SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks
2021-06-21
SCANimate is an end-to-end trainable framework that takes raw 3D scans of a clothed human and turns them into an animatable avatar. These avatars are driven by pose parameters and have realistic clothing that moves and deforms naturally. SCANimate uses an implicit shape representation and does not rely on a customized mesh template or surface mesh registration.
SCANimate is an end-to-end trainable framework that takes raw 3D scans of a clothed human and turns them into an animatable avatar. These avatars are driven by pose parameters and have realistic clothing that moves and deforms naturally. SCANimate uses an implicit shape representation and does not rely on a customized mesh template or surface mesh registration.
| Author(s): | Saito, S., Yang, J., Ma, Q., Black, M. J. |
| Department(s): |
Perceiving Systems |
| Publication(s): |
{SCANimate}: Weakly Supervised Learning of Skinned Clothed Avatar Networks
|
| Authors: | Saito, S., Yang, J., Ma, Q., Black, M. J. |
| Release Date: | 2021-06-21 |
| Repository: | https://github.com/shunsukesaito/SCANimate |
