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arXiv Computer Vision By Felix Windisch, Thomas K\"ohler, Lukas Radl, Chris Wyman, Georgios Kopanas, Bernhard Kerbl, Markus Steinberger

SteadySplats: Resampling of Low-Variance Gaussians for High-Fidelity Stochastic Rendering

Read the original on arXiv Computer Vision →

SteadySplats introduces a method to reduce high‑frequency noise in stochastic rendering of 3D Gaussian Splatting models. The approach combines a history‑based spatial resampling scheme for faster image convergence, temporal importance resampling for camera‑movement coherence, and a color regularizer during training to lower variance along view rays. The resulting Vulkan‑based renderer achieves a 13 dB PSNR improvement over prior stochastic methods at one sample per pixel and converges quickly to a low‑error sorted 3DGS representation.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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