Hacking VMAF and VMAF NEG: metrics vulnerability to different preprocessing.

Video quality measurement plays a critical role in the development of video processing applications. In this paper, we show how popular quality metrics VMAF and its tuning-resistant version VMAF NEG can be artificially increased by video preprocessing. We propose a pipeline for tuning parameters of processing algorithms that allows increasing VMAF by up to 218.8%. A subjective comparison of preprocessed videos showed that with the majority of methods visual quality drops down or stays unchanged. We show that VMAF NEG scores can also be increased by some preprocessing methods by up to 23.6%.