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 …

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 …

Transformer models have shown great success handling long-range interactions, making
them a promising tool for modeling video. However, they lack inductive biases and scale …

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

The recent video grounding works attempt to introduce vanilla contrastive learning into video
grounding. However, we claim that this naive solution is suboptimal. Contrastive learning …

We explore the task of language-guided video segmentation (LVS). Previous algorithms
mostly adopt 3D CNNs to learn video representation, struggling to capture long-term context …

Video moment localization aims at localizing the video segments which are most related to
the given free-form natural language query. The weakly supervised setting, where only …

The video grounding (VG) task aims to locate the queried action or event in an untrimmed
video based on rich linguistic descriptions. Existing proposal-free methods are trapped in …

Video summarization has recently engaged increasing attention in computer vision
communities. However, the scarcity of annotated data has been a key obstacle in this task …