Real-Time Video Quality Prediction on Live, High-Motion Studio/Professional-Grade Content

2023 Cycle


A.C. Bovik, Department of Electrical and Computer Engineering


Predicting perceptual video quality is a hard problem that has been successfully addressed in many scenarios, such as quality control of streaming and sharing of videos. However, videos continue to “get bigger” along every dimension including frame rate, bit depth, color gamut, resolution, and fusion with generative methods. This work addresses new quality issues that arise and how to deal with them to optimize perceptual video quality vs bandwidth consumption.