夸张化3D高斯泼面：基于高斯曲率的卡通化人脸生成

摘要

本文提出了一种逼真且可控的人脸三维夸张化框架。我们首先采用基于本征高斯曲率的表面夸张技术，但该方法与纹理结合时易产生过度平滑的渲染效果。为此，我们引入近期被证明能生成逼真自由视角虚拟形象的三维高斯泼溅技术（3DGS）。给定多视角序列，我们提取FLAME网格，求解曲率加权泊松方程，获得其夸张化形态。然而直接对高斯体进行变形会导致效果不佳，因此需通过局部仿射变换将每帧图像扭曲至其对应的二维夸张表征，从而合成伪真实夸张图像。随后我们设计了一种交替使用真实与合成监督信号的训练方案，使单一高斯集合能够同时表征自然与夸张的虚拟形象。该方案提升了保真度，支持局部编辑，并允许连续调节夸张强度。为实现实时变形，我们引入了原始表面与夸张表面之间的高效插值方法，并通过分析证明该方法与闭式解存在有界偏差。在定量与定性评估中，我们的结果均优于现有工作，能够生成具有几何可控性的逼真夸张虚拟形象。

English

A photorealistic and controllable 3D caricaturization framework for faces is introduced. We start with an intrinsic Gaussian curvature-based surface exaggeration technique, which, when coupled with texture, tends to produce over-smoothed renders. To address this, we resort to 3D Gaussian Splatting (3DGS), which has recently been shown to produce realistic free-viewpoint avatars. Given a multiview sequence, we extract a FLAME mesh, solve a curvature-weighted Poisson equation, and obtain its exaggerated form. However, directly deforming the Gaussians yields poor results, necessitating the synthesis of pseudo-ground-truth caricature images by warping each frame to its exaggerated 2D representation using local affine transformations. We then devise a training scheme that alternates real and synthesized supervision, enabling a single Gaussian collection to represent both natural and exaggerated avatars. This scheme improves fidelity, supports local edits, and allows continuous control over the intensity of the caricature. In order to achieve real-time deformations, an efficient interpolation between the original and exaggerated surfaces is introduced. We further analyze and show that it has a bounded deviation from closed-form solutions. In both quantitative and qualitative evaluations, our results outperform prior work, delivering photorealistic, geometry-controlled caricature avatars.

夸张化3D高斯泼面：基于高斯曲率的卡通化人脸生成

CaricatureGS: Exaggerating 3D Gaussian Splatting Faces With Gaussian Curvature

摘要

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