# FlashAvatar: High-fidelity Head Avatar with Efficient Gaussian Embedding

arXiv: https://arxiv.org/abs/2312.02214 · HTML: https://mlsanity.com/paper/2312.02214/

## Key facts

- Cited by 108 papers in the map (data through 14 Oct 2026).
- Builds on 50 of its 64 references that are in the map.
- First posted on arXiv 3 Dec 2023.

## Builds on (most cited first, 30 of 50)

- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://mlsanity.com/paper/2201.05989/) (2022)
- [DreamFusion: Text-to-3D using 2D Diffusion](https://mlsanity.com/paper/2209.14988/) (2022)
- [DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation](https://mlsanity.com/paper/1901.05103/) (2019)
- [Occupancy Networks: Learning 3D Reconstruction in Function Space](https://mlsanity.com/paper/1812.03828/) (2018)
- [Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields](https://mlsanity.com/paper/2111.12077/) (2021)
- [NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction](https://mlsanity.com/paper/2106.10689/) (2021)
- [Plenoxels: Radiance Fields without Neural Networks](https://mlsanity.com/paper/2112.05131/) (2021)
- [TensoRF: Tensorial Radiance Fields](https://mlsanity.com/paper/2203.09517/) (2022)
- [4D Gaussian Splatting for Real-Time Dynamic Scene Rendering](https://mlsanity.com/paper/2310.08528/) (2023)
- [Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction](https://mlsanity.com/paper/2111.11215/) (2021)
- [Neural Sparse Voxel Fields](https://mlsanity.com/paper/2007.11571/) (2020)
- [NeRF++: Analyzing and Improving Neural Radiance Fields](https://mlsanity.com/paper/2010.07492/) (2020)
- [DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation](https://mlsanity.com/paper/2309.16653/) (2023)
- [GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields](https://mlsanity.com/paper/2011.12100/) (2020)
- [Accelerating 3D Deep Learning with PyTorch3D](https://mlsanity.com/paper/2007.08501/) (2020)
- [Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction](https://mlsanity.com/paper/2309.13101/) (2023)
- [Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis](https://mlsanity.com/paper/2308.09713/) (2023)
- [FastNeRF: High-Fidelity Neural Rendering at 200FPS](https://mlsanity.com/paper/2103.10380/) (2021)
- [Learning an Animatable Detailed 3D Face Model from In-The-Wild Images](https://mlsanity.com/paper/2012.04012/) (2020)
- [Baking Neural Radiance Fields for Real-Time View Synthesis](https://mlsanity.com/paper/2103.14645/) (2021)
- [Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction](https://mlsanity.com/paper/2012.03065/) (2020)
- [AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis](https://mlsanity.com/paper/2103.11078/) (2021)
- [Text-to-3D using Gaussian Splatting](https://mlsanity.com/paper/2309.16585/) (2023)
- [BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation](https://mlsanity.com/paper/2004.02147/) (2020)
- [Mixture of Volumetric Primitives for Efficient Neural Rendering](https://mlsanity.com/paper/2103.01954/) (2021)
- [Generating 3D faces using Convolutional Mesh Autoencoders](https://mlsanity.com/paper/1807.10267/) (2018)

