15 citations · 17 across the 5 of their papers we have counts for
9 papers · 1 filter
Annotations Are Not All You Need: A Cross-modal Knowledge Transfer Network for Unsupervised Temporal Sentence Grounding
Xiang Fang, Daizong Liu, Wanlong Fang +4
This paper addresses the task of temporal sentence grounding (TSG). Although many respectable works have made decent achievements in this important topic, they severely rely on mas…
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 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…
A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends
Daizong Liu, Mingyu Yang, Xiaoye Qu +3
With the significant development of large models in recent years, Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across a wide range of multimodal u…
Unsupervised Temporal Video Grounding with Deep Semantic Clustering
Daizong Liu, Xiaoye Qu, Yinzhen Wang +5
Temporal video grounding (TVG) aims to localize a target segment in a video according to a given sentence query. Though respectable works have made decent achievements in this task…
Memory-Guided Semantic Learning Network for Temporal Sentence Grounding
Daizong Liu, Xiaoye Qu, Xing Di +3
Temporal sentence grounding (TSG) is crucial and fundamental for video understanding. Although the existing methods train well-designed deep networks with a large amount of data, w…