Аннотация:Video quality assessment (VQA) is a crucial task in the development of video compression standards, as it directly impacts theviewer experience. This paper presents the results of the CompressedVideo Quality Assessment challenge, held in conjunction with the Advances in Image Manipulation (AIM) workshop at ECCV 2024. Thechallenge aimed to evaluate the performance of VQA methods on adiverse dataset of 459 videos, encoded with 14 codecs of various compression standards (AVC/H.264, HEVC/H.265, AV1, and VVC/H.266)and containing a comprehensive collection of compression artifacts. Tomeasure the methods performance, we employed traditional correlationcoefficients between their predictions and subjective scores, which werecollected via large-scale crowdsourced pairwise human comparisons. Fortraining purposes, participants were provided with the Compressed VideoQuality Assessment Dataset (CVQAD), a previously developed datasetof 1022 videos. Up to 30 participating teams registered for the challenge,while we report the results of 6 teams, which submitted valid final solutions and code for reproducing the results. Moreover, we calculated andpresent the performance of state-of-the-art VQA methods on the developed dataset, providing a comprehensive benchmark for future research.The dataset, results, and online leaderboard are publicly available athttps://challenges.videoprocessing.ai/challenges/compressedvideo-quality-assessment.html
