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

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 …

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 …

Temporal sentence grounding aims to detect the most salient moment corresponding to the
natural language query from untrimmed videos. As labeling the temporal boundaries is labor …

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 …

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 …

Spatio-temporal video grounding aims to localize the aligned visual tube corresponding to a
language query. Existing techniques achieve such alignment by exploiting dense boundary …

Video moment localization aims at localizing the video segments which are most related to
the given free-form natural language query. The weakly supervised setting, where only …

We address the problem of localizing a specific moment described by a natural language
query. Existing works interact the query with either video frame or moment proposal, and …

We address the problem of localizing a specific moment from an untrimmed video by a
language sentence query. Generally, previous methods mainly exist two problems that are …