Blind Video Quality Assessment

Blind video quality assessment (BVQA) aims to automatically predict the perceived quality of videos without reference to a pristine original, focusing on accurately reflecting human judgment. Recent research emphasizes leveraging pre-trained models and incorporating rich features, including content and distortion priors, to improve the accuracy of BVQA models, often employing transformer-based architectures or incorporating perceptual representations inspired by the human visual system. These advancements are crucial for improving video processing and delivery across various platforms, enabling objective evaluation of video enhancement techniques and ultimately enhancing the user viewing experience.

Papers