## Built on by (most cited first, 30 of 108)

- [3D Gaussian Splatting: Survey, Technologies, Challenges, and Opportunities](https://mlsanity.com/paper/2407.17418/) (2024)
- [HeadGaS: Real-Time Animatable Head Avatars via 3D Gaussian Splatting](https://mlsanity.com/paper/2312.02902/) (2023)
- [Avat3r: Large Animatable Gaussian Reconstruction Model for High-fidelity 3D Head Avatars](https://mlsanity.com/paper/2502.20220/) (2025)
- [CAP4D: Creating Animatable 4D Portrait Avatars with Morphable Multi-View Diffusion Models](https://mlsanity.com/paper/2412.12093/) (2024)
- [SWinGS: Sliding Windows for Dynamic 3D Gaussian Splatting](https://mlsanity.com/paper/2312.13308/) (2023)
- [HeadGAP: Few-Shot 3D Head Avatar via Generalizable Gaussian Priors](https://mlsanity.com/paper/2408.06019/) (2024)
- [Gaussian Splatting: 3D Reconstruction and Novel View Synthesis, a Review](https://mlsanity.com/paper/2405.03417/) (2024)
- [MeGA: Hybrid Mesh-Gaussian Head Avatar for High-Fidelity Rendering and Head Editing](https://mlsanity.com/paper/2404.19026/) (2024)
- [HHAvatar: Gaussian Head Avatar with Dynamic Hairs](https://mlsanity.com/paper/2312.03029/) (2023)
- [FATE: Full-head Gaussian Avatar with Textural Editing from Monocular Video](https://mlsanity.com/paper/2411.15604/) (2024)
- [RGBAvatar: Reduced Gaussian Blendshapes for Online Modeling of Head Avatars](https://mlsanity.com/paper/2503.12886/) (2025)
- [HRAvatar: High-Quality and Relightable Gaussian Head Avatar](https://mlsanity.com/paper/2503.08224/) (2025)
- [Beyond Gaussians: Fast and High-Fidelity 3D Splatting with Linear Kernels](https://mlsanity.com/paper/2411.12440/) (2024)
- [GUAVA: Generalizable Upper Body 3D Gaussian Avatar](https://mlsanity.com/paper/2505.03351/) (2025)
- [VOODOO XP: Expressive One-Shot Head Reenactment for VR Telepresence](https://mlsanity.com/paper/2405.16204/) (2024)
- [Advancing Extended Reality with 3D Gaussian Splatting: Innovations and Prospects](https://mlsanity.com/paper/2412.06257/) (2024)
- [MVP4D: Multi-View Portrait Video Diffusion for Animatable 4D Avatars](https://mlsanity.com/paper/2510.12785/) (2025)
- [Rig3DGS: Creating Controllable Portraits from Casual Monocular Videos](https://mlsanity.com/paper/2402.03723/) (2024)
- [Arc2Avatar: Generating Expressive 3D Avatars from a Single Image via ID Guidance](https://mlsanity.com/paper/2501.05379/) (2025)
- [SurFhead: Affine Rig Blending for Geometrically Accurate 2D Gaussian Surfel Head Avatars](https://mlsanity.com/paper/2410.11682/) (2024)
- [Synthetic Prior for Few-Shot Drivable Head Avatar Inversion](https://mlsanity.com/paper/2501.06903/) (2025)
- [3D Gaussian Head Avatars with Expressive Dynamic Appearances by Compact Tensorial Representations](https://mlsanity.com/paper/2504.14967/) (2025)
- [GraphAvatar: Compact Head Avatars with GNN-Generated 3D Gaussians](https://mlsanity.com/paper/2412.13983/) (2024)
- [TaoAvatar: Real-Time Lifelike Full-Body Talking Avatars for Augmented Reality via 3D Gaussian Splatting](https://mlsanity.com/paper/2503.17032/) (2025)
- [SEGA: Drivable 3D Gaussian Head Avatar from a Single Image](https://mlsanity.com/paper/2504.14373/) (2025)
- [SOAP: Style-Omniscient Animatable Portraits](https://mlsanity.com/paper/2505.05022/) (2025)
- [GPHM: Gaussian Parametric Head Model for Monocular Head Avatar Reconstruction](https://mlsanity.com/paper/2407.15070/) (2024)
- [Gaussian Deja-vu: Creating Controllable 3D Gaussian Head-Avatars with Enhanced Generalization and Personalization Abilities](https://mlsanity.com/paper/2409.16147/) (2024)
- [FlexAvatar: Learning Complete 3D Head Avatars with Partial Supervision](https://mlsanity.com/paper/2512.15599/) (2025)
- [GazeGaussian: High-Fidelity Gaze Redirection with 3D Gaussian Splatting](https://mlsanity.com/paper/2411.12981/) (2024)

## Abstract (arXiv)

We propose FlashAvatar, a novel and lightweight 3D animatable avatar representation that could reconstruct a digital avatar from a short monocular video sequence in minutes and render high-fidelity photo-realistic images at 300FPS on a consumer-grade GPU. To achieve this, we maintain a uniform 3D Gaussian field embedded in the surface of a parametric face model and learn extra spatial offset to model non-surface regions and subtle facial details. While full use of geometric priors can capture high-frequency facial details and preserve exaggerated expressions, proper initialization can help reduce the number of Gaussians, thus enabling super-fast rendering speed. Extensive experimental results demonstrate that FlashAvatar outperforms existing works regarding visual quality and personalized details and is almost an order of magnitude faster in rendering speed. Project page: https://ustc3dv.github.io/FlashAvatar/