mlsanityData to 7 Oct 2026

TranSplat: Instant Object Relighting in Gaussian Splatting via Spherical Harmonic Radiance Transfer

arXiv 2503.22676 ↗First posted 28 Mar 2025cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

We present TranSplat, a method for instant, accurate object relighting within the Gaussian Splatting (GS) framework. Rather than relying on costly inverse rendering routines, we propose a BRDF-free radiance transfer strategy that analytically modulates the spherical harmonic (SH) appearance coefficients of an object's 2D Gaussian surfels using per-normal irradiance ratios derived from source and target environment maps. To handle view-dependent and glossy appearances without explicit material estimation, we introduce a specularity-aware dual-path SH transfer strategy that adapts higher-order SH bands in the reflection domain. Additionally, we propose a lightweight SH-domain self-shadowing module to ensure physically realistic occlusion without explicit mesh raycasting. Operating as a post-processing step, TranSplat requires no additional GS retraining for a pair of source and target scenes. Evaluations on synthetic and real-world objects demonstrate state-of-the-art accuracy, outperforming recent inverse-rendering and diffusion-based GS relighting methods across most conditions, all while completing relighting operations in under one second. Although bounded by radially symmetric BRDF approximations and the low-pass nature of the SH basis, TranSplat produces perceptually realistic renderings even for glossy, complex materials, establishing a valuable, lightweight path forward for GS relighting.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 28 of its 45 references that are in the map. First posted on arXiv 28 Mar 2025.

Builds on

28 of 45 references.

References · 28

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  2. 2023Segment Anythingcited by 8,158
  3. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  4. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
  5. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
  6. 2022TensoRF: Tensorial Radiance Fieldscited by 1,275
  7. 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,230
  8. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,061
  9. 2020NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesiscited by 493
  10. 2023GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splattingcited by 331
  11. 2023GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfacescited by 249
  12. 2023GS-IR: 3D Gaussian Splatting for Inverse Renderingcited by 220
16 more
  1. 2023TensoIR: Tensorial Inverse Renderingcited by 166
  2. 2023Segment Any 3D Gaussianscited by 158
  3. 2021NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illuminationcited by 135
  4. 2020Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipelinecited by 131
  5. 2023Relightable Gaussian Codec Avatarscited by 126
  6. 2021Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Biascited by 115
  7. 2022NeILF: Neural Incident Light Field for Physically-based Material Estimationcited by 105
  8. 2018InverseRenderNet: Learning single image inverse renderingcited by 100
  9. 2024Neural Gaffer: Relighting Any Object via Diffusioncited by 91
  10. 2023NeILF++: Inter-Reflectable Light Fields for Geometry and Material Estimationcited by 73
  11. 2020Crowdsampling the Plenoptic Functioncited by 62
  12. 2023Neural-PBIR Reconstruction of Shape, Material, and Illuminationcited by 45
  13. 2024IllumiNeRF: 3D Relighting Without Inverse Renderingcited by 29
  14. 2024LumiGauss: Relightable Gaussian Splatting in the Wildcited by 21
  15. 2024PRTGS: Precomputed Radiance Transfer of Gaussian Splats for Real-Time High-Quality Relightingcited by 17
  16. 2024ReCap: Better Gaussian Relighting with Cross-Environment Capturescited by 14

Built on by

Not cited yet.