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20202025
most citedTowards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted Approach

50 citations · 241 across the 52 of their papers we have counts for

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Showing 2025 · cs.CVShow all

5 papers · 2 filters

cs.CV2025

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

Hanwei Zhu, Haoning Wu, Zicheng Zhang +26

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 Workshop on Visual Quali…

cs.CV2025

Scaling-up Perceptual Video Quality Assessment

Ziheng Jia, Zicheng Zhang, Zeyu Zhang +12

The data scaling law has been shown to significantly enhance the performance of large multi-modal models (LMMs) across various downstream tasks. However, in the domain of perceptua…

cs.CV2025

Q-Adapt: Adapting LMM for Visual Quality Assessment with Progressive Instruction Tuning

Yiting Lu, Xin Li, Haoning Wu +3

The rapid advancement of Large Multi-modal Foundation Models (LMM) has paved the way for the possible Explainable Image Quality Assessment (EIQA) with instruction tuning from two p…

cs.CV2025

Image Quality Assessment: From Human to Machine Preference

Chunyi Li, Yuan Tian, Xiaoyue Ling +9

Image Quality Assessment (IQA) based on human subjective preferences has undergone extensive research in the past decades. However, with the development of communication protocols,…

cs.CV2025

Q-SiT: Teaching LMMs for Image Quality Scoring and Interpreting

Zicheng Zhang, Haoning Wu, Ziheng Jia +2

Image quality scoring and interpreting are two fundamental components of Image Quality Assessment (IQA). The former quantifies image quality, while the latter enables descriptive q…