# Holo-Relighting: Controllable Volumetric Portrait Relighting from a Single Image

arXiv: https://arxiv.org/abs/2403.09632 · HTML: https://mlsanity.com/paper/2403.09632/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- Builds on 55 of its 92 references that are in the map.
- First posted on arXiv 14 Mar 2024.

## Builds on (most cited first, 30 of 55)

- [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)
- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [Adding Conditional Control to Text-to-Image Diffusion Models](https://mlsanity.com/paper/2302.05543/) (2023)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Large Scale GAN Training for High Fidelity Natural Image Synthesis](https://mlsanity.com/paper/1809.11096/) (2018)
- [Efficient Geometry-aware 3D Generative Adversarial Networks](https://mlsanity.com/paper/2112.07945/) (2021)
- [Learning Implicit Fields for Generative Shape Modeling](https://mlsanity.com/paper/1812.02822/) (2018)
- [GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields](https://mlsanity.com/paper/2011.12100/) (2020)
- [Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation](https://mlsanity.com/paper/2008.00951/) (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)
- [Free-Form Image Inpainting with Gated Convolution](https://mlsanity.com/paper/1806.03589/) (2018)
- [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://mlsanity.com/paper/1903.08527/) (2019)
- [Learning an Animatable Detailed 3D Face Model from In-The-Wild Images](https://mlsanity.com/paper/2012.04012/) (2020)
- [StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis](https://mlsanity.com/paper/2110.08985/) (2021)
- [Pivotal Tuning for Latent-based Editing of Real Images](https://mlsanity.com/paper/2106.05744/) (2021)
- [GAN Inversion: A Survey](https://mlsanity.com/paper/2101.05278/) (2021)
- [PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models](https://mlsanity.com/paper/2003.03808/) (2020)
- [Towards Real-World Blind Face Restoration with Generative Facial Prior](https://mlsanity.com/paper/2101.04061/) (2021)
- [Learning Category-Specific Mesh Reconstruction from Image Collections](https://mlsanity.com/paper/1803.07549/) (2018)
- [StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation](https://mlsanity.com/paper/2112.11427/) (2021)
- [StyleRig: Rigging StyleGAN for 3D Control over Portrait Images](https://mlsanity.com/paper/2004.00121/) (2020)
- [GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation](https://mlsanity.com/paper/2112.08867/) (2021)
- [GAN Prior Embedded Network for Blind Face Restoration in the Wild](https://mlsanity.com/paper/2105.06070/) (2021)
- [Escaping Plato's Cave: 3D Shape From Adversarial Rendering](https://mlsanity.com/paper/1811.11606/) (2018)
- [Single Image Portrait Relighting](https://mlsanity.com/paper/1905.00824/) (2019)
- [CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis](https://mlsanity.com/paper/2110.09788/) (2021)
- [MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition](https://mlsanity.com/paper/2011.11961/) (2020)
- [A Light CNN for Deep Face Representation with Noisy Labels](https://mlsanity.com/paper/1511.02683/) (2015)

