1.8k citations · 2.6k across the 9 of their papers we have counts for
9 papers
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
Jun Liu, Amir Shahroudy, Mauricio Perez +3
Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition. The existing depth-…
Skeleton-Based Online Action Prediction Using Scale Selection Network
Jun Liu, Amir Shahroudy, Gang Wang +2
Action prediction is to recognize the class label of an ongoing activity when only a part of it is observed. In this paper, we focus on online action prediction in streaming 3D ske…
Feature Boosting Network For 3D Pose Estimation
Jun Liu, Henghui Ding, Amir Shahroudy +4
In this paper, a feature boosting network is proposed for estimating 3D hand pose and 3D body pose from a single RGB image. In this method, the features learned by the convolutiona…
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates
Jun Liu, Amir Shahroudy, Dong Xu +2
Skeleton-based human action recognition has attracted a lot of research attention during the past few years. Recent works attempted to utilize recurrent neural networks to model th…
Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition
Jun Liu, Amir Shahroudy, Dong Xu +1
3D action recognition - analysis of human actions based on 3D skeleton data - becomes popular recently due to its succinctness, robustness, and view-invariant representation. Recen…
NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis
Amir Shahroudy, Jun Liu, Tian-Tsong Ng +1
Recent approaches in depth-based human activity analysis achieved outstanding performance and proved the effectiveness of 3D representation for classification of action classes. Cu…
Deep Multimodal Feature Analysis for Action Recognition in RGB+D Videos
Amir Shahroudy, Tian-Tsong Ng, Yihong Gong +1
Single modality action recognition on RGB or depth sequences has been extensively explored recently. It is generally accepted that each of these two modalities has different streng…
Recent Advances in Convolutional Neural Networks
Jiuxiang Gu, Zhenhua Wang, Jason Kuen +9
In the last few years, deep learning has led to very good performance on a variety of problems, such as visual recognition, speech recognition and natural language processing. Amon…
Multimodal Multipart Learning for Action Recognition in Depth Videos
Amir Shahroudy, Gang Wang, Tian-Tsong Ng +1
The articulated and complex nature of human actions makes the task of action recognition difficult. One approach to handle this complexity is dividing it to the kinetics of body pa…