# VoLux-GAN: A Generative Model for 3D Face Synthesis with HDRI Relighting

arXiv: https://arxiv.org/abs/2201.04873 · HTML: https://mlsanity.com/paper/2201.04873/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- Builds on 52 of its 80 references that are in the map.
- First posted on arXiv 13 Jan 2022.

## Builds on (most cited first, 30 of 52)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Deep Learning Face Attributes in the Wild](https://mlsanity.com/paper/1411.7766/) (2014)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Progressive Growing of GANs for Improved Quality, Stability, and Variation](https://mlsanity.com/paper/1710.10196/) (2017)
- [Large Scale GAN Training for High Fidelity Natural Image Synthesis](https://mlsanity.com/paper/1809.11096/) (2018)
- [Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains](https://mlsanity.com/paper/2006.10739/) (2020)
- [Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields](https://mlsanity.com/paper/2103.13415/) (2021)
- [Demystifying MMD GANs](https://mlsanity.com/paper/1801.01401/) (2018)
- [Efficient Geometry-aware 3D Generative Adversarial Networks](https://mlsanity.com/paper/2112.07945/) (2021)
- [Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network](https://mlsanity.com/paper/1609.05158/) (2016)
- [Alias-Free Generative Adversarial Networks](https://mlsanity.com/paper/2106.12423/) (2021)
- [FaceForensics++: Learning to Detect Manipulated Facial Images](https://mlsanity.com/paper/1901.08971/) (2019)
- [StarGAN v2: Diverse Image Synthesis for Multiple Domains](https://mlsanity.com/paper/1912.01865/) (2019)
- [Self-Attention Generative Adversarial Networks](https://mlsanity.com/paper/1805.08318/) (2018)
- [GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields](https://mlsanity.com/paper/2011.12100/) (2020)
- [pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis](https://mlsanity.com/paper/2012.00926/) (2020)
- [GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis](https://mlsanity.com/paper/2007.02442/) (2020)
- [PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization](https://mlsanity.com/paper/2004.00452/) (2020)
- [StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis](https://mlsanity.com/paper/2110.08985/) (2021)
- [NeRD: Neural Reflectance Decomposition from Image Collections](https://mlsanity.com/paper/2012.03918/) (2020)
- [Making Convolutional Networks Shift-Invariant Again](https://mlsanity.com/paper/1904.11486/) (2019)
- [StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows](https://mlsanity.com/paper/2008.02401/) (2020)
- [StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation](https://mlsanity.com/paper/2112.11427/) (2021)
- [State of the Art on Neural Rendering](https://mlsanity.com/paper/2004.03805/) (2020)
- [StyleRig: Rigging StyleGAN for 3D Control over Portrait Images](https://mlsanity.com/paper/2004.00121/) (2020)
- [Deferred Neural Rendering: Image Synthesis using Neural Textures](https://mlsanity.com/paper/1904.12356/) (2019)
- [DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection](https://mlsanity.com/paper/2001.00179/) (2020)
- [HeadNeRF: A Real-time NeRF-based Parametric Head Model](https://mlsanity.com/paper/2112.05637/) (2021)
- [GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation](https://mlsanity.com/paper/2112.08867/) (2021)

