Abstract
This work addresses a novel and challenging problem of estimating the full 3D hand shape and pose from a single RGB image. Most current methods in 3D hand analysis from monocular RGB images only focus on estimating the 3D locations of hand keypoints, which cannot fully express the 3D shape of hand. In contrast, we propose a Graph Convolutional Neural Network (Graph CNN) based method to reconstruct a full 3D mesh of hand surface that contains richer information of both 3D hand shape and pose. To train networks with full supervision, we create a large-scale synthetic dataset containing both ground truth 3D meshes and 3D poses. When fine-tuning the networks on real-world datasets without 3D ground truth, we propose a weakly-supervised approach by leveraging the depth map as a weak supervision in training. Through extensive evaluations on our proposed new datasets and two public datasets, we show that our proposed method can produce accurate and reasonable 3D hand mesh, and can achieve superior 3D hand pose estimation accuracy when compared with state-of-the-art methods.
Original language | English |
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Title of host publication | Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019 |
Editors | Abhinav Gupta, Derek Hoiem, Gang Hua, Zhuowen Tu |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 10833-10842 |
Number of pages | 10 |
ISBN (Electronic) | 9781728132938 |
ISBN (Print) | 9781728132945 |
DOIs | |
Publication status | Published - 2019 |
Externally published | Yes |
Event | IEEE Conference on Computer Vision and Pattern Recognition 2019 - Long Beach, United States of America Duration: 16 Jun 2019 → 20 Jun 2019 Conference number: 32nd http://cvpr2019.thecvf.com/ https://ieeexplore.ieee.org/xpl/conhome/8938205/proceeding (Proceedings) |
Conference
Conference | IEEE Conference on Computer Vision and Pattern Recognition 2019 |
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Abbreviated title | CVPR 2019 |
Country | United States of America |
City | Long Beach |
Period | 16/06/19 → 20/06/19 |
Internet address |
Keywords
- 3D from Single Image
- And Body Pose
- Face
- Gesture