RNN-based approaches have achieved outstanding performance on action recognition with
skeleton inputs. Currently these methods limit their inputs to coordinates of joints and …

Massive open online courses and other forms of remote education continue to increase in
popularity and reach. The ability to efficiently proctor remote online examinations is an …

Abstract Recently, Long Short-Term Memory (LSTM) has become a popular choice to model
individual dynamics for single-person action recognition. However, existing RNN models …

When we say a person is texting, can you tell the person is walking or sitting? Emphatically,
no. In order to solve this incomplete representation problem, this paper presents a sub …

In this paper, we address the problem of human interaction recognition. We propose a novel
compositional interaction descriptor to represent complex human interactions containing …

Moving object detection is a widely used and important research topic in computer vision
and video processing. Foreground aperture, ghosting and sudden illumination changes are …

We propose a novel approach toward event detection in real-world continuous video
sequences. The method: 1) is able to model arbitrary-order non-Markovian dependences in …

As an important research topic in computer vision, abnormal detection has gained more and
more attention. In order to detect abnormal events effectively, we propose a novel method …

近年来, 卷积神经网络(CNN) 已经成为很多科学领域的研究热点之一. 卷积神经网络作为一种
深度模型可以直接作用于原始输入, 不需要手动设计特征描述子. 与传统神经网络相比识别效果 …

In this paper, we propose a novel model for recognizing human interaction in videos via
discriminative patches. Each frame is represented as a set of mid-level discriminative …