CaricatureGS: Exaggerating 3D Gaussian Splatting Faces With Gaussian Curvature
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.
6960e7365b7998385e6396e3
Eldad Matmon
claimed_verified
2026-01-09T15:45:52.792Z
6761f183e5b85d453550147a
/avatars/b071c0b1ee46955ee5ff38a3c3df457f.svg
EldadMat
eldad929
user
eldad929
6960e7365b7998385e6396e4
Amit Bracha
6960e7365b7998385e6396e5
Noam Rotstein
claimed_verified
2026-01-12T10:36:06.891Z
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/avatars/63125ce8a1e20b8c6e836f223d24284f.svg
noam rotstein
noamrot
user
noamrot
6960e7365b7998385e6396e6
Ron Kimmel
CaricatureGS: Exaggerating 3D Gaussian Splatting Faces With Gaussian Curvature
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.
A photorealistic 3D caricaturization framework combines Gaussian curvature-based surface exaggeration with 3D Gaussian Splatting to create controllable, realistic avatars with improved fidelity and real-time deformation capabilities.
3D Gaussian Splatting FLAME mesh curvature-weighted Poisson equation pseudo-ground-truth caricature images local affine transformations real-time deformations closed-form solutions