# HRAvatar: High-Quality and Relightable Gaussian Head Avatar

arXiv: https://arxiv.org/abs/2503.08224 · HTML: https://mlsanity.com/paper/2503.08224/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- Builds on 68 of its 89 references that are in the map.
- First posted on arXiv 11 Mar 2025.

## Builds on (most cited first, 30 of 68)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [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)
- [Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields](https://mlsanity.com/paper/2103.13415/) (2021)
- [NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction](https://mlsanity.com/paper/2106.10689/) (2021)
- [pixelNeRF: Neural Radiance Fields from One or Few Images](https://mlsanity.com/paper/2012.02190/) (2020)
- [NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections](https://mlsanity.com/paper/2008.02268/) (2020)
- [Efficient Geometry-aware 3D Generative Adversarial Networks](https://mlsanity.com/paper/2112.07945/) (2021)
- [4D Gaussian Splatting for Real-Time Dynamic Scene Rendering](https://mlsanity.com/paper/2310.08528/) (2023)
- [2D Gaussian Splatting for Geometrically Accurate Radiance Fields](https://mlsanity.com/paper/2403.17888/) (2024)
- [K-Planes: Explicit Radiance Fields in Space, Time, and Appearance](https://mlsanity.com/paper/2301.10241/) (2023)
- [pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction](https://mlsanity.com/paper/2312.12337/) (2023)
- [Mip-Splatting: Alias-free 3D Gaussian Splatting](https://mlsanity.com/paper/2311.16493/) (2023)
- [HexPlane: A Fast Representation for Dynamic Scenes](https://mlsanity.com/paper/2301.09632/) (2023)
- [Learning an Animatable Detailed 3D Face Model from In-The-Wild Images](https://mlsanity.com/paper/2012.04012/) (2020)
- [Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction](https://mlsanity.com/paper/2012.03065/) (2020)
- [NeRD: Neural Reflectance Decomposition from Image Collections](https://mlsanity.com/paper/2012.03918/) (2020)
- [LangSplat: 3D Language Gaussian Splatting](https://mlsanity.com/paper/2312.16084/) (2023)
- [PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting](https://mlsanity.com/paper/2104.00674/) (2021)
- [GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Image](https://mlsanity.com/paper/2403.12013/) (2024)
- [Mixture of Volumetric Primitives for Efficient Neural Rendering](https://mlsanity.com/paper/2103.01954/) (2021)
- [EMOCA: Emotion Driven Monocular Face Capture and Animation](https://mlsanity.com/paper/2204.11312/) (2022)
- [GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfaces](https://mlsanity.com/paper/2311.17977/) (2023)
- [I M Avatar: Implicit Morphable Head Avatars from Videos](https://mlsanity.com/paper/2112.07471/) (2021)
- [PointAvatar: Deformable Point-based Head Avatars from Videos](https://mlsanity.com/paper/2212.08377/) (2022)
- [SplattingAvatar: Realistic Real-Time Human Avatars with Mesh-Embedded Gaussian Splatting](https://mlsanity.com/paper/2403.05087/) (2024)
- [Modeling Indirect Illumination for Inverse Rendering](https://mlsanity.com/paper/2204.06837/) (2022)
- [TensoIR: Tensorial Inverse Rendering](https://mlsanity.com/paper/2304.12461/) (2023)

