1 University of Texas at Austin
2 Facebook AI
This project was supported and funded by Facebook AI.
For image quality assesment, check out PaQ-2-PiQ. Please email yingzhenqiang at gmail dot com for any questions. Thank you!
No-reference (NR) perceptual video quality assessment (VQA) is a complex, unsolved, and important problem to social and streaming media applications. Efficient and accurate video quality predictors are needed to monitor and guide the processing of billions of shared, often imperfect, user-generated content (UGC). Unfortunately, current NR models are limited in their prediction capabilities on real-world, "in-the-wild" UGC video data. To advance progress on this problem, we created the largest (by far) subjective video quality dataset, containing 39, 000 real-world distorted videos and 117, 000 space-time localized video patches ("v-patches"), and 5.5M human perceptual quality annotations. Using this, we created two unique NR-VQA models: (a) a local-to-global region-based NR VQA architecture (called PVQ) that learns to predict global video quality and achieves state-of-the-art performance on 3 UGC datasets, and (b) a first-of-a-kind space-time video quality mapping engine (called PVQ Mapper) that helps localize and visualize perceptual distortions in space and time.
Generated Space-time Quality Maps
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Zhenqiang Ying, Maniratnam Mandal, Deepti Ghadiyaram, Alan Bovik. Patch-VQ: 'Patching Up' the Video Quality Problem, In CVPR 2021
Zhenqiang Ying, Haoran Niu, Praful Gupta, Dhruv Mahajan, Deepti Ghadiyaram, Alan Bovik. From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality, In CVPR 2020
Vlad Hosu, Franz Hahn, Mohsen Jenadeleh, Hanhe Lin, Hui Men, Tamás Szirányi, Shujun Li, and Dietmar Saupe. The Konstanz natural video database(KoNViD-1k). In 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX)
Zeina Sinno and Alan C. Bovik. Large-scale study of percep-tual video quality. IEEE Transactions on Image Processing, vol. 28, no. 2, pp. 612-627, Feb. 2019.