The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Through-Wall Human Pose Estimation Using Radio Signals
Open accessAbstract
This paper demonstrates accurate human pose estimation through walls and occlusions. We leverage the fact that wireless signals in the WiFi frequencies traverse walls and reflect off the human body. We introduce a deep neural network approach that parses such radio signals to estimate 2D poses. Since humans cannot annotate radio signals, we use state-of-the-art vision model to provide cross-modal supervision. Specifically, during training the system uses synchronized wireless and visual inputs, extracts pose information from the visual stream, and uses it to guide the training process. Once trained, the network uses only the wireless signal for pose estimation. We show that, when tested on visible scenes, the radio-based system is almost as accurate as the vision-based system used to train it. Yet, unlike vision-based pose estimation, the radio-based system can estimate 2D poses through walls despite never trained on such scenarios. Demo videos are available at our website.
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Microsoft COCO: Common Objects in Context
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Learning Spatiotemporal Features with 3D Convolutional Networks
Tran, D., Bourdev, L., Fergus, R., Torresani, L., & Paluri, M. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.510 · Cited by 9,593
Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields
Cao, Z., Simon, T., Wei, S.-E., & Sheikh, Y. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.143 · Cited by 7,539
3D Convolutional Neural Networks for Human Action Recognition
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Stacked Hourglass Networks for Human Pose Estimation
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Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
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Cited by
Knowledge Distillation: A Survey
Gou, J., Yu, B., Maybank, S. J., & Tao, D. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-021-01453-z · Cited by 3,931
Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi
Zheng, Y., Zhang, Y., Qian, K., Zhang, G., Liu, Y., Wu, C., & Yang, Z. (2019) · Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services · doi:10.1145/3307334.3326081 · Cited by 557
Monocular human pose estimation: A survey of deep learning-based methods
Chen, Y., Tian, Y., & He, M. (2020) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2019.102897 · Cited by 441
Self-citation3D Human Pose Estimation in the Wild by Adversarial Learning
Yang, W., Ouyang, W., Wang, X., Ren, J., Li, H., & Wang, X. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00551 · Cited by 406
mm-Pose: Real-Time Human Skeletal Posture Estimation Using mmWave Radars and CNNs
Sengupta, A., Jin, F., Zhang, R., & Cao, S. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.2991741 · Cited by 401
Metadata
- Authors
- Zhao, M., Li, T., Alsheikh, M. A., Tian, Y., Zhao, H., Torralba, A., & Katabi, D.
- Venue
- 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2018-06
- Pages
- 7356-7365
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2799062425
- Cited by
- 658
- References
- 52
- FWCI
- 20.08
- Type
- conference paper
- Language
- en
- Open access
- green
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- Zhao, M., Li, T., Alsheikh, M. A., Tian, Y., Zhao, H., Torralba, A., & Katabi, D. (2018). Through-Wall Human Pose Estimation Using Radio Signals. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2018.00768
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