## Built on by (most cited first, 25 of 25)

- [GUAVA: Generalizable Upper Body 3D Gaussian Avatar](https://mlsanity.com/paper/2505.03351/) (2025)
- [A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation](https://mlsanity.com/paper/2508.09977/) (2025)
- [FlexAvatar: Learning Complete 3D Head Avatars with Partial Supervision](https://mlsanity.com/paper/2512.15599/) (2025)
- [HyPlaneHead: Rethinking Tri-plane-like Representations in Full-Head Image Synthesis](https://mlsanity.com/paper/2509.16748/) (2025)
- [STAvatar: Soft Binding and Temporal Density Control for Monocular 3D Head Avatars Reconstruction](https://mlsanity.com/paper/2511.19854/) (2025)
- [FlexAvatar: Flexible Large Reconstruction Model for Animatable Gaussian Head Avatars with Detailed Deformation](https://mlsanity.com/paper/2512.17717/) (2025)
- [AvatarBack: Back-Head Generation for Complete 3D Avatars from Front-View Images](https://mlsanity.com/paper/2508.20623/) (2025)
- [ArchitectHead: Continuous Level of Detail Control for 3D Gaussian Head Avatars](https://mlsanity.com/paper/2510.05488/) (2025)
- [GTAvatar: Bridging Gaussian Splatting and Texture Mapping for Relightable and Editable Gaussian Avatars](https://mlsanity.com/paper/2512.09162/) (2025)
- [POLAR: A Portrait OLAT Dataset and Generative Framework for Illumination-Aware Face Modeling](https://mlsanity.com/paper/2512.13192/) (2025)
- [Multi-view Consistent 3D Gaussian Head Avatars 'without' Multi-view Generation](https://mlsanity.com/paper/2605.25220/) (2026)
- [RelightAnyone: A Generalized Relightable 3D Gaussian Head Model](https://mlsanity.com/paper/2601.03357/) (2026)
- [Light Up Your Face: A Physically Consistent Dataset and Diffusion Model for Face Fill-Light Enhancement](https://mlsanity.com/paper/2602.04300/) (2026)
- [GeoDiff4D: Geometry-Aware Diffusion for 4D Head Avatar Reconstruction](https://mlsanity.com/paper/2602.24161/) (2026)
- [Giving Faces Their Feelings Back: Explicit Emotion Control for Feedforward Single-Image 3D Head Avatars](https://mlsanity.com/paper/2604.14541/) (2026)
- [LentiAvatar: Pseudo-Multiview Reconstruction and Subpixel Prism Rendering for Real-Time Stereoscopic Communication](https://mlsanity.com/paper/2606.10550/) (2026)
- [SpatialAvatar-0: High-Quality 4D Head Avatar with Multi-Stage Reconstruction](https://mlsanity.com/paper/2606.15659/) (2026)
- [EMOSH: Expressive Motion and Shape Disentanglement for Human Animation](https://mlsanity.com/paper/2606.28026/) (2026)
- [3D FaceShell: Attribute Transfer in 3D Face Avatars as a VLM Defense Mechanism](https://mlsanity.com/paper/2607.16280/) (2026)
- [FlexiAvatar: Unified 3D Gaussian Human Avatars Under Arbitrary Body Visibility](https://mlsanity.com/paper/2607.19100/) (2026)
- [S-Avatar: Diffusion-Guided Gaussian Head Avatars from a Single Image](https://mlsanity.com/paper/2607.28164/) (2026)
- [Unwarping the Lens: A Physics-Grounded Approach to Video Glasses Removal](https://mlsanity.com/paper/2608.20212/) (2026)
- [Relightable 3D Avatar Reconstruction with Semantic-Adaptive Motion-Illumination Responses](https://mlsanity.com/paper/2609.24158/) (2026)
- [Heartian: Physiology-Aware Relightable Gaussian Head Avatar](https://mlsanity.com/paper/2609.28539/) (2026)
- [ManifoldSplat: Language-Guided Semantic Shape Editing of 3D Gaussian Head Avatars](https://mlsanity.com/paper/2610.03599/) (2026)

## Abstract (arXiv)

Reconstructing animatable and high-quality 3D head avatars from monocular videos, especially with realistic relighting, is a valuable task. However, the limited information from single-view input, combined with the complex head poses and facial movements, makes this challenging. Previous methods achieve real-time performance by combining 3D Gaussian Splatting with a parametric head model, but the resulting head quality suffers from inaccurate face tracking and limited expressiveness of the deformation model. These methods also fail to produce realistic effects under novel lighting conditions. To address these issues, we propose HRAvatar, a 3DGS-based method that reconstructs high-fidelity, relightable 3D head avatars. HRAvatar reduces tracking errors through end-to-end optimization and better captures individual facial deformations using learnable blendshapes and learnable linear blend skinning. Additionally, it decomposes head appearance into several physical properties and incorporates physically-based shading to account for environmental lighting. Extensive experiments demonstrate that HRAvatar not only reconstructs superior-quality heads but also achieves realistic visual effects under varying lighting conditions.