Drivable 3D Gaussian Avatars
Wojciech Zielonka Timur Bagautdinov Shunsuke Saito Michael Zollhöfer Justus Thies Javier Romero
We present Drivable 3D Gaussian Avatars (D3GA), the first 3D controllable
model for human bodies rendered with Gaussian splats. Current photorealistic
drivable avatars require either accurate 3D registrations during training,
dense input images during testing, or both. The ones based on neural radiance
fields also tend to be prohibitively slow for telepresence applications. This
work uses the recently presented 3D Gaussian Splatting (3DGS) technique to
render realistic humans at real-time framerates, using dense calibrated
multi-view videos as input. To deform those primitives, we depart from the
commonly used point deformation method of linear blend skinning (LBS) and use a
classic volumetric deformation method: cage deformations. Given their smaller
size, we drive these deformations with joint angles and keypoints, which are
more suitable for communication applications. Our experiments on nine subjects
with varied body shapes, clothes, and motions obtain higher-quality results
than state-of-the-art methods when using the same training and test data.