[IEEE OJSP'2021] "RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content", Zhengzhong Tu, Xiangxu Yu, Yilin Wang, Neil Birkbeck, Balu Adsumilli, Alan C. Bovik
An official implementation of Rapid and Accurate Video Quality Evaluator (RAPIQUE) proposed in [IEEE OJSP2021] RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content. Arxiv. IEEExplore(Open Access!) and [PCS2021] Efficient User-Generated Video Quality Prediction. IEEExplore. Note that the temporal features can be used as standalone features in company with spatial models to boost performance on motion-intensive models. Check out the temporal-only modules in [ICIP21] A Temporal Statistics Model For UGC Video Quality Prediction. IEEExplore
Check out our BVQA resource list and performance benchmark/leaderboard results in https://github.com/vztu/BVQA_Benchmark.
For more evaluation codes, please check out VIDEVAL
Methods | KoNViD-1k | LIVE-VQC | YouTube-UGC | All-Combined |
---|---|---|---|---|
TLVQM | 0.7101 / 0.7037 | 0.7988 / 0.8025 | 0.6693 / 0.6590 | 0.7271 / 0.7342 |
VIDEVAL | 0.7832 / 0.7803 | 0.7522 / 0.7514 | 0.7787 / 0.7733 | 0.7960 / 0.7939 |
MDVSFA | 0.7812 / 0.7856 | 0.7382 / 0.7728 | - / - | - / - |
RAPIQUE | 0.8031 / 0.8175 | 0.7548 / 0.7863 | 0.7591 / 0.7684 | 0.8070 / 0.8229 |
Scatter plots and fitted logistic curves on these datasets:
KonVid-1k | LIVE-VQC | YouTube-UGC | All-Combined |
---|---|---|---|
The unit is average secs/video
.
Methods | 540p | 720p | 1080p | 4k@60 |
---|---|---|---|---|
Video-BLIINDS | 341.1 | 839.1 | 1989.9 | 16129.2 |
VIDEVAL | 61.9 | 146.5 | 354.5 | 1716.3 |
TLVQM | 34.5 | 78.9 | 183.8 | 969.3 |
RAPIQUE | 13.5 | 17.3 | 18.3 | 112 |
demo_compute_RAPIQUE_feats.m
You need to specify the parameters
We proposed several evaluation methods for BIQA/BVQA models. Please check out [ICASSP21] Regression or classification? New methods to evaluate no-reference picture and video quality models IEEExplore for details.
$ python evaluate_bvqa_features_regression.py
$ python evaluate_bvqa_features_binary_classification.py
$ python evaluate_bvqa_features_ordinal_classification.py
If you use this code for your research, please cite our papers.
@article{tu2021rapique,
title={RAPIQUE: Rapid and accurate video quality prediction of user generated content},
author={Tu, Zhengzhong and Yu, Xiangxu and Wang, Yilin and Birkbeck, Neil and Adsumilli, Balu and Bovik, Alan C},
journal={IEEE Open Journal of Signal Processing},
volume={2},
pages={425--440},
year={2021},
publisher={IEEE}
}
@article{tu2021ugc,
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={IEEE Transactions on Image Processing},
year={2021},
publisher={IEEE}
}
@inproceedings{tu2021efficient,
title={Efficient User-Generated Video Quality Prediction},
author={Tu, Zhengzhong and Chen, Chia-Ju and Wang, Yilin and Birkbeck, Neil and Adsumilli, Balu and Bovik, Alan C},
booktitle={2021 Picture Coding Symposium (PCS)},
pages={1--5},
year={2021},
organization={IEEE}
}
@inproceedings{tu2021temporal,
title={A Temporal Statistics Model For UGC Video Quality Prediction},
author={Tu, Zhengzhong and Chen, Chia-Ju and Wang, Yilin and Birkbeck, Neil and Adsumilli, Balu and Bovik, Alan C},
booktitle={2021 IEEE International Conference on Image Processing (ICIP)},
pages={1454--1458},
year={2021},
organization={IEEE}
}
@inproceedings{tu2021regression,
title={Regression or classification? New methods to evaluate no-reference picture and video quality models},
author={Tu, Zhengzhong and Chen, Chia-Ju and Chen, Li-Heng and Wang, Yilin and Birkbeck, Neil and Adsumilli, Balu and Bovik, Alan C},
booktitle={ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={2085--2089},
year={2021},
organization={IEEE}
}