Ti-Patch: Tiled Physical Adversarial Patch for no-reference video quality metrics

arXiv:2404.09961v1 Announce Type: new
Abstract: Objective no-reference image- and video-quality metrics are crucial in many computer vision tasks. However, state-of-the-art no-reference metrics have become learning-based and are vulnerable to adversarial attacks. The vulnerability of quality metrics imposes restrictions on using such metrics in quality control systems and comparing objective algorithms. Also, using vulnerable metrics as a loss for deep learning model training can mislead training to worsen visual quality. Because of that, quality metrics testing for vulnerability is a task …

adversarial arxiv cs.cv eess.iv metrics quality reference type video video quality