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 …

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 addresses the problem of text-to-video temporal grounding, which aims to
identify the time interval in a video semantically relevant to a text query. We tackle this …

We aim to address the problem of Natural Language Video Localization (NLVL)—localizing
the video segment corresponding to a natural language description in a long and untrimmed …

Temporal grounding aims to localize a video moment which is semantically aligned with a
given natural language query. Existing methods typically apply a detection or regression …

Both Minsky's" society of mind" and Schmidhuber's" learning to think" inspire diverse
societies of large multimodal neural networks (NNs) that solve problems by interviewing …

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 in videos aims to detect and localize one target video
segment, which semantically corresponds to a given sentence. Existing methods mainly …