Higher dimensional data such as video and 3D are the leading edge of multimedia retrieval
and computer vision research. In this survey, we give a comprehensive overview and key …

Over the past two decades, human action recognition from video has been an important
area of research in computer vision. Its applications include surveillance systems, human …

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 …

We present a deep-learning framework for real-time multiple spatio-temporal (S/T) action
localisation and classification. Current state-of-the-art approaches work offline, and are too …

In this paper, we present a novel approach of human activity prediction. Human activity
prediction is a probabilistic process of inferring ongoing activities from videos only …

This paper provides a comprehensive survey for activity recognition in video surveillance. It
starts with a description of simple and complex human activity, and various applications. The …

In this work, we aim to address the problem of human interaction recognition in videos by
exploring the long-term inter-related dynamics among multiple persons. Recently, Long …

Local video features provide state-of-the-art performance for action recognition. While the
accuracy of action recognition has been continuously improved over the recent years, the …

In contrast to the widely studied problem of recognizing an action given a complete
sequence, action anticipation aims to identify the action from only partially available videos …

The existing action recognition methods are mainly based on clip-level classifiers such as
two-stream CNNs or 3D CNNs, which are trained from the randomly selected clips and …