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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…
Perceptual Quality Assessment of 360 Images Based on Generative Scanpath Representation
Xiangjie Sui, Hanwei Zhu, Xuelin Liu +3
Despite substantial efforts dedicated to the design of heuristic models for omnidirectional (i.e., 360) image quality assessment (OIQA), a conspicuous gap remains due to th…