• DOI:10.1109/CVPR.2018.00551
Corpus ID: 4811901

3D Human Pose Estimation in the Wild by Adversarial Learning

@article{Yang20183DHP,
  title={3D Human Pose Estimation in the Wild by Adversarial Learning},
  author={Wei Yang and Wanli Ouyang and X. Wang and J. Ren and Hongsheng Li and Xiaogang Wang},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={5255-5264}
}

Wei Yang, Wanli Ouyang, +3 authors Xiaogang Wang

Published 2018

Computer Science

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Recently, remarkable advances have been achieved in 3D human pose estimation from monocular images because of the powerful Deep Convolutional Neural Networks (DCNNs). Despite their success on large-scale datasets collected in the constrained lab environment, it is difficult to obtain the 3D pose annotations for in-the-wild images. Therefore, 3D human pose estimation in the wild is still a challenge. In this paper, we propose an adversarial learning framework, which distills the 3D human pose… CONTINUE READING

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