The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
SMPL: A Skinned Multi-Person Linear Model
Abstract
We present a learned model of human body shape and posedependent shape variation that is more accurate than previous models and is compatible with existing graphics pipelines. Our Skinned Multi-Person Linear model (SMPL) is a skinned vertexbased model that accurately represents a wide variety of body shapes in natural human poses. The parameters of the model are learned from data including the rest pose template, blend weights, pose-dependent blend shapes, identity-dependent blend shapes, and a regressor from vertices to joint locations. Unlike previous models, the pose-dependent blend shapes are a linear function of the elements of the pose rotation matrices. This simple formulation enables training the entire model from a relatively large number of aligned 3D meshes of different people in different poses. We quantitatively evaluate variants of SMPL using linear or dual-quaternion blend skinning and show that both are more accurate than a Blend- SCAPE model trained on the same data. We also extend SMPL to realistically model dynamic soft-tissue deformations. Because it is based on blend skinning, SMPL is compatible with existing rendering engines and we make it available for research purposes.
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Cites
The space of human body shapes: reconstruction and parameterization from range scans
Allen, B., Curless, B., & Popović, Z. (2003) · ACM Transactions on Graphics · doi:10.1145/882262.882311 · Cited by 723
Automatic rigging and animation of 3D characters
Baran, I., & Popović, J. (2007) · ACM Transactions on Graphics · doi:10.1145/1276377.1276467 · Cited by 455
SCAPE: shape completion and animation of people
Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., & Davis, J. (2005) · ACM SIGGRAPH 2005 Papers · doi:10.1145/1186822.1073207 · Cited by 410
A Statistical Model of Human Pose and Body Shape
Hasler, N., Stoll, C., Sunkel, M., Rosenhahn, B., & Seidel, H. ‐. (2009) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2009.01373.x · Cited by 390
Geometric skinning with approximate dual quaternion blending
Kavan, L., Collins, S., Žára, J., & O'Sullivan, C. (2008) · ACM Transactions on Graphics · doi:10.1145/1409625.1409627 · Cited by 385
James, D. L., & Twigg, C. D. (2005) · ACM Transactions on Graphics · doi:10.1145/1073204.1073206 · Cited by 361
MoSh: motion and shape capture from sparse markers
Loper, M., Mahmood, N., & Black, M. J. (2014) · ACM Transactions on Graphics · doi:10.1145/2661229.2661273 · Cited by 344
Self-citationRobinette, K. M., Blackwell, S., Daanen, H., Boehmer, M., & Fleming, S. (2002) · doi:10.21236/ada406704 · Cited by 260
Building efficient, accurate character skins from examples
Mohr, A., & Gleicher, M. (2003) · ACM Transactions on Graphics · doi:10.1145/882262.882308 · Cited by 190
Spherical blend skinning: a real-time deformation of articulated models
Kavan, L., & Žára, J. (2005) · Proceedings of the 2005 symposium on Interactive 3D graphics and games · doi:10.1145/1053427.1053429 · Cited by 184
Cited by
Romero (2017) · doi:10.1145/3130800.3130883 · Cited by 1,056
Learning from Synthetic Humans
Varol, G., Romero, J., Martin, X., Mahmood, N., Black, M. J., Laptev, I., & Schmid, C. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.492 · Cited by 908
Self-citationLearning 3D Human Dynamics From Video
Kanazawa, A., Zhang, J. Y., Felsen, P., & Malik, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00576 · Cited by 531
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
Deep Representation Learning for Human Motion Prediction and Classification
Butepage, J., Black, M. J., Kragic, D., & Kjellstrom, H. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.173 · Cited by 406
Self-citation
Metadata
- Authors
- Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., & Black, M. J.
- Venue
- Seminal Graphics Papers: Pushing the Boundaries, Volume 2
- Publisher
- ACM
- Published
- 2023-08
- Pages
- 851-866
- OpenAlex
- W4385489997
- Cited by
- 768
- References
- 20
- FWCI
- 587.39
- Type
- book chapter
- Language
- en
- Open access
- closed
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- Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., & Black, M. J. (2023). SMPL: A Skinned Multi-Person Linear Model. Seminal Graphics Papers: Pushing the Boundaries, Volume 2. https://doi.org/10.1145/3596711.3596800
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