# One2Avatar: Generative Implicit Head Avatar For Few-shot User Adaptation

arXiv: https://arxiv.org/abs/2402.11909 · HTML: https://mlsanity.com/paper/2402.11909/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 35 references that are in the map.
- First posted on arXiv 19 Feb 2024.

## Builds on (most cited first, 23 of 23)

- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Efficient Geometry-aware 3D Generative Adversarial Networks](https://mlsanity.com/paper/2112.07945/) (2021)
- [VoxCeleb2: Deep Speaker Recognition](https://mlsanity.com/paper/1806.05622/) (2018)
- [VoxCeleb: a large-scale speaker identification dataset](https://mlsanity.com/paper/1706.08612/) (2017)
- [pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis](https://mlsanity.com/paper/2012.00926/) (2020)
- [StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis](https://mlsanity.com/paper/2110.08985/) (2021)
- [Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction](https://mlsanity.com/paper/2012.03065/) (2020)
- [Pivotal Tuning for Latent-based Editing of Real Images](https://mlsanity.com/paper/2106.05744/) (2021)
- [GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation](https://mlsanity.com/paper/2112.08867/) (2021)
- [Deep Appearance Models for Face Rendering](https://mlsanity.com/paper/1808.00362/) (2018)
- [Optimizing the Latent Space of Generative Networks](https://mlsanity.com/paper/1707.05776/) (2017)
- [RigNeRF: Fully Controllable Neural 3D Portraits](https://mlsanity.com/paper/2206.06481/) (2022)
- [Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars](https://mlsanity.com/paper/2211.11208/) (2022)
- [KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints](https://mlsanity.com/paper/2205.04992/) (2022)
- [Real-Time Radiance Fields for Single-Image Portrait View Synthesis](https://mlsanity.com/paper/2305.02310/) (2023)
- [AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatars](https://mlsanity.com/paper/2210.06465/) (2022)
- [Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos](https://mlsanity.com/paper/2304.01436/) (2023)
- [Preface: A Data-driven Volumetric Prior for Few-shot Ultra High-resolution Face Synthesis](https://mlsanity.com/paper/2309.16859/) (2023)
- [OmniAvatar: Geometry-Guided Controllable 3D Head Synthesis](https://mlsanity.com/paper/2303.15539/) (2023)
- [Self-Supervised Geometry-Aware Encoder for Style-Based 3D GAN Inversion](https://mlsanity.com/paper/2212.07409/) (2022)
- [DINER: Depth-aware Image-based NEural Radiance fields](https://mlsanity.com/paper/2211.16630/) (2022)

## Built on by (most cited first, 14 of 14)

- [Avat3r: Large Animatable Gaussian Reconstruction Model for High-fidelity 3D Head Avatars](https://mlsanity.com/paper/2502.20220/) (2025)
- [HeadGAP: Few-Shot 3D Head Avatar via Generalizable Gaussian Priors](https://mlsanity.com/paper/2408.06019/) (2024)
- [Synthetic Prior for Few-Shot Drivable Head Avatar Inversion](https://mlsanity.com/paper/2501.06903/) (2025)
- [SEGA: Drivable 3D Gaussian Head Avatar from a Single Image](https://mlsanity.com/paper/2504.14373/) (2025)
- [FlexAvatar: Learning Complete 3D Head Avatars with Partial Supervision](https://mlsanity.com/paper/2512.15599/) (2025)
- [HairCUP: Hair Compositional Universal Prior for 3D Gaussian Avatars](https://mlsanity.com/paper/2507.19481/) (2025)
- [UIKA: Fast Universal Head Avatar from Pose-Free Images](https://mlsanity.com/paper/2601.07603/) (2026)
- [FlexAvatar: Flexible Large Reconstruction Model for Animatable Gaussian Head Avatars with Detailed Deformation](https://mlsanity.com/paper/2512.17717/) (2025)
- [AvatarPointillist: AutoRegressive 4D Gaussian Avatarization](https://mlsanity.com/paper/2604.04787/) (2026)
- [Low-Rank Head Avatar Personalization with Registers](https://mlsanity.com/paper/2506.01935/) (2025)
- [3DRealHead: Few-Shot Detailed Head Avatar](https://mlsanity.com/paper/2604.13171/) (2026)
- [Self-Learning Expression Deformations for Data-Efficient Gaussian Avatars](https://mlsanity.com/paper/2606.05912/) (2026)
- [FA-LAM: Focus-Aware Large Avatar Model for One-Shot 4D Animatable Gaussian Head](https://mlsanity.com/paper/2607.20922/) (2026)
- [S-Avatar: Diffusion-Guided Gaussian Head Avatars from a Single Image](https://mlsanity.com/paper/2607.28164/) (2026)

## Abstract (arXiv)

Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge for scalability. This paper introduces a novel approach to create high quality head avatar utilizing only a single or a few images per user. We learn a generative model for 3D animatable photo-realistic head avatar from a multi-view dataset of expressions from 2407 subjects, and leverage it as a prior for creating personalized avatar from few-shot images. Different from previous 3D-aware face generative models, our prior is built with a 3DMM-anchored neural radiance field backbone, which we show to be more effective for avatar creation through auto-decoding based on few-shot inputs. We also handle unstable 3DMM fitting by jointly optimizing the 3DMM fitting and camera calibration that leads to better few-shot adaptation. Our method demonstrates compelling results and outperforms existing state-of-the-art methods for few-shot avatar adaptation, paving the way for more efficient and personalized avatar creation.