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Human3D+

Human 3D pose estimation from a single image is a challenging task with numerous applications. Convolutional Neural Networks (CNNs) have recently achieved superior performance on the task of 2D pose estimation from a single image, by training on images with 2D annotations collected by crowd sourcing. This suggests that similar success could be achieved for direct estimation of 3D poses.

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Cite this as

Wenzheng Chen, Changhe Tu, Huan Wang, Dani Lischinski, Yangyan Li, Hao Su, Zhenhua Wang, Daniel Cohen-Or, Baoquan Chen (2024). Dataset: Human3D+. https://doi.org/10.57702/vv3y7e26

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Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.1604.02703
Author Wenzheng Chen
More Authors
Changhe Tu
Huan Wang
Dani Lischinski
Yangyan Li
Hao Su
Zhenhua Wang
Daniel Cohen-Or
Baoquan Chen
Homepage http://irc.cs.sdu.edu.cn/Deep3DPose/