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 …

Real-world data typically follow a long-tailed distribution, where a few majority categories
occupy most of the data while most minority categories contain a limited number of samples …

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 …

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

Abstract Weakly-Supervised Video Grounding (WSVG) aims to localize events of interest in
untrimmed videos with only video-level annotations. To date, most of the state-of-the-art …

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

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

Video grounding, the process of identifying a specific moment in an untrimmed video based
on a natural language query, has become a popular topic in video understanding. However …

Current methods for text-to-video retrieval (T2VR) are trained and tested on video-captioning
oriented datasets such as MSVD, MSR-VTT and VATEX. A key property of these datasets is …