Real-time 3D hand pose estimation with 3D convolutional neural networks
In this paper, we present a novel method for real-time 3D hand pose estimation from single depth images using 3D Convolutional Neural Networks (CNNs). Image-based features extracted by 2D CNNs are not directly suitable for 3D hand pose estimation due to the lack of 3D spatial information. Our propos...
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Main Authors: | Ge, Liuhao, Liang, Hui, Yuan, Junsong, Thalmann, Daniel |
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Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2019
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/106412 http://hdl.handle.net/10220/47912 http://dx.doi.org/10.1109/TPAMI.2018.2827052 |
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Institution: | Nanyang Technological University |
Language: | English |
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