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 …

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 …

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

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 …

Given an untrimmed video and a sentence query, video moment retrieval using language
(VMR) aims to locate a target query-relevant moment. Since the untrimmed video is …

Video moment retrieval aims to retrieve a target moment from an untrimmed video that
semantically corresponds to the given language query. Existing methods commonly treat it …

Temporal sentence grounding (TSG) is an important yet challenging task in multimedia
information retrieval. Although previous TSG methods have achieved decent performance …

Temporal sentence grounding (TSG) is crucial and fundamental for video understanding.
Although existing methods train well-designed deep networks with large amount of data, we …

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 …