Understanding human behavior and activity facilitates advancement of numerous real-world
applications, and is critical for video analysis. Despite the progress of action recognition …

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 …

In this paper, we present a one-stage framework TriDet for temporal action detection.
Existing methods often suffer from imprecise boundary predictions due to the ambiguous …

Self-attention based Transformer models have demonstrated impressive results for image
classification and object detection, and more recently for video understanding. Inspired by …

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 …

Temporal action localization is an important yet challenging task in video understanding.
Typically, such a task aims at inferring both the action category and localization of the start …

Temporal action detection (TAD) aims to determine the semantic label and the temporal
interval of every action instance in an untrimmed video. It is a fundamental and challenging …

Temporal action detection is a fundamental yet challenging task in video understanding.
Video context is a critical cue to effectively detect actions, but current works mainly focus on …

Weakly-supervised temporal action localization aims to recognize and localize action
segments in untrimmed videos given only video-level action labels for training. Without the …

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