Hacking VMAF and VMAF NEG: vulnerability to different preprocessing methods
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Abstract (arXiv)
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%.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 3 of its 20 references that are in the map. First posted on arXiv 9 Jul 2021.
Builds on
3 of 20 references.
References · 3
- 2019ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image Compressioncited by 24
- 2019Hacking VMAF with Video Color and Contrast Distortioncited by 8
- 2019Barriers towards no-reference metrics application to compressed video quality analysis: on the example of no-reference metric NIQEcited by 3
Built on by
Citing papers per year: 2022: 1; 2023: 2; 2024: 2; 2025: 3.
8 papers.
- 2023Comparing the Robustness of Modern No-Reference Image- and Video-Quality Metrics to Adversarial Attackscited by 14
- 2023VMAF Re-implementation on PyTorch: Some Experimental Resultscited by 4
- 2024IOI: Invisible One-Iteration Adversarial Attack on No-Reference Image- and Video-Quality Metricscited by 4
- 2022Applicability limitations of differentiable full-reference image-qualitycited by 1
- 2025A Tri-Dynamic Preprocessing Framework for UGC Video Compressioncited by 1
- 2024IQA-Adapter: Exploring Knowledge Transfer from Image Quality Assessment to Diffusion-based Generative Modelscited by 0
- 2025Towards properties of adversarial image perturbationscited by 0
- 2025Adaptive High-Frequency Preprocessing for Video Codingcited by 0
- 2025A Tri-Dynamic Preprocessing Framework for UGC Video Compression18 Dec 2025
- 2025Adaptive High-Frequency Preprocessing for Video Coding12 Aug 2025
- 2025Towards properties of adversarial image perturbations18 Mar 2025
- 2024IQA-Adapter: Exploring Knowledge Transfer from Image Quality Assessment to Diffusion-based Generative Models2 Dec 2024
- 2024IOI: Invisible One-Iteration Adversarial Attack on No-Reference Image- and Video-Quality Metrics9 Mar 2024
- 2023VMAF Re-implementation on PyTorch: Some Experimental Results24 Oct 2023
- 2023Comparing the Robustness of Modern No-Reference Image- and Video-Quality Metrics to Adversarial Attacks10 Oct 2023
- 2022Applicability limitations of differentiable full-reference image-quality11 Dec 2022