64 citations · 113 across the 5 of their papers we have counts for
5 papers · 1 filter
Cooperative Training of Deep Aggregation Networks for RGB-D Action Recognition
Pichao Wang, Wanqing Li, Jun Wan +2
A novel deep neural network training paradigm that exploits the conjoint information in multiple heterogeneous sources is proposed. Specifically, in a RGB-D based action recognitio…
Learning Approximate Stochastic Transition Models
Yuhang Song, Christopher Grimm, Xianming Wang +1
We examine the problem of learning mappings from state to state, suitable for use in a model-based reinforcement-learning setting, that simultaneously generalize to novel states an…
Joint Geometrical and Statistical Alignment for Visual Domain Adaptation
Jing Zhang, Wanqing Li, Philip Ogunbona
This paper presents a novel unsupervised domain adaptation method for cross-domain visual recognition. We propose a unified framework that reduces the shift between domains both st…
Investigation of Different Skeleton Features for CNN-based 3D Action Recognition
Zewei Ding, Pichao Wang, Philip O. Ogunbona +1
Deep learning techniques are being used in skeleton based action recognition tasks and outstanding performance has been reported. Compared with RNN based methods which tend to over…
Scene Flow to Action Map: A New Representation for RGB-D based Action Recognition with Convolutional Neural Networks
Pichao Wang, Wanqing Li, Zhimin Gao +3
Scene flow describes the motion of 3D objects in real world and potentially could be the basis of a good feature for 3D action recognition. However, its use for action recognition,…