GAN

发布日期: 2025-09-10

更新日期: 2025-09-10

文章字数: 871

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2025-09-10 更新

VQualA 2025 Challenge on Image Super-Resolution Generated Content Quality Assessment: Methods and Results

Authors:Yixiao Li, Xin Li, Chris Wei Zhou, Shuo Xing, Hadi Amirpour, Xiaoshuai Hao, Guanghui Yue, Baoquan Zhao, Weide Liu, Xiaoyuan Yang, Zhengzhong Tu, Xinyu Li, Chuanbiao Song, Chenqi Zhang, Jun Lan, Huijia Zhu, Weiqiang Wang, Xiaoyan Sun, Shishun Tian, Dongyang Yan, Weixia Zhang, Junlin Chen, Wei Sun, Zhihua Wang, Zhuohang Shi, Zhizun Luo, Hang Ouyang, Tianxin Xiao, Fan Yang, Zhaowang Wu, Kaixin Deng

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.

本文介绍了基于图像超分辨率生成内容质量评估（ISRGen-QA）数据集构建的ISRGC-Q挑战，该挑战作为ICCV 2025研讨会视觉质量评估（VQualA）竞赛的一部分而组织。与现有的超分辨率图像质量评估（SR-IQA）数据集不同，ISRGen-QA更加侧重于由最新生成方法（包括生成对抗网络（GANs）和扩散模型）生成的SR图像。此挑战的主要目标是分析现代超分辨率技术引入的独特特征，并有效地评估其感知质量。共有108名参与者注册参加此次挑战，其中4支队伍为最终测试阶段提交了有效的解决方案和事实资料表。这些提交在ISRGen-QA数据集上展示了最先进的性能。该项目在：https://github.com/Lighting-YXLI/ISRGen-QA 公开可用。

论文及项目相关链接

PDF 11 pages, 12 figures, VQualA ICCV Workshop

Summary
提供的文本介绍了基于Image Super-Resolution Generated Content Quality Assessment（ISRGen-QA）数据集的ISRGC-Q挑战。该挑战旨在分析现代超分辨率技术引入的独特特征并有效地评估其感知质量。已有108名参与者注册，其中4支团队为最终测试阶段提交了有效解决方案，并在ISRGen-QA数据集上展现了最佳性能。该项目可在公开仓库中访问。

Key Takeaways