# Generating Editable Head Avatars with 3D Gaussian GANs

arXiv: https://arxiv.org/abs/2412.19149 · HTML: https://mlsanity.com/paper/2412.19149/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 29 references that are in the map.
- First posted on arXiv 26 Dec 2024.

## Builds on (most cited first, 22 of 22)

- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Efficient Geometry-aware 3D Generative Adversarial Networks](https://mlsanity.com/paper/2112.07945/) (2021)
- [2D Gaussian Splatting for Geometrically Accurate Radiance Fields](https://mlsanity.com/paper/2403.17888/) (2024)
- [MediaPipe: A Framework for Building Perception Pipelines](https://mlsanity.com/paper/1906.08172/) (2019)
- [Modular Primitives for High-Performance Differentiable Rendering](https://mlsanity.com/paper/2011.03277/) (2020)
- [PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamics](https://mlsanity.com/paper/2311.12198/) (2023)
- [Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion](https://mlsanity.com/paper/2212.06135/) (2022)
- [General Facial Representation Learning in a Visual-Linguistic Manner](https://mlsanity.com/paper/2112.03109/) (2021)
- [NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editing](https://mlsanity.com/paper/2207.11911/) (2022)
- [Relightable Gaussian Codec Avatars](https://mlsanity.com/paper/2312.03704/) (2023)
- [Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars](https://mlsanity.com/paper/2211.11208/) (2022)
- [Generative Neural Articulated Radiance Fields](https://mlsanity.com/paper/2206.14314/) (2022)
- [Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos](https://mlsanity.com/paper/2207.11094/) (2022)
- [AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatars](https://mlsanity.com/paper/2210.06465/) (2022)
- [MeGA: Hybrid Mesh-Gaussian Head Avatar for High-Fidelity Rendering and Head Editing](https://mlsanity.com/paper/2404.19026/) (2024)
- [NeRFFaceEditing: Disentangled Face Editing in Neural Radiance Fields](https://mlsanity.com/paper/2211.07968/) (2022)
- [Single-Shot Implicit Morphable Faces with Consistent Texture Parameterization](https://mlsanity.com/paper/2305.03043/) (2023)
- [AniPortraitGAN: Animatable 3D Portrait Generation from 2D Image Collections](https://mlsanity.com/paper/2309.02186/) (2023)
- [Adaptive Super Resolution For One-Shot Talking-Head Generation](https://mlsanity.com/paper/2403.15944/) (2024)
- [What You See is What You GAN: Rendering Every Pixel for High-Fidelity Geometry in 3D GANs](https://mlsanity.com/paper/2401.02411/) (2024)
- [3D Face Modeling via Weakly-supervised Disentanglement Network joint Identity-consistency Prior](https://mlsanity.com/paper/2404.16536/) (2024)

## Built on by (most cited first, 5 of 5)

- [Unmasking Puppeteers: Leveraging Biometric Leakage to Expose Impersonation in AI-Based Videoconferencing](https://mlsanity.com/paper/2510.03548/) (2025)
- [CaricatureGS: Exaggerating 3D Gaussian Splatting Faces With Gaussian Curvature](https://mlsanity.com/paper/2601.03319/) (2026)
- [FHAvatar: Fast and High-Fidelity Reconstruction of Face-and-Hair Composable 3D Head Avatar from Few Casual Captures](https://mlsanity.com/paper/2603.23345/) (2026)
- [FaceParts: Segmentation and Editing of Gaussian Splatting](https://mlsanity.com/paper/2605.13853/) (2026)
- [COSY: Compositional 3DGS Synthesis for Disentangled Human Head Editing](https://mlsanity.com/paper/2605.24114/) (2026)

## Abstract (arXiv)

Generating animatable and editable 3D head avatars is essential for various applications in computer vision and graphics. Traditional 3D-aware generative adversarial networks (GANs), often using implicit fields like Neural Radiance Fields (NeRF), achieve photorealistic and view-consistent 3D head synthesis. However, these methods face limitations in deformation flexibility and editability, hindering the creation of lifelike and easily modifiable 3D heads. We propose a novel approach that enhances the editability and animation control of 3D head avatars by incorporating 3D Gaussian Splatting (3DGS) as an explicit 3D representation. This method enables easier illumination control and improved editability. Central to our approach is the Editable Gaussian Head (EG-Head) model, which combines a 3D Morphable Model (3DMM) with texture maps, allowing precise expression control and flexible texture editing for accurate animation while preserving identity. To capture complex non-facial geometries like hair, we use an auxiliary set of 3DGS and tri-plane features. Extensive experiments demonstrate that our approach delivers high-quality 3D-aware synthesis with state-of-the-art controllability. Our code and models are available at https://github.com/liguohao96/EGG3D.