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3D Gaussian Blendshapes for Head Avatar Animation

About

We introduce 3D Gaussian blendshapes for modeling photorealistic head avatars. Taking a monocular video as input, we learn a base head model of neutral expression, along with a group of expression blendshapes, each of which corresponds to a basis expression in classical parametric face models. Both the neutral model and expression blendshapes are represented as 3D Gaussians, which contain a few properties to depict the avatar appearance. The avatar model of an arbitrary expression can be effectively generated by combining the neutral model and expression blendshapes through linear blending of Gaussians with the expression coefficients. High-fidelity head avatar animations can be synthesized in real time using Gaussian splatting. Compared to state-of-the-art methods, our Gaussian blendshape representation better captures high-frequency details exhibited in input video, and achieves superior rendering performance.

Shengjie Ma, Yanlin Weng, Tianjia Shao, Kun Zhou• 2024

Related benchmarks

TaskDatasetResultRank
Self-ReenactmentHDTF
PSNR27.81
35
Self-ReenactmentINSTA
PSNR29.64
19
Audio-Video SynchronizationCross-driven (Audio IV)
Sync Error4.149
10
Audio-Video SynchronizationCross-driven Audio II
Sync4.459
10
Audio-Video SynchronizationCross-driven (Audio III)
Sync Error4.648
10
Audio-Video SynchronizationCross-driven (Audio I)
Sync Error4.762
10
Talking Head GenerationMEAD self-driven
FID32.33
10
Head Avatar ReconstructionINSTA dataset (test)
PSNR (bala)33.21
8
Head Avatar ReconstructionGaussianBlendShapes (test)
PSNR (Subject 1)33.14
8
Head Avatar RenderingINSTA
Inverse MAE98
7
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