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

In this work, we present a new intuitive, end-to-end approach for temporal action detection in
untrimmed videos. We introduce our new architecture for Single-Stream Temporal Action …

Deep learning has been demonstrated to achieve excellent results for image classification
and object detection. However, the impact of deep learning on video analysis (eg action …

Abstract Temporal Action Detection (TAD) aims to accurately capture each action interval in
an untrimmed video and to understand human actions. This paper comprehensively surveys …

Detecting actions in untrimmed videos is an important yet challenging task. In this paper, we
present the structured segment network (SSN), a novel framework which models the …

Temporal action detection in long videos is an important problem. State-of-the-art methods
address this problem by applying action classifiers on sliding windows. Although sliding …

Existing approaches for spatio-temporal action detection in videos are limited by the spatial
extent and temporal duration of the actions. In this paper, we present a modular system for …

Online action detection aims to detect a current action from an untrimmed, streaming video,
where only current and past frames are available. Recent methods for online action …

Temporal action detection is a very important yet challenging problem, since videos in real
applications are usually long, untrimmed and contain multiple action instances. This …

Detecting activities in untrimmed videos is an important but challenging task. The
performance of existing methods remains unsatisfactory, eg, they often meet difficulties in …