7 citations · 13 across the 5 of their papers we have counts for
4 papers · 1 filter
Ti-Patch: Tiled Physical Adversarial Patch for no-reference video quality metrics
Victoria Leonenkova, Ekaterina Shumitskaya, Anastasia Antsiferova +1
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…
Adversarial purification for no-reference image-quality metrics: applicability study and new methods
Aleksandr Gushchin, Anna Chistyakova, Vladislav Minashkin +2
Recently, the area of adversarial attacks on image quality metrics has begun to be explored, whereas the area of defences remains under-researched. In this study, we aim to cover t…
BASED: Benchmarking, Analysis, and Structural Estimation of Deblurring
Nikita Alutis, Egor Chistov, Mikhail Dremin +1
This paper discusses the challenges of evaluating deblurring-methods quality and proposes a reduced-reference metric based on machine learning. Traditional quality-assessment metri…
Fast Adversarial CNN-based Perturbation Attack on No-Reference Image- and Video-Quality Metrics
Ekaterina Shumitskaya, Anastasia Antsiferova, Dmitriy Vatolin
Modern neural-network-based no-reference image- and video-quality metrics exhibit performance as high as full-reference metrics. These metrics are widely used to improve visual qua…