Hacking VMAF and VMAF NEG: vulnerability to different preprocessing methods

Maksim Siniukov; Anastasia Antsiferova; Dmitriy Kulikov; Dmitriy Vatolin

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arXiv · 2107.04510

Hacking VMAF and VMAF NEG: vulnerability to different preprocessing methods

Maksim Siniukov·Anastasia Antsiferova·Dmitriy Kulikov·Dmitriy Vatolin

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Abstract

Video-quality measurement plays a critical role in the development of video-processing applications. In this paper, we show how video preprocessing can artificially increase the popular quality metric VMAF and its tuning-resistant version, VMAF NEG. We propose a pipeline that tunes processing-algorithm parameters to increase VMAF by up to 218.8%. A subjective comparison revealed that for most preprocessing methods, a video's visual quality drops or stays unchanged. We also show that some preprocessing methods can increase VMAF NEG scores by up to 23.6%.

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Maksim Siniukov, Anastasia Antsiferova, Dmitriy Kulikov, Dmitriy Vatolin. 2021-08-16. Hacking VMAF and VMAF NEG: vulnerability to different preprocessing methods. https://arxiv.org/abs/2107.04510

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