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Ultra-fast Neural Inference for Stochastic Gaussian Splatting Denoising
Stochastic rendering eliminates the sorting and alpha blending process in Gaussian splatting, at the cost of introducing spatial noise. Formulating temporal denoising over the pixel stream shared by view-consistent stochastic splatting renderers, we propose a temporal neural denoiser validated on stochastic 2D Gaussian Splatting rendering, combining dual-path exponential moving average accumulation, per-pixel learned trust prediction for history validation, a fixed anisotropic spatial filter and a variance-gated composition with stabilization. The denoiser suppresses the noise, achieving tempo
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-22T02:51:29.000Z
First collected: 2026-09-23T04:21:13.910Z. This is not the publication date.