/VideoSuperResolution

A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.

Primary LanguagePythonMIT LicenseMIT

Video Super Resolution

A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow. (Now VEPSCN model has finally been added to Models, pretrained weights will be uploaded soon...)

Network list and reference (Updating)

The hyperlink directs to paper site, follows the official codes if the authors open sources.

All these models are implemented in ONE framework.

Model Published Code* VSR Included** Keywords
SRCNN ECCV14 -, Keras Y Kaiming
RAISR arXiv - N Google, Pixel 3
ESPCN CVPR16 -, Keras Y Real time
VDSR CVPR16 - Y Deep, Residual
DRCN CVPR16 - Y Recurrent
DRRN CVPR17 Caffe, PyTorch Y Recurrent
LapSRN CVPR17 Matlab Y Huber loss
EDSR CVPR17 - Y NTIRE17 Champion
SRGAN CVPR17 - Y 1st proposed GAN
VESPCN CVPR17 - Y VideoSR
MemNet ICCV17 Caffe Y
SRDenseNet ICCV17 -, PyTorch T Dense
SPMC ICCV17 Tensorflow N VideoSR
DnCNN TIP17 Matlab Y Denoise
DCSCN arXiv Tensorflow Y
IDN CVPR18 Caffe Y Fast
RDN CVPR18 Torch Y Deep, BI-BD-DN
SRMD CVPR18 Matlab T Denoise/Deblur/SR
DBPN CVPR18 PyTorch Y
ZSSR CVPR18 Tensorflow N Zero-shot
FRVSR CVPR18 PDF T VideoSR
DUF CVPR18 Tensorflow T VideoSR
CARN ECCV18 PyTorch Y Fast
RCAN ECCV18 PyTorch Y Deep, BI-BD-DN
MSRN ECCV18 PyTorch Y
SRFeat ECCV18 Tensorflow T GAN
NLRN NIPS18 Tensorflow T Non-local, Recurrent
SRCliqueNet NIPS18 - N Wavelet
CBDNet arXiv Matlab T Blind-denoise

*The 1st repo is by paper author.

**Y: included; N: non-included; T: under-testing.

Link of datasets

(please contact me if any of links offend you or any one disabled)

Name Usage # Site Comments
SET5 Test 5 download jbhuang0604
SET14 Test 14 download jbhuang0604
SunHay80 Test 80 download jbhuang0604
Urban100 Test 100 download jbhuang0604
VID4 Test 4 download 4 videos
BSD100 Train 300 download jbhuang0604
BSD300 Train/Val 300 download -
BSD500 Train/Val 500 download -
91-Image Train 91 download Yang
DIV2K Train/Val 900 website NTIRE17
Waterloo Train 4741 website -
MCL-V Train 12 website 12 videos
GOPRO Train/Val 33 website 33 videos
CelebA Train 202599 website Human faces
Sintel Train/Val 35 website Optical flow
FlyingChairs Train 22872 website Optical flow
DND Train/Val 1000 website Real noisy photos

Other open datasets: Kaggle ImageNet COCO

VSR package

This package offers a training and data processing framework based on TF. What I made is a simple, easy-to-use framework without lots of encapulations and abstractions. Moreover, VSR can handle raw NV12/YUV as well as a sequence of images as inputs.

Install

git clone https://github.com/loseall/VideoSuperResolution && cd VideoSuperResolution
pip install -e .

How to use

To train/test/infer any model in VSR.Models, please see README. To write and train your own model via VSR, please see Docs.