https://github.com/it-hao/Super-Resolution

Awesome-Super-Resolution（in progress…）

collect some super-resolution related papers, datasets, metrics and repositories.

most of these contents are referenced from here. Thank you!!!

1.Important Repositories

Awesome paper list:

Paper with code: Super Resolution

Single-Image-Super-Resolution

Super-Resolution. Benckmark

Video-Super-Resolution

VideoSuperResolution

Awesome Super-Resolution

Awesome repos:

repo	Framework
EDSR-PyTorch	PyTorch
RCAN-PyTorch	PyTorch
BasicSR	PyTorch
Image-Super-Resolution	Keras
image-super-resolution	Keras
Super-Resolution-Zoo	MxNet
super-resolution	Keras
neural-enhance	Theano
srez	Tensorflow
waifu2x	Torch
Super-resolution	PyTorch
VideoSuperResolution	Tensorflow
Video-super-resolution	PyTorch

SR Metrics

Note this table is referenced from here.

Metric	Papers
MS-SSIM	Multiscale structural similarity for image quality assessment, Wang, Zhou; Simoncelli, Eero P.; Bovik, Alan C., ACSSC 2003, [ACSSC], `MS-SSIM`
SSIM	Image Quality Assessment: From Error Visibility to Structural Similarity, Wang, Zhou; Bovik, Alan C.; Sheikh, Hamid R.; Simoncelli, Eero P, TIP 2004, [TIP], `SSIM`
IFC	An information fidelity criterion for image quality assessment using natural scene statistics, Sheikh, Hamid Rahim; Bovik, Alan Conrad; de Veciana, Gustavo de Veciana, TIP 2005, [TIP], `IFC`
VIF	Image information and visual quality, Sheikh, Hamid Rahim; Bovik, Alan C., TIP 2006, [TIP], `VIF`
FSIM	FSIM: A Feature Similarity Index for Image Quality Assessment, Zhang, Lin; Zhang, Lei; Mou, Xuanqin; Zhang, David, TIP 2011, [Project], [TIP], `FSIM`
NIQE	Making a “Completely Blind” Image Quality Analyzer, Mittal, Anish; Soundararajan, Rajiv; Bovik, Alan C., Signal Processing Letters 2013, [Matlab*], [Signal Processing Letters], `NIQE`
Ma	Learning a no-reference quality metric for single-image super-resolution, Ma, Chao; Yang, Chih-Yuan; Yang, Xiaokang; Yang, Ming-Hsuan, CVIU 2017, [arXiv], [CVIU], [Matlab*], [Project], `Ma`

2.Datasets

Note this table is referenced from here.

Name	Usage	Link	Comments
Set5	Test	download	jbhuang0604
SET14	Test	download	jbhuang0604
BSD100	Test	download	jbhuang0604
Urban100	Test	download	jbhuang0604
Manga109	Test	website
SunHay80	Test	download	jbhuang0604
BSD300	Train/Val	download
BSD500	Train/Val	download
91-Image	Train	download	Yang
DIV2K2017	Train/Val	website	NTIRE2017
Real SR	Train/Val	website	NTIRE2019
Waterloo	Train	website
VID4	Test	download	4 videos
MCL-V	Train	website	12 videos
GOPRO	Train/Val	website	33 videos, deblur
CelebA	Train	website	Human faces
Sintel	Train/Val	website	Optical flow
FlyingChairs	Train	website	Optical flow
Vimeo-90k	Train/Test	website	90k HQ videos
SR-RAW	Train/Test	website	raw sensor image dataset
Benchmark and DIV2k(SR)	Train/Test	website	super-resolution dataset
SR Testing Datasets	Test	website	super-resolution dataset

