6 papers
DPC-VQA: Decoupling Quality Perception and Residual Calibration for Video Quality Assessment
Xinyue Li, Shubo Xu, Zhichao Zhang +3
Recent multimodal large language models (MLLMs) have shown promising performance on video quality assessment (VQA) tasks. However, adapting them to new scenarios remains expensive…
ELIQ: A Label-Free Framework for Quality Assessment of Evolving AI-Generated Images
Xinyue Li, Zhiming Xu, Min Tang +5
Generative text-to-image models are advancing at an unprecedented pace, continuously shifting the perceptual quality ceiling and rendering previously collected labels unreliable fo…
Decoupling Perception and Calibration: Label-Efficient Image Quality Assessment Framework
Xinyue Li, Zhichao Zhang, Zhiming Xu +4
Recent multimodal large language models (MLLMs) have demonstrated strong capabilities in image quality assessment (IQA) tasks. However, adapting such large-scale models is computat…
Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric
Zhichao Zhang, Wei Sun, Xinyue Li +9
AI-driven video generation techniques have made significant progress in recent years. However, AI-generated videos (AGVs) involving human activities often exhibit substantial visua…
AGHI-QA: A Subjective-Aligned Dataset and Metric for AI-Generated Human Images
Yunhao Li, Sijing Wu, Wei Sun +6
The rapid development of text-to-image (T2I) generation approaches has attracted extensive interest in evaluating the quality of generated images, leading to the development of var…
Large Multi-modality Model Assisted AI-Generated Image Quality Assessment
Puyi Wang, Wei Sun, Zicheng Zhang +5
Traditional deep neural network (DNN)-based image quality assessment (IQA) models leverage convolutional neural networks (CNN) or Transformer to learn the quality-aware feature rep…