Kernel Modeling Super-Resolution on Real Low-Resolution Images
Project Page | Paper | Supplementary Material | Psychovisual Experiment
by Ruofan Zhou, Sabine Süsstrunk
Dependencies
- Pytorch >= 0.4.0
- OpenCV
- NVIDIA GPU
- HDF5 (only for training)
- MATLAB (only for training)
Quick start (Demo)
In test_code
folder, run the following command:
python demo.py
Training the network yourself
Step 1: prepare the dataset
Download DEPD dataset, prepare the patches and run training_code/kernel_estimation/getkernels.m
in MATLAB.
Step 2: train a GAN on kernels
run training_code/kernel_generator/train.py
.
Step 3: generate
run training_code/kernel_generator/generate.py
.
Step 4: train the super-resolution network
run training_code/super-resolution/main.py
.
Citations
@inproceedings{zhou2019kernel,
title={Kernel Modeling Super-Resolution on Real Low-Resolution Images},
author={Zhou, Ruofan and S{\"u}sstrunk, Sabine},
booktitle={2019 International Conference on Computer Vision},
year={2019}
}