The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Learning to Estimate 3D Hand Pose from Single RGB Images
Open accessAbstract
Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand pose estimation from single depth images. In this paper, we present an approach that estimates 3D hand pose from regular RGB images. This task has far more ambiguities due to the missing depth information. To this end, we propose a deep network that learns a network-implicit 3D articulation prior. Together with detected keypoints in the images, this network yields good estimates of the 3D pose. We introduce a large scale 3D hand pose dataset based on synthetic hand models for training the involved networks. Experiments on a variety of test sets, including one on sign language recognition, demonstrate the feasibility of 3D hand pose estimation on single color images.
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Cites
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., et al. (2016) · arXiv · doi:10.48550/arxiv.1603.04467 · Cited by 9,408
Cited by
GANerated Hands for Real-Time 3D Hand Tracking from Monocular RGB
Mueller, F., Bernard, F., Sotnychenko, O., Mehta, D., Sridhar, S., Casas, D., & Theobalt, C. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00013 · Cited by 521
Learning Joint Reconstruction of Hands and Manipulated Objects
Hasson, Y., Varol, G., Tzionas, D., Kalevatykh, I., Black, M. J., Laptev, I., & Schmid, C. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01208 · Cited by 513
3D Hand Shape and Pose Estimation From a Single RGB Image
Ge, L., Ren, Z., Li, Y., Xue, Z., Wang, Y., Cai, J., & Yuan, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01109 · Cited by 458
FreiHAND: A Dataset for Markerless Capture of Hand Pose and Shape From Single RGB Images
Zimmermann, C., Ceylan, D., Yang, J., Russell, B., Argus, M. J., & Brox, T. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00090 · Cited by 445
Self-citationHOnnotate: A Method for 3D Annotation of Hand and Object Poses
Hampali, S., Rad, M., Oberweger, M., & Lepetit, V. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00326 · Cited by 422
Metadata
- Authors
- Zimmermann, C., & Brox, T.
- Venue
- 2017 IEEE International Conference on Computer Vision (ICCV)
- Publisher
- IEEE
- Published
- 2017-10
- Pages
- 4913-4921
- OpenAlex
- W2611797529
- Cited by
- 761
- References
- 1
- FWCI
- 50.68
- Type
- conference paper
- Language
- en
- Open access
- green
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