Temporal action proposal generation is an challenging and promising task which aims to
locate temporal regions in real-world videos where action or event may occur. Current …

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 …

Most state-of-the-art action localization systems process each action proposal individually,
without explicitly exploiting their relations during learning. However, the relations between …

Temporal action proposal generation is an important yet challenging problem, since
temporal proposals with rich action content are indispensable for analysing real-world …

We propose TAL-Net, an improved approach to temporal action localization in video that is
inspired by the Faster R-CNN object detection framework. TAL-Net addresses three key …

Temporally localizing actions in a video is a fundamental challenge in video understanding.
Most existing approaches have often drawn inspiration from image object detection and …

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 …

We address the problem of activity detection in continuous, untrimmed video streams. This is
a difficult task that requires extracting meaningful spatio-temporal features to capture …

Temporal action localization is an important yet challenging problem. Given a long,
untrimmed video consisting of multiple action instances and complex background contents …

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 …