# PRTGaussian: Efficient Relighting Using 3D Gaussians with Precomputed Radiance Transfer

arXiv: https://arxiv.org/abs/2408.05631 · HTML: https://mlsanity.com/paper/2408.05631/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 23 references that are in the map.
- First posted on arXiv 10 Aug 2024.

## Builds on (most cited first, 14 of 14)

- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation](https://mlsanity.com/paper/1612.00593/) (2016)
- [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)
- [GS-IR: 3D Gaussian Splatting for Inverse Rendering](https://mlsanity.com/paper/2311.16473/) (2023)
- [TensoIR: Tensorial Inverse Rendering](https://mlsanity.com/paper/2304.12461/) (2023)
- [Relightable Gaussian Codec Avatars](https://mlsanity.com/paper/2312.03704/) (2023)
- [EfficientNeRF: Efficient Neural Radiance Fields](https://mlsanity.com/paper/2206.00878/) (2022)
- [GIR: 3D Gaussian Inverse Rendering for Relightable Scene Factorization](https://mlsanity.com/paper/2312.05133/) (2023)
- [Neural Light Transport for Relighting and View Synthesis](https://mlsanity.com/paper/2008.03806/) (2020)
- [Relighting Neural Radiance Fields with Shadow and Highlight Hints](https://mlsanity.com/paper/2308.13404/) (2023)
- [EyeNeRF: A Hybrid Representation for Photorealistic Synthesis, Animation and Relighting of Human Eyes](https://mlsanity.com/paper/2206.08428/) (2022)
- [Relightable and Animatable Neural Avatars from Videos](https://mlsanity.com/paper/2312.12877/) (2023)

## Built on by (most cited first, 4 of 4)

- [LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes](https://mlsanity.com/paper/2601.15283/) (2026)
- [HumanOLAT: A Large-Scale Dataset for Full-Body Human Relighting and Novel-View Synthesis](https://mlsanity.com/paper/2508.09137/) (2025)
- [OLATverse: A Large-scale Real-world Object Dataset with Precise Lighting Control](https://mlsanity.com/paper/2511.02483/) (2025)
- [UTrice: Unifying Primitives in Differentiable Ray Tracing and Rasterization via Triangles for Particle-Based 3D Scenes](https://mlsanity.com/paper/2512.04421/) (2025)

## Abstract (arXiv)

We present PRTGaussian, a realtime relightable novel-view synthesis method made possible by combining 3D Gaussians and Precomputed Radiance Transfer (PRT). By fitting relightable Gaussians to multi-view OLAT data, our method enables real-time, free-viewpoint relighting. By estimating the radiance transfer based on high-order spherical harmonics, we achieve a balance between capturing detailed relighting effects and maintaining computational efficiency. We utilize a two-stage process: in the first stage, we reconstruct a coarse geometry of the object from multi-view images. In the second stage, we initialize 3D Gaussians with the obtained point cloud, then simultaneously refine the coarse geometry and learn the light transport for each Gaussian. Extensive experiments on synthetic datasets show that our approach can achieve fast and high-quality relighting for general objects. Code and data are available at https://github.com/zhanglbthu/PRTGaussian.