collaborators

8 papers

eess.IV2026

Enhancing Blind Video Quality Assessment with Rich Quality-aware Features

Wei Sun, Linhan Cao, Jun Jia +4

Blind video quality assessment (BVQA) is a highly challenging task due to the intrinsic complexity of video content and visual distortions, especially given the high popularity of…

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

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…