Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Human activity recognition has attracted enormous research interest thanks to its
fundamental importance in several domains spanning from health-care to security, safety …

Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …

Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …

Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …

Group activity recognition is a crucial yet challenging problem, whose core lies in fully
exploring spatial-temporal interactions among individuals and generating reasonable group …

Humans navigate crowded spaces such as a university campus by following common sense
rules based on social etiquette. In this paper, we argue that in order to enable the design of …

Modeling relation between actors is important for recognizing group activity in a multi-person
scene. This paper aims at learning discriminative relation between actors efficiently using …

This paper strives to recognize individual actions and group activities from videos. While
existing solutions for this challenging problem explicitly model spatial and temporal …

This article aims to tackle the problem of group activity recognition in the multiple-person
scene. To model the group activity with multiple persons, most long short-term memory …