Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Although widely used in many applications, accurate and efficient human action recognition
remains a challenging area of research in the field of computer vision. Most recent surveys …

This work focuses on the task of elderly activity recognition, which is a challenging task due
to the existence of individual actions and human-object interactions in elderly activities …

Temporal modeling is key for action recognition in videos. It normally considers both short-
range motions and long-range aggregations. In this paper, we propose a Temporal …

Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …

On public benchmarks, current action recognition techniques have achieved great success.
However, when used in real-world applications, eg sport analysis, which requires the …

Human action Recognition for unknown views, is a challenging task. We propose a deep
view-invariant human action recognition framework, which is a novel integration of two …

Temporal action detection aims to locate the boundaries of action in the video. The current
method based on boundary matching enumerates and calculates all possible boundary …

Two-stream convolutional neural networks have been widely applied to action recognition.
However, two-stream networks are usually adopted to capture spatial information and …

The success of deep neural networks generally requires a vast amount of training data to be
labeled, which is expensive and unfeasible in scale, especially for video collections. To …