Abstract
We present a learned model of human body shape and pose-dependent 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 vertex-based 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…
Citation impact
- FWCI
- 65.64
- Percentile
- 100%
- References
- 43
Authors
5- MLMatthew LoperCorresponding
Max Planck Institute for Intelligent Systems
- NMNaureen Mahmood
Max Planck Institute for Intelligent Systems
- JRJavier Romero
Max Planck Institute for Intelligent Systems
- GPGerard Pons‐Moll
Max Planck Institute for Intelligent Systems
- MJMichael J. Black
Max Planck Institute for Intelligent Systems
Topics & keywords
- Skinning
- Computer science
- Computer graphics
- Rendering (computer graphics)
- Polygon mesh
- Vertex (graph theory)
- Artificial intelligence
- Virtual reality