## Built on by (most cited first, 30 of 37)

- [EpiGRAF: Rethinking training of 3D GANs](https://mlsanity.com/paper/2206.10535/) (2022)
- [DiffusionRig: Learning Personalized Priors for Facial Appearance Editing](https://mlsanity.com/paper/2304.06711/) (2023)
- [Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark](https://mlsanity.com/paper/2310.16044/) (2023)
- [StyleGAN knows Normal, Depth, Albedo, and More](https://mlsanity.com/paper/2306.00987/) (2023)
- [URAvatar: Universal Relightable Gaussian Codec Avatars](https://mlsanity.com/paper/2410.24223/) (2024)
- [3D GAN Inversion with Facial Symmetry Prior](https://mlsanity.com/paper/2211.16927/) (2022)
- [Preface: A Data-driven Volumetric Prior for Few-shot Ultra High-resolution Face Synthesis](https://mlsanity.com/paper/2309.16859/) (2023)
- [Cafca: High-quality Novel View Synthesis of Expressive Faces from Casual Few-shot Captures](https://mlsanity.com/paper/2410.00630/) (2024)
- [Holo-Relighting: Controllable Volumetric Portrait Relighting from a Single Image](https://mlsanity.com/paper/2403.09632/) (2024)
- [AvatarStudio: Text-driven Editing of 3D Dynamic Human Head Avatars](https://mlsanity.com/paper/2306.00547/) (2023)
- [Lux Post Facto: Learning Portrait Performance Relighting with Conditional Video Diffusion and a Hybrid Dataset](https://mlsanity.com/paper/2503.14485/) (2025)
- [UrbanGIRAFFE: Representing Urban Scenes as Compositional Generative Neural Feature Fields](https://mlsanity.com/paper/2303.14167/) (2023)
- [SynthLight: Portrait Relighting with Diffusion Model by Learning to Re-render Synthetic Faces](https://mlsanity.com/paper/2501.09756/) (2025)
- [LPFF: A Portrait Dataset for Face Generators Across Large Poses](https://mlsanity.com/paper/2303.14407/) (2023)
- [Gaussian3Diff: 3D Gaussian Diffusion for 3D Full Head Synthesis and Editing](https://mlsanity.com/paper/2312.03763/) (2023)
- [FaceLit: Neural 3D Relightable Faces](https://mlsanity.com/paper/2303.15437/) (2023)
- [LumiGAN: Unconditional Generation of Relightable 3D Human Faces](https://mlsanity.com/paper/2304.13153/) (2023)
- [Isotropic3D: Image-to-3D Generation Based on a Single CLIP Embedding](https://mlsanity.com/paper/2403.10395/) (2024)
- [GeneAvatar: Generic Expression-Aware Volumetric Head Avatar Editing from a Single Image](https://mlsanity.com/paper/2404.02152/) (2024)
- [Controllable Light Diffusion for Portraits](https://mlsanity.com/paper/2305.04745/) (2023)
- [Relightable Neural Actor with Intrinsic Decomposition and Pose Control](https://mlsanity.com/paper/2312.11587/) (2023)
- [Makeup Extraction of 3D Representation via Illumination-Aware Image Decomposition](https://mlsanity.com/paper/2302.13279/) (2023)
- [3DPortraitGAN: Learning One-Quarter Headshot 3D GANs from a Single-View Portrait Dataset with Diverse Body Poses](https://mlsanity.com/paper/2307.14770/) (2023)
- [Learning with Unreliability: Fast Few-shot Voxel Radiance Fields with Relative Geometric Consistency](https://mlsanity.com/paper/2403.17638/) (2024)
- [COMPOSE: Comprehensive Portrait Shadow Editing](https://mlsanity.com/paper/2408.13922/) (2024)
- [Parametric Shadow Control for Portrait Generation in Text-to-Image Diffusion Models](https://mlsanity.com/paper/2503.21943/) (2025)
- [GR3EN: Generative Relighting for 3D Environments](https://mlsanity.com/paper/2601.16272/) (2026)
- [StyLitGAN: Prompting StyleGAN to Produce New Illumination Conditions](https://mlsanity.com/paper/2205.10351/) (2022)
- [NARRATE: A Normal Assisted Free-View Portrait Stylizer](https://mlsanity.com/paper/2207.00974/) (2022)
- [Towards Flexible, Scalable, and Adaptive Multi-Modal Conditioned Face Synthesis](https://mlsanity.com/paper/2312.16274/) (2023)

## Abstract (arXiv)

We propose VoLux-GAN, a generative framework to synthesize 3D-aware faces with convincing relighting. Our main contribution is a volumetric HDRI relighting method that can efficiently accumulate albedo, diffuse and specular lighting contributions along each 3D ray for any desired HDR environmental map. Additionally, we show the importance of supervising the image decomposition process using multiple discriminators. In particular, we propose a data augmentation technique that leverages recent advances in single image portrait relighting to enforce consistent geometry, albedo, diffuse and specular components. Multiple experiments and comparisons with other generative frameworks show how our model is a step forward towards photorealistic relightable 3D generative models.