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VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models: Methods and Results

  • Hanwei Zhu
  • , Haoning Wu
  • , Zicheng Zhang
  • , Lingyu Zhu
  • , Yixuan Li
  • , Peilin Chen
  • , Shiqi Wang*
  • , Chris Wei Zhou
  • , Linhan Cao
  • , Wei Sun
  • , Xiangyang Zhu
  • , Weixia Zhang
  • , Yucheng Zhu
  • , Jing Liu
  • , Dandan Zhu
  • , Guangtao Zhai
  • , Xiongkuo Min
  • , Zhichao Zhang
  • , Xinyue Li
  • , Shubo Xu
  • Anh Dao, Yifan Li, Hongyuan Yu, Jiaojiao Yi, Yiding Tian, Yupeng Wu, Feiran Sun, Lijuan Liao, Song Jiang
*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a summary of the VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models (LMMs), hosted as part of the ICCV 2025 Work-shop on Visual Quality Assessment. The challenge aims to evaluate and enhance the ability of state-of-the-art LMMs to perform open-ended and detailed reasoning about visual quality differences across multiple images. To this end, the competition introduces a novel benchmark comprising thousands of coarse-to-fine grained visual quality comparison tasks, spanning single images, pairs, and multi-image groups. Each task requires models to provide accurate quality judgments. The competition emphasizes holistic evaluation protocols, including 2AFC-based binary preference and multi-choice questions (MCQs). Around 100 participants submitted entries, with five models demonstrating the emerging capabilities of instruction-tuned LMMs on quality assessment. This challenge marks a significant step toward open-domain visual quality reasoning and comparison and serves as a catalyst for future research on inter-pretable and human-aligned quality evaluation systems.

Original languageEnglish
Title of host publicationProceedings - 2025 IEEE/CVF International Conference on Computer Vision Workshops, ICCV-W 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3383-3393
Number of pages11
ISBN (Electronic)9798331589882
DOIs
StatePublished - 2025
Event2025 IEEE/CVF International Conference on Computer Vision Workshops, ICCV-W 2025 - Honolulu, United States
Duration: 19 Oct 202520 Oct 2025

Publication series

NameProceedings - 2025 IEEE/CVF International Conference on Computer Vision Workshops, ICCV-W 2025

Conference

Conference2025 IEEE/CVF International Conference on Computer Vision Workshops, ICCV-W 2025
Country/TerritoryUnited States
CityHonolulu
Period19/10/2520/10/25

Keywords

  • Image Quality Assessment
  • Large Multimodal Models

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