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

• URL: http://arxiv.org/abs/2509.06413v1
• Date: Mon, 08 Sep 2025 08:07:50 GMT
• Title: 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,
• Abstract summary: This paper presents the ISRGC-Q Challenge, built upon the Image Super-Resolution Generated Content Quality Assessment dataset.<n>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.
• Score: 65.82676254264837
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

Related papers

• NTIRE 2025 Challenge on Image Super-Resolution ($\times$4): Methods and Results [159.15538432295656]
  The NTIRE 2025 image super-resolution ($times$4) challenge is one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025.<n>The challenge aims to recover high-resolution (HR) images from low-resolution (LR) counterparts generated through bicubic downsampling with a $times$4 scaling factor.<n>A total of 286 participants registered for the competition, with 25 teams submitting valid entries.
  arXiv  Detail & Related papers  (2025-04-20T12:08:22Z)
• NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results [179.05961380270648]
  Review of the NTIRE 2025 Challenge on Short-form Video Quality Assessment and Enhancement.<n>Challenge comprises two tracks: (i) Efficient Video Quality Assessment (KVQ), and (ii) Diffusion-based Image Super-Resolution (KwaiSR)
  arXiv  Detail & Related papers  (2025-04-17T17:45:34Z)
• AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results [76.64868221556145]
  This paper presents the Video Super-Resolution (SR) Quality Assessment (QA) Challenge that was part of the Advances in Image Manipulation (AIM) workshop. The task of this challenge was to develop an objective QA method for videos upscaled 2x and 4x by modern image- and video-SR algorithms. The goal was to advance the state-of-the-art in SR QA, which had proven to be a challenging problem with limited applicability of traditional QA methods.
  arXiv  Detail & Related papers  (2024-10-05T16:42:23Z)
• Study of Subjective and Objective Quality in Super-Resolution Enhanced Broadcast Images on a Novel SR-IQA Dataset [4.770359059226373]
  Super-Resolution (SR), a key consumer technology, is essential to display low-quality broadcast content on high-resolution screens in full-screen format. evaluating the quality of SR images generated from low-quality sources, such as SR-enhanced broadcast content, is challenging. We introduce a new IQA dataset for SR broadcast images in both 2K and 4K resolutions.
  arXiv  Detail & Related papers  (2024-09-26T01:07:15Z)
• NTIRE 2024 Challenge on Image Super-Resolution ($\ imes$4): Methods and Results [126.78130602974319]
  This paper reviews the NTIRE 2024 challenge on image super-resolution ($times$4) The challenge involves generating corresponding high-resolution (HR) images, magnified by a factor of four, from low-resolution (LR) inputs. The aim of the challenge is to obtain designs/solutions with the most advanced SR performance.
  arXiv  Detail & Related papers  (2024-04-15T13:45:48Z)
• NTIRE 2021 Challenge on Perceptual Image Quality Assessment [128.83256694901726]
  This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA) It was held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) at CVPR 2021. As a new type of image processing technology, perceptual image processing algorithms based on Generative Adversarial Networks (GAN) have produced images with more realistic textures.
  arXiv  Detail & Related papers  (2021-05-07T05:36:54Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.