5 citations · 5 across the 9 of their papers we have counts for
12 papers · 1 filter
From Global to Granular: Revealing IQA Model Performance via Correlation Surface
Baoliang Chen, Danni Huang, Hanwei Zhu +5
Evaluation of Image Quality Assessment (IQA) models has long been dominated by global correlation metrics, such as Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank-O…
Plug In, Grade Right: Psychology-Inspired AGIQA
Zhicheng Liao, Baoliang Chen, Hanwei Zhu +3
Existing AGIQA models typically estimate image quality by measuring and aggregating the similarities between image embeddings and text embeddings derived from multi-grade quality d…
AgenticIQA: An Agentic Framework for Adaptive and Interpretable Image Quality Assessment
Hanwei Zhu, Yu Tian, Keyan Ding +4
Image quality assessment (IQA) is inherently complex, as it reflects both the quantification and interpretation of perceptual quality rooted in the human visual system. Conventiona…
AI-generated Image Quality Assessment in Visual Communication
Yu Tian, Yixuan Li, Baoliang Chen +3
Assessing the quality of artificial intelligence-generated images (AIGIs) plays a crucial role in their application in real-world scenarios. However, traditional image quality asse…
Mitigating Perception Bias: A Training-Free Approach to Enhance LMM for Image Quality Assessment
Baoliang Chen, Siyi Pan, Dongxu Wu +4
Despite the impressive performance of large multimodal models (LMMs) in high-level visual tasks, their capacity for image quality assessment (IQA) remains limited. One main reason…
RCNet: Deep Recurrent Collaborative Network for Multi-View Low-Light Image Enhancement
Hao Luo, Baoliang Chen, Lingyu Zhu +2
Scene observation from multiple perspectives would bring a more comprehensive visual experience. However, in the context of acquiring multiple views in the dark, the highly correla…