7 citations · 9 across the 8 of their papers we have counts for
3 papers · 1 filter
Exploring adversarial robustness of JPEG AI: methodology, comparison and new methods
Egor Kovalev, Georgii Bychkov, Khaled Abud +5
Adversarial robustness of neural networks is an increasingly important area of research, combining studies on computer vision models, large language models (LLMs), and others. With…
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and Results
Maksim Smirnov, Aleksandr Gushchin, Anastasia Antsiferova +29
Video quality assessment (VQA) is a crucial task in the development of video compression standards, as it directly impacts the viewer experience. This paper presents the results of…
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…