136 citations · 823 across the 50 of their papers we have counts for
7 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…
RGB-D-based Human Motion Recognition with Deep Learning: A Survey
Pichao Wang, Wanqing Li, Philip Ogunbona +2
Human motion recognition is one of the most important branches of human-centered research activities. In recent years, motion recognition based on RGB-D data has attracted much att…
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…
Skeleton-based Action Recognition Using LSTM and CNN
Chuankun Li, Pichao Wang, Shuang Wang +2
Recent methods based on 3D skeleton data have achieved outstanding performance due to its conciseness, robustness, and view-independent representation. With the development of deep…
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,…
Large-scale Isolated Gesture Recognition Using Convolutional Neural Networks
Pichao Wang, Wanqing Li, Song Liu +3
This paper proposes three simple, compact yet effective representations of depth sequences, referred to respectively as Dynamic Depth Images (DDI), Dynamic Depth Normal Images (DDN…