5 papers
Not All Inputs Are Valid: Towards Open-Set Video Moment Retrieval Using Language
Xiang Fang, Wanlong Fang, Daizong Liu +8
Video Moment Retrieval (VMR) targets to retrieve the specific moment corresponding to a sentence query from an untrimmed video. Although recent works have made remarkable progress…
Rethinking Video-Language Model from the Language Input Perspective
Xiang Fang, Wanlong Fang, Changshuo Wang +2
Driven by the wave of large language models, Video-Language Models (VLMs) have become a significant yet challenging technology to bridge the gap between videos and texts. Although…
Rethinking Weakly-supervised Video Temporal Grounding From a Game Perspective
Xiang Fang, Zeyu Xiong, Wanlong Fang +7
This paper addresses the challenging task of weakly-supervised video temporal grounding. Existing approaches are generally based on the moment proposal selection framework that uti…
VCE: A zero-cost hallucination mitigation method of LVLMs via visual contrastive editing
Yanbin Huang, Yisen Li, Guiyao Tie +6
Large vision-language models (LVLMs) frequently suffer from Object Hallucination (OH), wherein they generate descriptions containing objects that are not actually present in the in…
Audio Does Matter: Importance-Aware Multi-Granularity Fusion for Video Moment Retrieval
Junan Lin, Daizong Liu, Xianke Chen +5
Video Moment Retrieval (VMR) aims to retrieve a specific moment semantically related to the given query. To tackle this task, most existing VMR methods solely focus on the visual a…