Simple and effective deep hand shape and pose regression from a single depth image

Author:

Malik Jameel,Elhayek AhmedORCID,Nunnari Fabrizio,Stricker Didier

Funder

Federal Ministry of Education and Research

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Human-Computer Interaction,General Engineering

Reference31 articles.

1. 3DAirSig: a framework for enabling in-air signatures using a multi-modal depth sensor;Malik;Sensors,2018

2. BigHand2. 2M benchmark: hand pose dataset and state of the art analysis;Yuan,2017

3. Moon G, Chang JY, Lee KM. V2V-posenet: voxel-to-voxel prediction network for accurate 3d hand and human pose estimation from a single depth map. arXiv:1711073992017.

4. Rad M, Oberweger M, Lepetit V. Feature mapping for learning fast and accurate 3D pose inference from synthetic images. arXiv:1712039042017.

5. Deephps: End-to-end estimation of 3d hand pose and shape by learning from synthetic depth;Malik,2018

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