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Collect super-resolution related papers, data, repositories

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Awesome-Super-Resolution（in progress）

Collect some super-resolution related papers, data and repositories.

repositories

Awesome paper list:

Single-Image-Super-Resolution

Super-Resolution.Benckmark

Video-Super-Resolution

VideoSuperResolution

Awesome Super-Resolution

Awesome-LF-Image-SR

Awesome-Stereo-Image-SR

AI-video-enhance

Awesome repos:

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

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
Flickr2K Train download
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
W2S Train/Test arxiv A Joint Denoising and Super-Resolution Dataset
PIPAL Test ECCV 2020 Perceptual Image Quality Assessment dataset

Dataset collections

Benckmark and DIV2K: Set5, Set14, B100, Urban100, Manga109, DIV2K2017 include bicubic downsamples with x2,3,4,8

SR_testing_datasets: Test: Set5, Set14, B100, Urban100, Manga109, Historical; Train: T91,General100, BSDS200

paper

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

2014-2016

Model Published Code Keywords
SRCNN ECCV14 Keras Kaiming
RAISR arXiv - Google, Pixel 3
ESPCN CVPR16 Keras Real time/SISR/VideoSR
VDSR CVPR16 Matlab Deep, Residual
DRCN CVPR16 Matlab Recurrent

2017

Model Published Code Keywords
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
SRDenseNet ICCV17 -, PyTorch Dense
SPMC ICCV17 Tensorflow VideoSR
EnhanceNet ICCV17 TensorFlow Perceptual Loss
PRSR ICCV17 TensorFlow an extension of PixelCNN
AffGAN ICLR17 -

2018

Model Published Code Keywords
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
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
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
MSRN ECCV18 PyTorch
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

2019

Model Published Code Keywords
RBPN CVPR19 PyTorch VideoSR
SRFBN CVPR19 PyTorch Feedback
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
edge-informed ICCVW19 PyTorch Edge-Informed Single Image Super-Resolution
s-LWSR arxiv Lightweight
DNLN arxiv Video SR Deformable Non-local Network
MGAN arxiv Multi-grained Attention Networks
IMDN ACM MM 2019 PyTorch AIM19 Champion
ESRN arxiv NAS
PFNL ICCV19 Tensorflow VideoSR oral,Non-Local Spatio-Temporal Correlations
EBRN ICCV19 Tensorflow 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
CFSNet ICCV19 PyTorch Controllable Feature
FSRnet ICCV19 Multi-bin Trainable Linear Units
SAM+VAM ICCVW19
SinGAN ICCV19 PyTorch bestpaper, train from single image

2020

Model Published Code Keywords
FISR AAAI 2020 TensorFlow Video joint VFI-SR method,Multi-scale Temporal Loss
ADCSR arxiv
SCN AAAI 2020 Scale-wise Convolution
LSRGAN arxiv Latent Space Regularization for srgan
Zooming Slow-Mo CVPR 2020 PyTorch joint VFI and SR，one-stage， deformable ConvLSTM
MZSR CVPR 2020 Meta-Transfer Learning, Zero-Shot
VESR-Net arxiv Youku Video Enhancement and Super-Resolution Challenge Champion
blindvsr arxiv PyTorch Motion blur estimation
HNAS-SR arxiv PyTorch Hierarchical Neural Architecture Search, Lightweight
DRN CVPR 2020 PyTorch Dual Regression, SISR STOA
SFM arxiv PyTorch Stochastic Frequency Masking, Improve method
EventSR CVPR 2020 split three phases
USRNet CVPR 2020 PyTorch
PULSE CVPR 2020 Self-Supervised
SPSR CVPR 2020 Code Gradient Guidance, GAN
DASR arxiv Code Real-World Image Super-Resolution, Unsupervised SuperResolution, Domain Adaptation.
STVUN arxiv PyTorch Video Super-Resolution, Video Frame Interpolation, Joint space-time upsampling
AdaDSR arxiv PyTorch Adaptive Inference
Scale-Arbitrary SR arxiv Code Scale-Arbitrary Super-Resolution, Knowledge Transfer
DeepSEE arxiv Code Extreme super-resolution,32× magnification
CutBlur CVPR 2020 PyTorch SR Data Augmentation
UDVD CVPR 2020 Unified Dynamic Convolutional，SISR and denoise
DIN IJCAI-PRICAI 2020 SISR，asymmetric co-attention
PANet arxiv PyTorch Pyramid Attention
SRResCGAN arxiv PyTorch
ISRN arxiv iterative optimization, feature normalization.
RFB-ESRGAN CVPR 2020 NTIRE 2020 Perceptual Extreme Super-Resolution Challenge winner
PHYSICS_SR AAAI 2020 PyTorch
CSNLN CVPR 2020 PyTorch Cross-Scale Non-Local Attention,Exhaustive Self-Exemplars Mining, Similar to PANet
TTSR CVPR 2020 PyTorch Texture Transformer
NSR arxiv PyTorch Neural Sparse Representation
RFANet CVPR 2020 state-of-the-art SISR
Correction filter CVPR 2020 Enhance SISR model generalization
Unpaired SR CVPR 2020 Unpaired Image Super-Resolution
STARnet CVPR 2020 Space-Time-Aware multi-Resolution
SSSR CVPR 2020 code SISR for Semantic Segmentation and Human pose estimation
VSR_TGA CVPR 2020 code Temporal Group Attention, Fast Spatial Alignment
SSEN CVPR 2020 Similarity-Aware Deformable Convolution
SMSR arxiv Sparse Masks, Efficient SISR
LF-InterNet ECCV 2020 PyTorch Spatial-Angular Interaction, Light Field Image SR
Invertible-Image-Rescaling ECCV 2020 Code ECCV oral
IGNN arxiv Code GNN, SISR
MIRNet ECCV 2020 PyTorch multi-scale residual block
SFM ECCV 2020 PyTorch stochastic frequency mask
TCSVT arxiv TensorFlow LightWeight modules
PISR ECCV 2020 PyTorch FSRCNN,distillation framework, HR privileged information
MuCAN ECCV 2020 VideoSR, Temporal Multi-Correspondence Aggregation
DGP ECCV 2020 PyTorch ECCV oral, GAN, Image Restoration and Manipulation,
RSDN ECCV 2020 Code VideoSR, Recurrent Neural Network, TwoStream Block
CDC ECCV 2020 PyTorch Diverse Real-world SR dataset, Component Divide-and-Conquer model, GradientWeighted loss
MS3-Conv arxiv Multi-Scale cross-Scale Share-weights convolution
OverNet arxiv Lightweight, Overscaling Module, multi-scale loss, Arbitrary Scale Factors
RRN BMVC20 code VideoSR, Recurrent Residual Network, temporal modeling method

Super Resolution workshop papers

NTIRE17 papers

NTIRE18 papers

PIRM18 Web

NTIRE19 papers

AIM19 papers

NTIRE20 papers

NOTE! AIM20 Started!

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

[4]Hongying Liu and Zhubo Ruan and Peng Zhao and Fanhua Shang and Linlin Yang and Yuanyuan Liu. Video Super Resolution Based on Deep Learning: A comprehensive survey. arXiv preprint arXiv:2007.12928.paper