This paper presents the ISRGC-Q Challenge, built upon the Image Super-Resolution Generated Content Quality Assessment (ISRGen-QA) dataset, and organized as part of the Visual Quality Assessment (VQualA) Competition at the ICCV 2025 Workshops. Unlike existing Super-Resolution Image Quality Assessment (SR-IQA) datasets, ISRGen-QA places a greater emphasis on SR images generated by the latest generative approaches, including Generative Adversarial Networks (GANs) and diffusion models. The primary goal of this challenge is to analyze the unique artifacts introduced by modern super-resolution techniques and to evaluate their perceptual quality effectively. A total of 108 participants registered for the challenge, with 4 teams submitting valid solutions and fact sheets for the final testing phase. These submissions demonstrated state-of-the-art (SOTA) performance on the ISRGen-QA dataset. The project is publicly available at: https://github.com/Lighting-YXLI/ISRGen-QA.

翻译：本文介绍了 ISRGC-Q 挑战赛，该挑战赛基于图像超分辨率生成内容质量评估（ISRGen-QA）数据集构建，并作为 ICCV 2025 研讨会中视觉质量评估（VQualA）竞赛的一部分组织。与现有的超分辨率图像质量评估（SR-IQA）数据集不同，ISRGen-QA 更侧重于由最新生成方法（包括生成对抗网络和扩散模型）生成的超分辨率图像。本挑战赛的主要目标是分析现代超分辨率技术引入的独特伪影，并有效评估其感知质量。共有 108 名参与者注册了挑战赛，其中 4 支团队在最终测试阶段提交了有效的解决方案和事实说明表。这些提交在 ISRGen-QA 数据集上展示了最先进的性能。该项目公开可用，地址为：https://github.com/Lighting-YXLI/ISRGen-QA。