36 citations · 73 across the 8 of their papers we have counts for
8 papers
Contrastive Positive Mining for Unsupervised 3D Action Representation Learning
Haoyuan Zhang, Yonghong Hou, Wenjing Zhang +1
Recent contrastive based 3D action representation learning has made great progress. However, the strict positive/negative constraint is yet to be relaxed and the use of non-self po…
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…
Action Recognition Based on Joint Trajectory Maps with Convolutional Neural Networks
Pichao Wang, Wanqing Li, Chuankun Li +1
Convolutional Neural Networks (ConvNets) have recently shown promising performance in many computer vision tasks, especially image-based recognition. How to effectively apply ConvN…
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks
Pichao Wang, Zhaoyang Li, Yonghong Hou +1
Recently, Convolutional Neural Networks (ConvNets) have shown promising performances in many computer vision tasks, especially image-based recognition. How to effectively use ConvN…
Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks
Pichao Wang, Wanqing Li, Song Liu +3
This paper addresses the problem of continuous gesture recognition from sequences of depth maps using convolutional neutral networks (ConvNets). The proposed method first segments…
Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
Pichao Wang, Wanqing Li, Zhimin Gao +3
Recently, deep learning approach has achieved promising results in various fields of computer vision. In this paper, a new framework called Hierarchical Depth Motion Maps (HDMM) +…