A hybrid classification-regression approach for 3D hand pose estimation using graph convolutional networks

Author:

Kourbane IkramORCID,Genc YakupORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference46 articles.

1. A multi-branch hand pose estimation network with joint-wise feature extraction and fusion;Li;Signal Process., Image Commun.,2020

2. Chengde Wan, Thomas Probst, Luc Van Gool, Angela Yao, Crossing nets: Combining gans and vaes with a shared latent space for hand pose estimation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 680–689.

3. Shile Li, Dongheui Lee, Point-to-pose voting based hand pose estimation using residual permutation equivariant layer, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, pp. 11927–11936.

4. Markus Oberweger, Vincent Lepetit, Deepprior++: Improving fast and accurate 3d hand pose estimation, in: Proceedings of the IEEE International Conference on Computer Vision Workshops, 2017, pp. 585–594.

5. Hierarchical neural network for hand pose estimation;Chen;Signal Process., Image Commun.,2020

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. 3D Hand Pose Estimation Using Semantic Dynamic Hypergraph Convolutional Networks;Journal of Shanghai Jiaotong University (Science);2024-01-25

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