5 papers
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…
LongVQUBench: Benchmarking Long-Term Video Quality Understanding of Vision-Language Models
Arpita Nema, Hanwei Zhu, Xi Zhang +1
The evaluation of long-term video quality understanding remains an open challenge for large vision-language models (LVLMs). Existing video quality benchmarks predominantly focus on…
FakeScope: Large Multimodal Expert Model for Transparent AI-Generated Image Forensics
Yixuan Li, Yu Tian, Yipo Huang +4
The rapid and unrestrained advancement of generative artificial intelligence (AI) presents a double-edged sword. While enabling unprecedented creativity, it also facilitates the ge…
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…