25 citations · 58 across the 21 of their papers we have counts for
8 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…
VQualA 2025 Challenge on Engagement Prediction for Short Videos: Methods and Results
Dasong Li, Sizhuo Ma, Hang Hua +40
This paper presents an overview of the VQualA 2025 Challenge on Engagement Prediction for Short Videos, held in conjunction with ICCV 2025. The challenge focuses on understanding a…
Engagement Prediction of Short Videos with Large Multimodal Models
Wei Sun, Linhan Cao, Yuqin Cao +7
The rapid proliferation of user-generated content (UGC) on short-form video platforms has made video engagement prediction increasingly important for optimizing recommendation syst…
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…
Ges-QA: A Multidimensional Quality Assessment Dataset for Audio-to-3D Gesture Generation
Zhilin Gao, Yunhao Li, Sijing Wu +3
The Audio-to-3D-Gesture (A2G) task has enormous potential for various applications in virtual reality and computer graphics, etc. However, current evaluation metrics, such as Fréch…
NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results
Xiaohong Liu, Xiongkuo Min, Qiang Hu +92
This paper reports on the NTIRE 2025 XGC Quality Assessment Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) a…
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…