64 citations · 323 across the 24 of their papers we have counts for
8 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…
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…
Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition: A Problem-Oriented Perspective
Jing Zhang, Wanqing Li, Philip Ogunbona +1
This paper takes a problem-oriented perspective and presents a comprehensive review of transfer learning methods, both shallow and deep, for cross-dataset visual recognition. Speci…