## Built on by (most cited first, 30 of 32)

- [URAvatar: Universal Relightable Gaussian Codec Avatars](https://mlsanity.com/paper/2410.24223/) (2024)
- [DifFRelight: Diffusion-Based Facial Performance Relighting](https://mlsanity.com/paper/2410.08188/) (2024)
- [Lux Post Facto: Learning Portrait Performance Relighting with Conditional Video Diffusion and a Hybrid Dataset](https://mlsanity.com/paper/2503.14485/) (2025)
- [RelitLRM: Generative Relightable Radiance for Large Reconstruction Models](https://mlsanity.com/paper/2410.06231/) (2024)
- [GenLit: Reformulating Single-Image Relighting as Video Generation](https://mlsanity.com/paper/2412.11224/) (2024)
- [Generative Portrait Shadow Removal](https://mlsanity.com/paper/2410.05525/) (2024)
- [High-Fidelity Relightable Monocular Portrait Animation with Lighting-Controllable Video Diffusion Model](https://mlsanity.com/paper/2502.19894/) (2025)
- [LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes](https://mlsanity.com/paper/2601.15283/) (2026)
- [DreamLight: Towards Harmonious and Consistent Image Relighting](https://mlsanity.com/paper/2506.14549/) (2025)
- [3DPR: Single Image 3D Portrait Relight using Generative Priors](https://mlsanity.com/paper/2510.15846/) (2025)
- [Text2Relight: Creative Portrait Relighting with Text Guidance](https://mlsanity.com/paper/2412.13734/) (2024)
- [Interactive Rendering of Relightable and Animatable Gaussian Avatars](https://mlsanity.com/paper/2407.10707/) (2024)
- [Parametric Shadow Control for Portrait Generation in Text-to-Image Diffusion Models](https://mlsanity.com/paper/2503.21943/) (2025)
- [UniLight: A Unified Representation for Lighting](https://mlsanity.com/paper/2512.04267/) (2025)
- [Total-Editing: Head Avatar with Editable Appearance, Motion, and Lighting](https://mlsanity.com/paper/2505.20582/) (2025)
- [TransLight: Image-Guided Customized Lighting Control with Generative Decoupling](https://mlsanity.com/paper/2508.14814/) (2025)
- [Relightable Holoported Characters: Capturing and Relighting Dynamic Human Performance from Sparse Views](https://mlsanity.com/paper/2512.00255/) (2025)
- [POLAR: A Portrait OLAT Dataset and Generative Framework for Illumination-Aware Face Modeling](https://mlsanity.com/paper/2512.13192/) (2025)
- [F-RNG: Feed-Forward Relightable Neural Gaussians](https://mlsanity.com/paper/2605.25975/) (2026)
- [ID-V2V: Identity-Preserving Video Restylization](https://mlsanity.com/paper/2607.22830/) (2026)
- [Low-Rank Head Avatar Personalization with Registers](https://mlsanity.com/paper/2506.01935/) (2025)
- [Multi-scale Attention-Guided Intrinsic Decomposition and Rendering Pass Prediction for Facial Images](https://mlsanity.com/paper/2512.16511/) (2025)
- [HeadLighter: Disentangling Illumination in Generative 3D Gaussian Heads via Lightstage Captures](https://mlsanity.com/paper/2601.02103/) (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)
- [BodyReLux: Temporally Consistent Full-Body Video Relighting](https://mlsanity.com/paper/2605.21766/) (2026)
- [HarmoVid: Relightful Video Portrait Harmonization](https://mlsanity.com/paper/2605.28811/) (2026)
- [Before the Shutter: Aesthetic and Actionable Portrait Photography Planning in 3D Scenes](https://mlsanity.com/paper/2605.30318/) (2026)
- [Pixel Cube: Diffusion-based Portrait Video Relighting Through Realistic Lighting Reproduction](https://mlsanity.com/paper/2606.02919/) (2026)
- [Generative Relightable Avatars](https://mlsanity.com/paper/2606.22718/) (2026)

## Abstract (arXiv)

At the core of portrait photography is the search for ideal lighting and viewpoint. The process often requires advanced knowledge in photography and an elaborate studio setup. In this work, we propose Holo-Relighting, a volumetric relighting method that is capable of synthesizing novel viewpoints, and novel lighting from a single image. Holo-Relighting leverages the pretrained 3D GAN (EG3D) to reconstruct geometry and appearance from an input portrait as a set of 3D-aware features. We design a relighting module conditioned on a given lighting to process these features, and predict a relit 3D representation in the form of a tri-plane, which can render to an arbitrary viewpoint through volume rendering. Besides viewpoint and lighting control, Holo-Relighting also takes the head pose as a condition to enable head-pose-dependent lighting effects. With these novel designs, Holo-Relighting can generate complex non-Lambertian lighting effects (e.g., specular highlights and cast shadows) without using any explicit physical lighting priors. We train Holo-Relighting with data captured with a light stage, and propose two data-rendering techniques to improve the data quality for training the volumetric relighting system. Through quantitative and qualitative experiments, we demonstrate Holo-Relighting can achieve state-of-the-arts relighting quality with better photorealism, 3D consistency and controllability.