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

Many real-world video-text tasks involve different levels of granularity, such as frames and
words, clip and sentences or videos and paragraphs, each with distinct semantics. In this …

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 …

Weakly-supervised vision-language grounding aims to localize a target moment in a video
or a specific region in an image according to the given sentence query, where only video …

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 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 …

The task of weakly supervised temporal sentence grounding aims at finding the
corresponding temporal moments of a language description in the video, given video …

Temporal video grounding aims to localize the target segment which is semantically aligned
with the given sentence in an untrimmed video. Existing methods can be divided into two …

Abstract Dense Event Captioning (DEC) aims to jointly localize and describe multiple events
of interest in untrimmed videos, which is an advancement of the conventional video …

Video moment retrieval has progressed significantly over the past few years, aiming to
search the moment that is most relevant to a given natural language query. Most existing …