activity
20142022
most citedDeep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences

36 citations · 77 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

9 papers · 1 filter

cs.CV2022★ 3 cited

A Unified Multimodal De- and Re-coupling Framework for RGB-D Motion Recognition

Benjia Zhou, Pichao Wang, Jun Wan +2

Motion recognition is a promising direction in computer vision, but the training of video classification models is much harder than images due to insufficient data and considerable…

cs.CV2021

ELSA: Enhanced Local Self-Attention for Vision Transformer

Jingkai Zhou, Pichao Wang, Fan Wang +3

Self-attention is powerful in modeling long-range dependencies, but it is weak in local finer-level feature learning. The performance of local self-attention (LSA) is just on par w…

cs.CV2021★ 3 cited

Decoupling and Recoupling Spatiotemporal Representation for RGB-D-based Motion Recognition

Benjia Zhou, Pichao Wang, Jun Wan +6

Decoupling spatiotemporal representation refers to decomposing the spatial and temporal features into dimension-independent factors. Although previous RGB-D-based motion recognitio…

cs.CV2017★ 5 cited

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…

cs.CV2016★ 8 cited

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…

cs.CV2016

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…