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 …

We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It
offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household …

Abstract Video Temporal Grounding (VTG), which aims to ground target clips from videos
(such as consecutive intervals or disjoint shots) according to custom language queries (eg …

Abstract Video-Language Pretraining (VLP), which aims to learn transferable representation
to advance a wide range of video-text downstream tasks, has recently received increasing …

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 …

Detecting customized moments and highlights from videos given natural language (NL) user
queries is an important but under-studied topic. One of the challenges in pursuing this …

Recently, video moment retrieval and highlight detection (MR/HD) are being spotlighted as
the demand for video understanding is drastically increased. The key objective of MR/HD is …

Temporal action proposal generation is an important and challenging task in video
understanding, which aims at detecting all temporal segments containing action instances of …

While large-scale image-text pretrained models such as CLIP have been used for multiple
video-level tasks on trimmed videos, their use for temporal localization in untrimmed videos …