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 ECCV 2024. The task of this challenge was to develop an objective QA method for videos upscaled 2x and 4x by modern image- and video-SR algorithms. QA methods were evaluated by comparing their output with aggregate subjective scores collected from >150,000 pairwise votes obtained through crowd-sourced comparisons across 52 SR methods and 1124 upscaled videos. The goal was to advance the state-of-the-art in SR QA, which had proven to be a challenging problem with limited applicability of traditional QA methods. The challenge had 29 registered participants, and 5 teams had submitted their final results, all outperforming the current state-of-the-art. All data, including the private test subset, has been made publicly available on the challenge homepage at https://challenges.videoprocessing.ai/challenges/super-resolution-metrics-challenge.html

翻译：本文介绍了作为ECCV 2024同期举办的图像处理前沿技术研讨会一部分的视频超分辨率质量评估挑战赛。该挑战赛的任务是针对通过现代图像与视频超分辨率算法进行2倍和4倍放大的视频，开发客观的质量评估方法。质量评估方法的性能通过将其输出与聚合主观评分进行比较来评估，这些主观评分源自对52种超分辨率方法和1124段放大视频进行众包比较所获得的超过15万对投票。本挑战赛旨在推动超分辨率质量评估领域的技术前沿，该领域已被证明是一个具有挑战性的问题，传统质量评估方法的适用性有限。本次挑战赛共有29名注册参与者，其中5支团队提交了最终结果，所有提交结果均超越了当前最优水平。所有数据，包括私有测试子集，已在挑战赛主页（https://challenges.videoprocessing.ai/challenges/super-resolution-metrics-challenge.html）上公开。