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

A graph structure is a powerful mathematical abstraction, which can not only represent
information about individuals but also capture the interactions between individuals for …

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

Abstract 3D action recognition–analysis of human actions based on 3D skeleton data–
becomes popular recently due to its succinctness, robustness, and view-invariant …

Skeleton-based human action recognition has attracted a lot of research attention during the
past few years. Recent works attempted to utilize recurrent neural networks to model the …

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 …

Designing autonomous vehicles suitable for urban environments remains an unresolved
problem. One of the major dilemmas faced by autonomous cars is how to understand the …

In this paper, we propose a novel deep learning architecture for multi-label zero-shot
learning (ML-ZSL), which is able to predict multiple unseen class labels for each input …