# Ultra-fast Neural Inference for Stochastic Gaussian Splatting Denoising

arXiv: https://arxiv.org/abs/2609.25604 · HTML: https://mlsanity.com/paper/2609.25604/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 23 of its 43 references that are in the map.
- First posted on arXiv 22 Sep 2026.

## Builds on (most cited first, 23 of 23)

- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields](https://mlsanity.com/paper/2111.12077/) (2021)
- [2D Gaussian Splatting for Geometrically Accurate Radiance Fields](https://mlsanity.com/paper/2403.17888/) (2024)
- [Modular Primitives for High-Performance Differentiable Rendering](https://mlsanity.com/paper/2011.03277/) (2020)
- [3D Gaussian Ray Tracing: Fast Tracing of Particle Scenes](https://mlsanity.com/paper/2407.07090/) (2024)
- [StopThePop: Sorted Gaussian Splatting for View-Consistent Real-time Rendering](https://mlsanity.com/paper/2402.00525/) (2024)
- [Speedy-Splat: Fast 3D Gaussian Splatting with Sparse Pixels and Sparse Primitives](https://mlsanity.com/paper/2412.00578/) (2024)
- [FlashGS: Efficient 3D Gaussian Splatting for Large-scale and High-resolution Rendering](https://mlsanity.com/paper/2408.07967/) (2024)
- [Don't Splat your Gaussians: Volumetric Ray-Traced Primitives for Modeling and Rendering Scattering and Emissive Media](https://mlsanity.com/paper/2405.15425/) (2024)
- [Efficient Perspective-Correct 3D Gaussian Splatting Using Hybrid Transparency](https://mlsanity.com/paper/2410.08129/) (2024)
- [ColorVideoVDP: A visual difference predictor for image, video and display distortions](https://mlsanity.com/paper/2401.11485/) (2024)
- [AdR-Gaussian: Accelerating Gaussian Splatting with Adaptive Radius](https://mlsanity.com/paper/2409.08669/) (2024)
- [Sort-free Gaussian Splatting via Weighted Sum Rendering](https://mlsanity.com/paper/2410.18931/) (2024)
- [StochasticSplats: Stochastic Rasterization for Sorting-Free 3D Gaussian Splatting](https://mlsanity.com/paper/2503.24366/) (2025)
- [Deformable Radial Kernel Splatting](https://mlsanity.com/paper/2412.11752/) (2024)
- [When Gaussian Meets Surfel: Ultra-fast High-fidelity Radiance Field Rendering](https://mlsanity.com/paper/2504.17545/) (2025)
- [Mobile-GS: Real-time Gaussian Splatting for Mobile Devices](https://mlsanity.com/paper/2603.11531/) (2026)
- [FuseSR: Super Resolution for Real-time Rendering through Efficient Multi-resolution Fusion](https://mlsanity.com/paper/2310.09726/) (2023)
- [Duplex-GS: Proxy-Guided Weighted Blending for Real-Time Order-Independent Gaussian Splatting](https://mlsanity.com/paper/2508.03180/) (2025)
- [Arbitrary-Scale 3D Gaussian Super-Resolution](https://mlsanity.com/paper/2508.16467/) (2025)
- [Stochastic Ray Tracing of Transparent 3D Gaussians](https://mlsanity.com/paper/2504.06598/) (2025)
- [Accelerating 3D Gaussian Splatting using Tensor Cores](https://mlsanity.com/paper/2605.17855/) (2026)
- [Depth Peeling for High-Fidelity Gaussian-Enhanced Surfel Rendering](https://mlsanity.com/paper/2605.25345/) (2026)

## Abstract (arXiv)

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 temporally stable, visually compelling outputs during free camera navigation, all while retaining the sort-free, blend-free rasterization performance. The combined pipeline retains a PSNR gap to sorted alpha-blending renderers, but the denoiser's overhead stays below the time saved by removing sorting and blending.
