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A MATLAB implementation of feature fused VIDeo quality EVALuator (VIDEVAL) proposed in UGC-VQA: Benchmarking blind video quality assessment for user generated content.
Check out our performance benchmark results in https://github.com/tu184044109/BVQA_Benchmark.
demo_compute_VIDEVAL_feats.m
You need to specify the parameters
This pre-trained model was trained on the combined dataset.
You need first extract features:
demo_compute_VIDEVAL_feats.m
Then run:
demo_pred_MOS_pretrained_VIDEVAL.py
demo_eval_BVQA_feats_one_dataset.py
You need to specify the parameters
demo_eval_BVQA_feats_all_combined.py
You need to specify the parameters
If you use this code for your research, please cite our papers.
@article{tu2020ugc,
title={UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content},
author={Tu, Zhengzhong and Wang, Yilin and Birkbeck, Neil and Adsumilli, Balu and Bovik, Alan C},
journal={arXiv preprint arXiv:2005.14354},
year={2020}
}
Zhengzhong TU, zhengzhong.tu@utexas.edu
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