LumiTokens：基于标记空间光照变换的三维重光照
LumiTokens: 3D Relighting via Token-Space Lighting Transformation
- Northeastern University（东北大学）
- Adobe Research（奥多比研究院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
LumiTokens是将三维重光照转化为潜在场景标记直接变换的框架，支持渐进式可组合光照编辑，重光照质量优于或媲美现有方法。
AI中文摘要：
现有的三维重光照方法要么通过显式材质分解、基于扩散的视图空间生成，要么是两者结合，每种新光照条件都需要完全重新计算。我们注意到，近期的潜在场景表示法将多视图图像编码为一组紧凑标记，且无固定物理语义，这为重光照开辟了新的设计空间。我们提出LumiTokens，一个将三维重光照表述为对潜在场景标记直接变换的框架，无需显式三维表示、渲染方程或基于物理的分解。我们的模型引入了场景标记编辑器，该编辑器通过自注意力联合处理场景标记与光线标记，生成可解码为多视图一致重光照图像的更新标记。为通过统一接口支持多样光照类型，所有光照信号（包括环境贴图、点光源和区域光）都被参数化为Plucker光线标记，使该无显式空间结构的表示可原生支持三维用户交互。关键是，该设计支持渐进式重光照：由于编辑器的输出与输入处于同一潜在空间，用户可一次添加一个光源逐步构建光照，每次编辑在标记空间中组合。实验表明，LumiTokens的重光照质量与其他方法相当或更优，且支持渐进式、可组合的光照编辑。项目页面：this https URL
英文摘要：
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/
