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 …

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

We consider the problem of localizing a spatio-temporal tube in a video corresponding to a
given text query. This is a challenging task that requires the joint and efficient modeling of …

We study visually grounded VideoQA in response to the emerging trends of utilizing
pretraining techniques for video-language understanding. Specifically by forcing vision …

Tremendous progress has been made in recent years in developing better image captioning
models, yet most of them rely on a separate object detector to extract regional features …

Video grounding aims to localize a moment from an untrimmed video for a given textual
query. Existing approaches focus more on the alignment of visual and language stimuli with …

This paper addresses the problem of temporal sentence grounding (TSG), which aims to
identify the temporal boundary of a specific segment from an untrimmed video by a sentence …

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 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 …