Thanks for your attention. In this repo, we provide the codes for the paper [Blind Omnidirectional Image Quality Assessment with Viewport Oriented Graph Convolutional Networks].
- scipy==1.2.1
- opencv_python==4.1.0.25
- numpy==1.16.4
- torchvision==0.3.0
- torch==1.1.0
- Pillow==6.2.0
To install all the dependencies in prerequisites
- Obtain cviqd_local_epoch.pth, cviqd_global_epoch.pth, and cviqd_model.pth
- Download database
matlab fov_selection/demo.m
python main.py --root1 cviqd_local_epoch.pth --root2 cviqd_global_epoch.pth --save test
python main.py --resume cviqd_model.pth --skip_training
You may cite it in your paper. Thanks a lot.
@article{xu2020blind,
title={Blind omnidirectional image quality assessment with viewport oriented graph convolutional networks},
author={Xu, Jiahua and Zhou, Wei and Chen, Zhibo},
journal={IEEE Transactions on Circuits and Systems for Video Technology},
year={2020},
publisher={IEEE}
}