Search Results for author: Amir Shahroudy

Found 10 papers, 2 papers with code

NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding

2 code implementations12 May 2019 Jun Liu, Amir Shahroudy, Mauricio Perez, Gang Wang, Ling-Yu Duan, Alex C. Kot

Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition.

Action Recognition One-Shot 3D Action Recognition

Skeleton-Based Online Action Prediction Using Scale Selection Network

no code implementations8 Feb 2019 Jun Liu, Amir Shahroudy, Gang Wang, Ling-Yu Duan, Alex C. Kot

Since there are significant temporal scale variations in the observed part of the ongoing action at different time steps, a novel window scale selection method is proposed to make our network focus on the performed part of the ongoing action and try to suppress the possible incoming interference from the previous actions at each step.

Frame Skeleton Based Action Recognition

Feature Boosting Network For 3D Pose Estimation

no code implementations15 Jan 2019 Jun Liu, Henghui Ding, Amir Shahroudy, Ling-Yu Duan, Xudong Jiang, Gang Wang, Alex C. Kot

Learning a set of features that are reliable and discriminatively representative of the pose of a hand (or body) part is difficult due to the ambiguities, texture and illumination variation, and self-occlusion in the real application of 3D pose estimation.

3D Hand Pose Estimation 3D Pose Estimation

SSNet: Scale Selection Network for Online 3D Action Prediction

no code implementations CVPR 2018 Jun Liu, Amir Shahroudy, Gang Wang, Ling-Yu Duan, Alex C. Kot

As there are significant temporal scale variations of the observed part of the ongoing action at different progress levels, we propose a novel window scale selection scheme to make our network focus on the performed part of the ongoing action and try to suppress the noise from the previous actions at each time step.

Action Recognition

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

no code implementations24 Jul 2016 Jun Liu, Amir Shahroudy, Dong Xu, Gang Wang

To handle the noise and occlusion in 3D skeleton data, we introduce new gating mechanism within LSTM to learn the reliability of the sequential input data and accordingly adjust its effect on updating the long-term context information stored in the memory cell.

Action Analysis Skeleton Based Action Recognition

NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis

1 code implementation CVPR 2016 Amir Shahroudy, Jun Liu, Tian-Tsong Ng, Gang Wang

Recent approaches in depth-based human activity analysis achieved outstanding performance and proved the effectiveness of 3D representation for classification of action classes.

General Classification Skeleton Based Action Recognition

Recent Advances in Convolutional Neural Networks

no code implementations22 Dec 2015 Jiuxiang Gu, Zhenhua Wang, Jason Kuen, Lianyang Ma, Amir Shahroudy, Bing Shuai, Ting Liu, Xingxing Wang, Li Wang, Gang Wang, Jianfei Cai, Tsuhan Chen

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.

Speech Recognition

Multimodal Multipart Learning for Action Recognition in Depth Videos

no code implementations31 Jul 2015 Amir Shahroudy, Gang Wang, Tian-Tsong Ng, Qingxiong Yang

We propose a joint sparse regression based learning method which utilizes the structured sparsity to model each action as a combination of multimodal features from a sparse set of body parts.

Action Recognition Multimodal Activity Recognition

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