This repository contains the implementation of the following paper:

Reference-based Image and Video Super-Resolution via C2-Matching
Yuming Jiang, Kelvin C.K. Chan, Xintao Wang, Chen Change Loy, Ziwei Liu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022

[Paper] [Project Page]

1. Clone Repo

   git clone git@github.com:yumingj/C2-Matching.git

2. Create Conda Environment

   conda create --name c2_matching_video python=3.7
   conda activate c2_matching_video

3. Install Dependencies

   conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1 -c pytorch
   pip install -U openmim
   mim install mmcv-full==1.3.5
   pip install -r requirements.txt
   pip install -v -e .
   

Downloading the pretrained models from this link and put them under experiments/pretrained_models folder.

For REDS dataset, please refer to this link. The reference images are taken from the first frame of REDS 120fps. For your convience, we put the references of REDS4 dataset in this link.

For Vid4 dataset, please refer to this link.

We provide quick test code with the pretrained model.

python tools/test.py configs/restorers/refvsr/test_reds4.py pretrained_models/c2_matching_video.pth --save-path work_dirs/reds4_results\
python tools/test.py configs/restorers/refvsr/test_vid4.py pretrained_models/c2_matching_video.pth --save-path work_dirs/vid4_results

If you find our repo useful for your research, please consider citing our paper:

@article{jiang2022reference,
   title={Reference-based Image and Video Super-Resolution via $ C\^{}$\{$2$\}$ $-Matching},
   author={Jiang, Yuming and Chan, Kelvin CK and Wang, Xintao and Loy, Chen Change and Liu, Ziwei},
   journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
   year={2022},
   publisher={IEEE}
}

This project is open sourced under MIT license. The code framework is mainly modified from BasicSR and MMSR (Now reorganized as MMEditing). Please refer to the original repo for more usage and documents.

If you have any question, please feel free to contact us via yuming002@e.ntu.edu.sg.