12 papers
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…
Fewer Steps, Better Performance: Efficient Cross-Modal Clip Trimming for Video Moment Retrieval Using Language
Xiang Fang, Daizong Liu, Wanlong Fang +5
Given an untrimmed video and a sentence query, video moment retrieval using language (VMR) aims to locate a target query-relevant moment. Since the untrimmed video is overlong, alm…
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…
Multi-Pair Temporal Sentence Grounding via Multi-Thread Knowledge Transfer Network
Xiang Fang, Wanlong Fang, Changshuo Wang +5
Given some video-query pairs with untrimmed videos and sentence queries, temporal sentence grounding (TSG) aims to locate query-relevant segments in these videos. Although previous…
You Can Ground Earlier than See: An Effective and Efficient Pipeline for Temporal Sentence Grounding in Compressed Videos
Xiang Fang, Daizong Liu, Pan Zhou +1
Given an untrimmed video, temporal sentence grounding (TSG) aims to locate a target moment semantically according to a sentence query. Although previous respectable works have made…