Video quality analysis (VQA) is a critical processing task for all major video services. We take streaming services as a key example. Among many possible video encodings of the source material, it is vital to distinguish which encoding would produce the most favorable ratings in terms of quality by the viewers. VQA techniques aim to predict that human quality rating by objective methods. Among such methods, the VMAF algorithm, designed by Netflix, has come into prominence in recent years. We examine VMAF as well as several variants that we have developed, and assess their ability to predict human quality scoring.
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