9 papers
VideoAesBench: Benchmarking the Video Aesthetics Perception Capabilities of Large Multimodal Models
Yunhao Li, Sijing Wu, Zhilin Gao +5
Large multimodal models (LMMs) have demonstrated outstanding capabilities in various visual perception tasks, which has in turn made the evaluation of LMMs significant. However, th…
SFQA: A Comprehensive Perceptual Quality Assessment Dataset for Singing Face Generation
Zhilin Gao, Yunhao Li, Sijing Wu +3
The Talking Face Generation task has enormous potential for various applications in digital humans and agents, etc. Singing, as a common facial movement second only to talking, can…
Q-Bench-Portrait: Benchmarking Multimodal Large Language Models on Portrait Image Quality Perception
Sijing Wu, Yunhao Li, Zicheng Zhang +5
Recent advances in multimodal large language models (MLLMs) have demonstrated impressive performance on existing low-level vision benchmarks, which primarily focus on generic image…
DHQA-4D: Perceptual Quality Assessment of Dynamic 4D Digital Human
Yunhao Li, Sijing Wu, Yucheng Zhu +3
With the rapid development of 3D scanning and reconstruction technologies, dynamic digital human avatars based on 4D meshes have become increasingly popular. A high-precision dynam…
RGC-VQA: An Exploration Database for Robotic-Generated Video Quality Assessment
Jianing Jin, Jiangyong Ying, Huiyu Duan +6
As camera-equipped robotic platforms become increasingly integrated into daily life, robotic-generated videos have begun to appear on streaming media platforms, enabling us to envi…
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…