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

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 …

This paper addresses the challenging task of weakly-supervised video temporal grounding.
Existing approaches are generally based on the moment proposal selection framework that …

Video sentence grounding (VSG) is the task of identifying the segment of an untrimmed
video that semantically corresponds to a given natural language query. While many existing …

Existing audio-visual segmentation datasets typically focus on short-trimmed videos with
only one pixel-map annotation for a per-second video clip. In contrast for untrimmed videos …

This paper addresses the temporal sentence grounding (TSG). Although existing methods
have made decent achievements in this task, they not only severely rely on abundant video …

Joint video moment retrieval (MR) and highlight detection (HD) aims to find relevant video
moments according to the query text. Existing methods are fully supervised based on …

Temporal sentence grounding (TSG) is crucial and fundamental for video understanding.
Previous works typically model the target activity referred to the sentence query in a video by …

Temporal sentence grounding (TSG) aims to localize the temporal segment which is
semantically aligned with a natural language query in an untrimmed video. Most existing …