Video moment retrieval pursues an efficient and generalized solution to identify the specific
temporal segments within an untrimmed video that correspond to a given language …

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

The recent and increasing interest in video-language research has driven the development
of large-scale datasets that enable data-intensive machine learning techniques. In …

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 …

Temporal grounding in videos aims to localize one target video segment that semantically
corresponds to a given query sentence. Thanks to the semantic diversity of natural language …

Abstract Weakly-Supervised Object Detection (WSOD) and Localization (WSOL), ie.,
detecting multiple and single instances with bounding boxes in an image using image-level …

Video activity localisation has recently attained increasing attention due to its practical
values in automatically localising the most salient visual segments corresponding to their …

Temporal sentence grounding in videos (TSGV), which aims at localizing one target
segment from an untrimmed video with respect to a given sentence query, has drawn …

Given an untrimmed video and a natural language query, Natural Language Video
Localization (NLVL) aims to identify the video moment described by the query. To address …

Video temporal grounding aims to identify video segments within untrimmed videos that are
most relevant to a given natural language query. Existing video temporal localization models …