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 …

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

Temporal Grounding is to identify specific moments or highlights from a video corresponding
to textual descriptions. Typical approaches in temporal grounding treat all video clips …

Temporal sentence grounding in video has witnessed significant advancements, but suffers
from substantial dataset bias, which undermines its generalization ability. Existing debias …

This paper addresses the challenging task of language-driven moment retrieval. Previous
methods are typically trained to localize the target moment corresponding to a single …

Temporal grounding of text descriptions in videos is a central problem in vision-language
learning and video understanding. Existing methods often prioritize accuracy over scalability …

Temporal sentence grounding (TSG) aims to locate a semantically related segment of an
untrimmed video guided by a sentence query. Since the untrimmed videos are too long …

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 …

Temporal sentence localization (TSL) aims to localize a target segment in a video according
to a given sentence query. Though respectable works have made decent achievements in …

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 …