EgoVSR: Towards High-Quality Egocentric Video Super-Resolution

Paper

EgoVSR: Towards High-Quality Egocentric Video Super-Resolution

Yichen Chi, Junhao Gu, Jiamiao Zhang, Wenming Yang, Yapeng Tian

Arxiv

Installation

This work is based on the MMEditing (now MMagic) framework. Thanks to OpenMMLab.

MMEditing depends on PyTorch and MMCV. Below are quick steps for installation.

Step 1. Install PyTorch following official instructions.

Step 2. Install MMCV with MIM.

pip3 install openmim
mim install mmcv-full

Step 3. Install MMEditing from source.

git clone https://github.com/chiyich/EGOVSR.git
cd EGOVSR
pip3 install -e .

Please refer to install.md for more detailed instruction.

Getting Started

Step 1. Download our checkpoint and EGOVSR test/valid dataset and REDS dataset. We need train_sharp subset and train_blur if you need to train second-order model.

Step 2. Prepare datasets and modify the folder location in config files.

Step 3. Train your own model(4 indicates the number of GPUs):

#for first stage training (L1 Model)
bash tools/dist_train.sh configs/egovsr/egovsr_L1_reds.py 4
#for second stage training (GAN Model)
bash tools/dist_train.sh configs/egovsr/egovsr_reds.py 4

Or test:

python tools/test.py configs/egovsr/egovsr_reds.py experiments/egovsr/iter_250000.pth --save-path work_dirs/results/

We use PIRM2018 code to evaluate all metrics.

Contributing

We appreciate all contributions to improve MMEditing. Please refer to our contributing guidelines.

Citation

If our work is helpful to your research, please cite it as below.

@article{chi2023egovsr,
  title={EgoVSR: Towards High-Quality Egocentric Video Super-Resolution},
  author={Chi, Yichen and Gu, Junhao and Zhang, Jiamiao and Yang, Wenming and Tian, Yapeng},
  journal={arXiv preprint arXiv:2305.14708},
  year={2023}
}

License

This project is released under the Apache 2.0 license.