1 citations · 2 across the 13 of their papers we have counts for
6 papers · 1 filter
Scale Contrastive Learning with Selective Attentions for Blind Image Quality Assessment
Runze Hu, Zihao Huang, Xudong Li +3
Human visual perception naturally evaluates image quality across multiple scales, a hierarchical process that existing blind image quality assessment (BIQA) algorithms struggle to…
Few-Shot Image Quality Assessment via Adaptation of Vision-Language Models
Xudong Li, Zihao Huang, Yan Zhang +5
Image Quality Assessment (IQA) remains an unresolved challenge in computer vision due to complex distortions, diverse image content, and limited data availability. Existing Blind I…
Contrastive Local Manifold Learning for No-Reference Image Quality Assessment
Zihao Huang, Runze Hu, Timin Gao +3
Image Quality Assessment (IQA) methods typically overlook local manifold structures, leading to compromised discriminative capabilities in perceptual quality evaluation. To address…
Multi-Modal Prompt Learning on Blind Image Quality Assessment
Wensheng Pan, Timin Gao, Yan Zhang +10
Image Quality Assessment (IQA) models benefit significantly from semantic information, which allows them to treat different types of objects distinctly. Currently, leveraging seman…
Cantor: Inspiring Multimodal Chain-of-Thought of MLLM
Timin Gao, Peixian Chen, Mengdan Zhang +8
With the advent of large language models(LLMs) enhanced by the chain-of-thought(CoT) methodology, visual reasoning problem is usually decomposed into manageable sub-tasks and tackl…
Feature Denoising Diffusion Model for Blind Image Quality Assessment
Xudong Li, Jingyuan Zheng, Runze Hu +8
Blind Image Quality Assessment (BIQA) aims to evaluate image quality in line with human perception, without reference benchmarks. Currently, deep learning BIQA methods typically de…