33 citations · 71 across the 21 of their papers we have counts for
6 papers · 1 filter
XGC-AVis: Towards Audio-Visual Content Understanding with a Multi-Agent Collaborative System
Yuqin Cao, Xiongkuo Min, Yixuan Gao +4
In this paper, we propose XGC-AVis, a multi-agent framework that enhances the audio-video temporal alignment capabilities of multimodal large models (MLLMs) and improves the effici…
Audio-Assisted Face Video Restoration with Temporal and Identity Complementary Learning
Yuqin Cao, Yixuan Gao, Wei Sun +3
Face videos accompanied by audio have become integral to our daily lives, while they often suffer from complex degradations. Most face video restoration methods neglect the intrins…
Exploring Image Quality Assessment from a New Perspective: Pupil Size
Yixuan Gao, Xiongkuo Min, Guangtao Zhai
This paper explores how the image quality assessment (IQA) task affects the cognitive processes of people from the perspective of pupil size and studies the relationship between pu…
FVQ: A Large-Scale Dataset and an LMM-based Method for Face Video Quality Assessment
Sijing Wu, Yunhao Li, Ziwen Xu +4
Face video quality assessment (FVQA) deserves to be explored in addition to general video quality assessment (VQA), as face videos are the primary content on social media platforms…
Mitigating Low-Level Visual Hallucinations Requires Self-Awareness: Database, Model and Training Strategy
Yinan Sun, Xiongkuo Min, Zicheng Zhang +3
The rapid development of multimodal large language models has resulted in remarkable advancements in visual perception and understanding, consolidating several tasks into a single…
AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment
Yuqin Cao, Xiongkuo Min, Yixuan Gao +2
Many video-to-audio (VTA) methods have been proposed for dubbing silent AI-generated videos. An efficient quality assessment method for AI-generated audio-visual content (AGAV) is…