abs/1501.00092	http://mmlab.ie.cuhk.edu.hk/projects/SRCNN/SRCNN_train.zip (caffe)， http://mmlab.ie.cuhk.edu.hk/projects/SRCNN/SRCNN_v1.zip (MATLAB), https://github.com/tegg89/SRCNN-Tensorflow (TensorFlow，非作者)
FSRCNN	Accelerating the Super-Resolution Convolutional Neural Network	https://arxiv.org/abs/1608.00367	https://drive.google.com/open?id=0B7tU5Pj1dfCMWjhhaE1HR3dqcGs (caffe), https://drive.google.com/open?id=0B7tU5Pj1dfCMVktYZUN2aV8xVTQ (MATLAB)
VDSR	Accurate Image Super-Resolution Using Very Deep Convolutional Networks	https://arxiv.org/abs/1511.04587	https://github.com/twtygqyy/pytorch-vdsr（PyTorch，非作者）
ESPCN	Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network	https://arxiv.org/abs/1609.05158	https://github.com/leftthomas/ESPCN（PyTorch，非作者）
LapSRN	Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks	https://arxiv.org/abs/1710.01992	https://github.com/phoenix104104/LapSRN (MATLAB), https://github.com/twtygqyy/pytorch-LapSRN （PyTorch，非作者）
EDSR	Enhanced Deep Residual Networks for Single Image Super-Resolution	https://arxiv.org/abs/1707.02921	https://github.com/LimBee/NTIRE2017 (torch), https://github.com/thstkdgus35/EDSR-PyTorch (PyTorch)
RCAN	Image Super-Resolution Using Very Deep Residual Channel Attention Networks	https://arxiv.org/abs/1807.02758	https://github.com/yulunzhang/RCAN (PyTorch)
SRGAN	Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network	https://arxiv.org/abs/1609.04802	https://github.com/tensorlayer/srgan （TensorFlow，非作者）， https://github.com/leftthomas/SRGAN （PyTorch，非作者）
ESRGAN	ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks	https://arxiv.org/abs/1809.00219	https://github.com/xinntao/ESRGAN (PyTorch), https://github.com/xinntao/BasicSR (PyTorch)
SFTGAN	Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform	https://arxiv.org/abs/1804.02815	https://github.com/xinntao/SFTGAN (PyTorch), https://github.com/xinntao/BasicSR (PyTorch)
Meta-SR	Meta-SR: A Magnification-Arbitrary Network for Super-Resolution	https://arxiv.org/abs/1903.00875	https://github.com/XuecaiHu/Meta-SR-Pytorch
DRN	Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution	https://arxiv.org/abs/2003.07018	https://github.com/guoyongcs/DRN
CutBlur	Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy	https://arxiv.org/abs/2004.00448	https://github.com/clovaai/cutblur
EDVR	EDVR: Video Restoration with Enhanced Deformable Convolutional Networks	https://arxiv.org/abs/1905.02716	https://github.com/xinntao/EDVR (PyTorch), https://github.com/xinntao/BasicSR (PyTorch)

常用資料

Set5，Set14，Urban100，BSD100，Sun-Hays 80（均為小資料集）：

https://github.com/jbhuang0604/SelfExSR

Flickr2K（20G）：

http://cv.snu.ac.kr/research/EDSR/Flickr2K.tar

DIV2K（8G+）

https://data.vision.ee.ethz.ch/cvl/DIV2K/