mlsanityData to 14 Oct 2026

LumiTokens: 3D Relighting via Token-Space Lighting Transformation

arXiv 2608.18215 ↗First posted 18 Aug 2026cs.CVcited by 0

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Abstract (arXiv)

Existing 3D relighting methods operate through either explicit material decomposition, diffusion-based view-space generation, or a combination of both, requiring full recomputation for each new lighting condition. We observe that recent latent scene representations, which encode multi-view images into a set of compact tokens with no fixed physical semantics, open up a novel design space for relighting. We present LumiTokens, a framework that formulates 3D relighting as a direct transformation on latent scene tokens, without explicit 3D representations, rendering equations, or physics-based decomposition. Our model introduces a Scene Token Editor that processes scene tokens jointly with light-ray tokens through self-attention, producing updated tokens that can be decoded into multi-view-consistent relit images. To support diverse lighting types through a unified interface, all lighting signals, including environment maps, point lights, and area lights, are parameterized as Plucker ray tokens, enabling native 3D user interaction with a representation that carries no explicit spatial structure. Crucially, this design supports progressive relighting: because the editor's output remains in the same latent space as its input, a user can incrementally build up illumination one light source at a time, with each edit composing in token space. Experiments demonstrate that LumiTokens achieves comparable or superior relighting quality to other methods and supports progressive, composable lighting edits. Project page: https://neu-vi.github.io/LumiTokens/

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 36 of its 41 references that are in the map. First posted on arXiv 18 Aug 2026.

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36 of 41 references.

References · 36

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  2. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
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  9. 2021PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relightingcited by 335
  10. 2021Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representationscited by 227
  11. 2023GS-IR: 3D Gaussian Splatting for Inverse Renderingcited by 224
  12. 2024LVSM: A Large View Synthesis Model with Minimal 3D Inductive Biascited by 189
24 more
  1. 2023TensoIR: Tensorial Inverse Renderingcited by 168
  2. 2022Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoisingcited by 163
  3. 2024RGBleftrightarrowX: Image decomposition and synthesis using material- and lighting-aware diffusion modelscited by 161
  4. 2024DiLightNet: Fine-grained Lighting Control for Diffusion-based Image Generationcited by 93
  5. 2024Neural Gaffer: Relighting Any Object via Diffusioncited by 91
  6. 2025RayZer: A Self-supervised Large View Synthesis Modelcited by 77
  7. 2023Intrinsic Image Diffusion for Indoor Single-view Material Estimationcited by 73
  8. 2025DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Modelscited by 57
  9. 2023I2-SDF: Intrinsic Indoor Scene Reconstruction and Editing via Raytracing in Neural SDFscited by 42
  10. 2025UniRelight: Learning Joint Decomposition and Synthesis for Video Relightingcited by 40
  11. 2024A Diffusion Approach to Radiance Field Relighting using Multi-Illumination Synthesiscited by 37
  12. 2024IllumiNeRF: 3D Relighting Without Inverse Renderingcited by 29
  13. 2024RelitLRM: Generative Relightable Radiance for Large Reconstruction Modelscited by 23
  14. 2025E-RayZer: Self-supervised 3D Reconstruction as Spatial Visual Pre-trainingcited by 22
  15. 2024GenLit: Reformulating Single-Image Relighting as Video Generationcited by 20
  16. 2025LightSwitch: Multi-view Relighting with Material-guided Diffusioncited by 15
  17. 2026SceneTok: A Compressed, Diffusable Token Space for 3D Scenescited by 10
  18. 2026LuxRemix: Lighting Decomposition and Remixing for Indoor Scenescited by 9
  19. 2025ROGR: Relightable 3D Objects using Generative Relightingcited by 7
  20. 2025CtrlVDiff: Controllable Video Generation via Unified Multimodal Video Diffusioncited by 6
  21. 2025NeAR: Coupled Neural Asset-Renderer Stackcited by 5
  22. 2026GR3EN: Generative Relighting for 3D Environmentscited by 5
  23. 2025Generalizable and Relightable Gaussian Splatting for Human Novel View Synthesiscited by 4
  24. 2025X2Video: Adapting Diffusion Models for Multimodal Controllable Neural Video Renderingcited by 3

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