We present a novel framework for generating photorealistic 3D human head and
subsequently manipulating and reposing them with remarkable flexibility. The
proposed approach leverages an implicit function representation of 3D human
heads, employing 3D Gaussians anchored on a parametric face model. To enhance
representational capabilities and encode spatial information, we embed a
lightweight tri-plane payload within each Gaussian rather than directly storing
color and opacity. Additionally, we parameterize the Gaussians in a 2D UV space
via a 3DMM, enabling effective utilization of the diffusion model for 3D head
avatar generation. Our method facilitates the creation of diverse and realistic
3D human heads with fine-grained editing over facial features and expressions.
Extensive experiments demonstrate the effectiveness of our method.

我们提出了一个新颖的框架，用于生成逼真的 3D 人头，并以卓越的灵活性操纵和更改它们。

Gaussian3Diff：3D 高斯扩散用于 3D 全头部合成与编辑

Gaussian3Diff: 3D Gaussian Diffusion for 3D Full Head Synthesis and  Editing

Manipulating training data leads to robust neural models for MT.

通过操纵训练数据可得到鲁棒的用于 MT 的神经模型。