8 citations · 27 across the 22 of their papers we have counts for
5 papers · 1 filter
VQA: Visual Question Answering for Video Quality Assessment
Ziheng Jia, Zicheng Zhang, Jiaying Qian +7
The advent and proliferation of large multi-modal models (LMMs) have introduced new paradigms to computer vision, transforming various tasks into a unified visual question answerin…
AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results
Ivan Molodetskikh, Artem Borisov, Dmitriy Vatolin +24
This paper presents the Video Super-Resolution (SR) Quality Assessment (QA) Challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with E…
AIM 2024 Challenge on Video Saliency Prediction: Methods and Results
Andrey Moskalenko, Alexey Bryncev, Dmitry Vatolin +30
This paper reviews the Challenge on Video Saliency Prediction at AIM 2024. The goal of the participants was to develop a method for predicting accurate saliency maps for the provid…
Q-Bench-Video: Benchmarking the Video Quality Understanding of LMMs
Zicheng Zhang, Ziheng Jia, Haoning Wu +8
With the rising interest in research on Large Multi-modal Models (LMMs) for video understanding, many studies have emphasized general video comprehension capabilities, neglecting t…
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…