3.Papers

Non-DL based approach

SCSR: TIP2010, Jianchao Yang et al.paper, code

ANR: ICCV2013, Radu Timofte et al. paper, code

A+: ACCV 2014, Radu Timofte et al. paper, code

IA: CVPR2016, Radu Timofte et al. paper

SelfExSR: CVPR2015, Jia-Bin Huang et al. paper, code

NBSRF: ICCV2015, Jordi Salvador et al. paper

RFL: ICCV2015, Samuel Schulter et al paper, code

DL based approach

Note this table is referenced from here

Model	Published	Code	Keywords
SRCNN	ECCV14	Keras	CNN
RAISR	arXiv	-	Google, Pixel 3
ESPCN	CVPR16	Keras	Real time/SISR/VideoSR
VDSR	CVPR16	Matlab	Deep, Residual
DRCN	CVPR16	Matlab	Recurrent
DRRN	CVPR17	Caffe, PyTorch	Recurrent
LapSRN	CVPR17	Matlab	Huber loss
IRCNN	CVPR17	Matlab
EDSR	CVPR17	PyTorch	NTIRE17 Champion
BTSRN	CVPR17	-	NTIRE17
SelNet	CVPR17	-	NTIRE17
TLSR	CVPR17	-	NTIRE17
SRGAN	CVPR17	Tensorflow	1st proposed GAN
VESPCN	CVPR17	-	VideoSR
MemNet	ICCV17	Caffe	Dense && Recurrent
SRDenseNet	ICCV17	-, PyTorch	Dense
SPMC	ICCV17	Tensorflow	VideoSR
EnhanceNet	ICCV17	TensorFlow	Perceptual Loss
PRSR	ICCV17	TensorFlow	an extension of PixelCNN
AffGAN	ICLR17	-
MS-LapSRN	TPAMI18	Matlab	Fast LapSRN
DCSCN	arXiv	Tensorflow
IDN	CVPR18	Caffe	Fast
DSRN	CVPR18	TensorFlow	Dual state && Recurrent
RDN	CVPR18	Torch	Deep && BI-BD-DN && Dense
SRMD	CVPR18	Matlab	Denoise/Deblur/SR
xUnit	CVPR18	PyTorch	Spatial Activation Function
DBPN	CVPR18	PyTorch	NTIRE18 Champion
WDSR	CVPR18	PyTorch，TensorFlow	NTIRE18 Champion
ProSRN	CVPR18	PyTorch	NTIRE18 && Progressive
ZSSR	CVPR18	Tensorflow	Zero-shot
FRVSR	CVPR18	PDF	VideoSR
DUF	CVPR18	Tensorflow	VideoSR
TDAN	arXiv	-	VideoSR && Deformable Align
SFTGAN	CVPR18	PyTorch
CARN	ECCV18	PyTorch	Lightweight
RCAN	ECCV18	PyTorch	Deep && BI-BD-DN && Channel-wise Attention
MSRN	ECCV18	PyTorch	Multi-scale
SRFeat	ECCV18	Tensorflow	GAN
TSRN	ECCV18	Pytorch
ESRGAN	ECCV18	PyTorch	PRIM18 region 3 Champion
EPSR	ECCV18	PyTorch	PRIM18 region 1 Champion
PESR	ECCV18	PyTorch	ECCV18 workshop
FEQE	ECCV18	Tensorflow	Fast
NLRN	NIPS18	Tensorflow	Non-local, Recurrent
SRCliqueNet	NIPS18	-	Wavelet
CBDNet	arXiv	Matlab	Blind-denoise
TecoGAN	arXiv	Tensorflow	VideoSR GAN
RBPN	CVPR19	PyTorch	VideoSR
SRFBN	CVPR19	PyTorch	Feedback && Recurrent
AdaFM	CVPR19	PyTorch	Adaptive Feature Modification Layers
MoreMNAS	arXiv	-	Lightweight，NAS
FALSR	arXiv	TensorFlow	Lightweight，NAS
Meta-SR	CVPR19	PyTorch	Arbitrary Magnification
AWSRN	arXiv	PyTorch	Lightweight
OISR	CVPR19	PyTorch	ODE-inspired Network
DPSR	CVPR19	PyTorch
DNI	CVPR19	PyTorch
MAANet	arXiv		Multi-view Aware Attention
RNAN	ICLR19	PyTorch	Residual Non-local Attention
FSTRN	CVPR19	-	VideoSR, fast spatio-temporal residual block
MsDNN	arXiv	TensorFlow	NTIRE19 real SR 21th place
SAN	CVPR19	Pytorch	Second-order Attention, cvpr19 oral
EDVR	CVPRW19	Pytorch	Video, NTIRE19 video restoration and enhancement champions
Ensemble for VSR	CVPRW19	-	VideoSR, NTIRE19 video SR 2nd place
TENet	arXiv	Pytorch	a Joint Solution for Demosaicking, Denoising and Super-Resolution
MCAN	arXiv	Pytorch	Matrix-in-matrix CAN, Lightweight
IKC&SFTMD	CVPR19	-	Blind Super-Resolution
SRNTT	CVPR19	TensorFlow	Neural Texture Transfer
RawSR	CVPR19	TensorFlow	Real Scene Super-Resolution, Raw Images
resLF	CVPR19		Light field
CameraSR	CVPR19		realistic image SR
ORDSR	TIP	model	DCT domain SR
U-Net	CVPRW19		NTIRE19 real SR 2nd place, U-Net,MixUp,Synthesis
DRLN	arxiv		Densely Residual Laplacian Super-Resolution
EDRN	CVPRW19	Pytorch	NTIRE19 real SR 9th places
FC2N	arXiv		Fully Channel-Concatenated
GMFN	BMVC2019	Pytorch	Gated Multiple Feedback
CNN&TV-TV Minimization	BMVC2019		TV-TV Minimization
HRAN	arXiv		Hybrid Residual Attention Network
PPON	arXiv	code	Progressive Perception-Oriented Network
SROBB	ICCV19		Targeted Perceptual Loss
RankSRGAN	ICCV19	PyTorch	oral, rank-content loss
s-LWSR	arXiv		Lightweight Network
ESRN	arXiv
MGAN	arXiv
IMDN	ACM MM 2019	PyTorch	Lightweight Network
WDST	arXiv		perception-distortion tradeoff
ABPN	arXiv	PyTorch
PFNL	ICCV19	Tensorflow	VideoSR oral,Non-Local Spatio-Temporal Correlations
EBRN	ICCV19		Embedded Block Residual Network
Deep SR-ITM	ICCV19	matlab	SDR to HDR, 4K SR
feature SR	ICCV19		Super-Resolution for Small Object Detection
STFAN	ICCV19	PyTorch	Video Deblurring
KMSR	ICCV19	PyTorch	GAN for blur-kernel estimation
JDSR	arXiv		Demosaicing and SR
CFSNet	ICCV19	PyTorch	Controllable Feature
FSRnet	ICCV19		Multi-bin Trainable Linear Units
SAM+VAM	ICCVW19

Super Resolution survey：

[1] Wenming Yang, Xuechen Zhang, Yapeng Tian, Wei Wang, Jing-Hao Xue. Deep Learning for Single Image Super-Resolution: A Brief Review. arxiv, 2018. paper

[2]Saeed Anwar, Salman Khan, Nick Barnes. A Deep Journey into Super-resolution: A survey. arxiv, 2019.paper

[3]Wang, Z., Chen, J., & Hoi, S. C. (2019). Deep learning for image super-resolution: A survey. arXiv preprint arXiv:1902.06068.paper