Splatshot: 3D Face Avatar Generation from a Single Unconstrained Photo
Reconstructing a photorealistic 3D face avatar from a single unconstrained photograph is challenging: feed-forward 3D Gaussian Splatting (3DGS) models degrade on out-of-distribution inputs, while pretrained diffusion models produce high-fidelity images but lack multi-view consistency. We observe that these paradigms are fundamentally complementary: explicit 3D representations guarantee geometric consistency, whereas 2D diffusion priors ensure photorealism. Building on this, we propose SplatShot, a training-free framework that couples these representations directly within the denoising process. Given a base 3DGS face model and a single reference image, we jointly denoise all target views u...
| Authors | Hao Liang, Zhixuan Ge, Soumendu Majee et al. |
|---|---|
| Primary category | cs.CV |
| Published | 31 May 2026 |
| Last updated at source | 31 May 2026 |
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