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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.

Data and Resources

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

DOI retrieved: December 16, 2024

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/