3D Human Pose Estimation from RGB-D Images Using Deep Learning Method-Reference-Cited by-同舟云学术

3D Human Pose Estimation from RGB-D Images Using Deep Learning Method

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 International Conference on Sensors, Signal and Image Processing - SSIP 2018
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Author:

Chun Junchul¹,Park Seohee¹,Ji Myunggeun¹

Affiliation:

1. CS Department, Kyonggi Univ., Yeongtong-gu, Suwon, S. Korea

Publisher

ACM Press

Reference19 articles.

1. Grant, Jason M., and Patrick J. Flynn, 2017. Crowd Scene Understanding from Video: A Survey, ACM Trans. on Multi. Comp, Comm., and App. (TOMM), 13, 2 (2017), 1--23. DOI= https://doi.org/10.0.4.121/3052930

2. Zhang, S., et al. 2017. Vision-Based Human Activity Recognition: A Review, Journal of Healthcare Engineering, Vol 2017 (2017), 1--31.

3. Gong, Wenjuan, et al. 2016. Human Pose Estimation from Monocular Images: A Comprehensive Survey, Sensors, 16, 12 (2016), 1--36. DIO=https://doi.org/10.3390/s16121966

4. Wei, Shih-En, et al. 2016. Convolutional pose machines, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. (2016), 4724--4732. DOI= https://doi.org/10.1109/CVPR.2016.511

5. Papandreou, George, et al. 2017. Towards Accurate Multi-Person Pose Estimation in the Wild. arXiv preprint arXiv:1701.01779, (2017), DOI=https://arxiv.org/abs/1701.01779

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