activity
20192022
most citedLearning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching

27 citations · 44 across the 5 of their papers we have counts for

collaborators

6 papers

eess.IV2022

Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks

Wei Peng, Li Feng, Guoying Zhao +1

The inherent slow imaging speed of Magnetic Resonance Image (MRI) has spurred the development of various acceleration methods, typically through heuristically undersampling the MRI…

cs.LG202111 cited

Hyperbolic Deep Neural Networks: A Survey

Wei Peng, Tuomas Varanka, Abdelrahman Mostafa +2

Recently, there has been a rising surge of momentum for deep representation learning in hyperbolic spaces due to theirhigh capacity of modeling data like knowledge graphs or synony…

cs.CV20202 cited

2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework

Haoyu Chen, Zitong Yu, Xin Liu +3

To address the problem of training on small datasets for action recognition tasks, most prior works are either based on a large number of training samples or require pre-trained mo…

cs.CV20204 cited

Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition

Wei Peng, Jingang Shi, Zhaoqiang Xia +1

Graph Convolutional Networks (GCNs) have already demonstrated their powerful ability to model the irregular data, e.g., skeletal data in human action recognition, providing an exci…

cs.CV201927 cited

Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching

Wei Peng, Xiaopeng Hong, Haoyu Chen +1

Human action recognition from skeleton data, fueled by the Graph Convolutional Network (GCN), has attracted lots of attention, due to its powerful capability of modeling non-Euclid…

eess.IV2019

Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement

Zitong Yu, Wei Peng, Xiaobai Li +2

Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications (e.g., remote healthcare). Existing rPPG…