3DSS: 3D Surface Splatting for Inverse Rendering
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Abstract (arXiv)
We present 3D Surface Splatting (3DSS), the first differentiable surface splatting renderer for physically-based inverse rendering from multi-view images. Our central insight is that the surface separation problem at the heart of surface splatting admits a direct formulation in terms of the reconstruction kernels themselves. From this foundation we derive a coverage-based compositing model whose per-layer opacity arises directly from the accumulated Elliptical Weighted Average reconstruction weight, yielding anti-aliased silhouettes and informative visibility gradients at sparsely covered edges. Combined with forward microfacet shading under co-optimized HDR environment lighting and density-aware adaptive refinement, 3DSS jointly recovers shape, spatially-varying BRDF materials, and illumination. Because the optimized representation is a set of oriented surface samples, it bridges natively to mesh-based workflows via surface reconstruction from oriented point cloud methods. We evaluate 3DSS against mesh-based, implicit, and Gaussian-splatting baselines across geometry reconstruction, novel-view synthesis, and novel-illumination relighting.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 22 of its 62 references that are in the map. First posted on arXiv 7 May 2026.
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References · 22
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,964
- 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,712
- 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,360
- 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,076
- 2020NeRD: Neural Reflectance Decomposition from Image Collectionscited by 449
- 2020Modular Primitives for High-Performance Differentiable Renderingcited by 441
- 2019Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoningcited by 420
- 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 366
- 2021PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relightingcited by 335
- 2023GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfacescited by 252
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- 2019Differentiable Surface Splatting for Point-based Geometry Processingcited by 239
- 2023GS-IR: 3D Gaussian Splatting for Inverse Renderingcited by 224
- 2019Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderercited by 221
- 2023GIR: 3D Gaussian Inverse Rendering for Relightable Scene Factorizationcited by 87
- 20243D Gaussian Splatting with Deferred Reflectioncited by 63
- 2023Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmarkcited by 51
- 2023NeFII: Inverse Rendering for Reflectance Decomposition with Near-Field Indirect Illuminationcited by 38
- 2025RTR-GS: 3D Gaussian Splatting for Inverse Rendering with Radiance Transfer and Reflectioncited by 10
- 2024Filtering After Shading With Stochastic Texture Filteringcited by 5
- 2025TextureSplat: Per-Primitive Texture Mapping for Reflective Gaussian Splattingcited by 3
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