Volumetrically Consistent 3D Gaussian Rasterization
Chinmay Talegaonkar, Yash Belhe, Ravi Ramamoorthi, Nicholas Antipa
摘要
Recently, 3D Gaussian Splatting (3DGS) has enabled photorealistic view synthesis at high inference speeds. However, its splatting-based rendering model makes several approximations to the rendering equation, reducing physical accuracy. We show that the core approximations in splatting are unnecessary, even within a rasterizer; we instead volumetrically integrate 3D Gaussians directly to compute the transmittance across them analytically. We use this analytic transmittance to derive more physicallyaccurate alpha values than 3DGS, which can directly be used within their framework. The result is a method that more closely follows the volume rendering equation (similar to ray-tracing) while enjoying the speed benefits of rasterization. Our method represents opaque surfaces with higher accuracy and fewer points than 3DGS. This enables it to outperform 3DGS for view synthesis (measured in SSIM and LPIPS). Being volumetrically consistent also enables our method to work out of the box for tomography. We match the state-of-the-art 3DGS-based tomography method with fewer points. Our code is publicly available at: https://github.com/chinmay0301ucsd/Vol3DGS
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引用它的顶会 Paper9
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- 3DGEER: 3D Gaussian Rendering Made Exact and Efficient for Generic CamerasZixun Huang, Cho-Ying Wu, Yuliang Guo, Xinyu Huang 等ICLR 2026 · 被引用 9 次
- Splat the Net: Radiance Fields with Splattable Neural Primitivesxilong zhou, Bao-Huy Nguyen, Loïc Magne, Vladislav Golyanik 等ICLR 2026 · 被引用 8 次
- AAA-Gaussians: Anti-Aliased and Artifact-Free 3D Gaussian RenderingMichael Steiner, Thomas Köhler, Lukas Radl, Felix Windisch 等ICCV 2025 · 被引用 5 次
- SAP: Exact Sorting in Splatting via Screen-Aligned PrimitivesZhanke Wang, Zhiyan Wang, Kaiqiang Xiong, Jiahao Wu 等NeurIPS 2025 · 被引用 1 次
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