Multi-virtual View Scoring Network for 3D Hand Pose Estimation from a Single Depth Image
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9109-9_15
Reference31 articles.
1. Tompson, J., Stein, M., Lecun, Y., et al.: Re.-time continuous pose recovery of human hands using convolutional networks. ACM Trans. Graph. 33(5), 1–10 (2014)
2. Tang, D., Chang, H.J., Tejani, A., et al.: Latent regression forest: structured estimation of 3D articulated hand posture. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition. IEEE (2014)
3. Sun, X., Wei, Y., Liang, S., et al.: Cascaded hand pose regression. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE (2015)
4. Yuan, S., Ye, Q., Garcia-Hernando, G., et al.: The 2017 Hands in the Million Challenge on 3D Hand Pose Estimation. https://doi.org/10.48550/arXiv.1707.02237 (2017)
5. Xiong, F., Zhang, B., Xiao, Y., et al.: A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image (2019)
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