Video moment localization, also known as video moment retrieval, aims to search a target
segment within a video described by a given natural language query. Beyond the task of …

Temporal sentence grounding in videos (TSGV), aka, natural language video localization
(NLVL) or video moment retrieval (VMR), aims to retrieve a temporal moment that …

We tackle the task of video moment retrieval (VMR), which aims to localize a specific
moment in a video according to a textual query. Existing methods primarily model the …

This paper addresses the problem of temporal sentence grounding (TSG), which aims to
identify the temporal boundary of a specific segment from an untrimmed video by a sentence …

The recent and increasing interest in video-language research has driven the development
of large-scale datasets that enable data-intensive machine learning techniques. In …

This paper targets at fast video moment retrieval (fast VMR), aiming to localize the target
moment efficiently and accurately as queried by a given natural language sentence. We …

Recent DETR-based video grounding models have made the model directly predict moment
timestamps without any hand-crafted components, such as a pre-defined proposal or non …

Given an untrimmed video, temporal sentence grounding (TSG) aims to locate a target
moment semantically according to a sentence query. Although previous respectable works …

The recent video grounding works attempt to introduce vanilla contrastive learning into video
grounding. However, we claim that this naive solution is suboptimal. Contrastive learning …

Abstract Video-Text Pre-training (VTP) aims to learn transferable representations for various
downstream tasks from large-scale web videos. To date, almost all existing VTP methods …