Gaussian Wave Splatting for Computer-Generated Holography

Fuente: arXiv
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Main Authors: Choi, Suyeon, Chao, Brian, Yang, Jacqueline, Gopakumar, Manu, Wetzstein, Gordon
Format: Preprint
Published: 2025
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author Choi, Suyeon
Chao, Brian
Yang, Jacqueline
Gopakumar, Manu
Wetzstein, Gordon
author_facet Choi, Suyeon
Chao, Brian
Yang, Jacqueline
Gopakumar, Manu
Wetzstein, Gordon
contents State-of-the-art neural rendering methods optimize Gaussian scene representations from a few photographs for novel-view synthesis. Building on these representations, we develop an efficient algorithm, dubbed Gaussian Wave Splatting, to turn these Gaussians into holograms. Unlike existing computer-generated holography (CGH) algorithms, Gaussian Wave Splatting supports accurate occlusions and view-dependent effects for photorealistic scenes by leveraging recent advances in neural rendering. Specifically, we derive a closed-form solution for a 2D Gaussian-to-hologram transform that supports occlusions and alpha blending. Inspired by classic computer graphics techniques, we also derive an efficient approximation of the aforementioned process in the Fourier domain that is easily parallelizable and implement it using custom CUDA kernels. By integrating emerging neural rendering pipelines with holographic display technology, our Gaussian-based CGH framework paves the way for next-generation holographic displays.
format Preprint
id arxiv_https___arxiv_org_abs_2505_06582
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Gaussian Wave Splatting for Computer-Generated Holography
Choi, Suyeon
Chao, Brian
Yang, Jacqueline
Gopakumar, Manu
Wetzstein, Gordon
Graphics
Computational Physics
Optics
State-of-the-art neural rendering methods optimize Gaussian scene representations from a few photographs for novel-view synthesis. Building on these representations, we develop an efficient algorithm, dubbed Gaussian Wave Splatting, to turn these Gaussians into holograms. Unlike existing computer-generated holography (CGH) algorithms, Gaussian Wave Splatting supports accurate occlusions and view-dependent effects for photorealistic scenes by leveraging recent advances in neural rendering. Specifically, we derive a closed-form solution for a 2D Gaussian-to-hologram transform that supports occlusions and alpha blending. Inspired by classic computer graphics techniques, we also derive an efficient approximation of the aforementioned process in the Fourier domain that is easily parallelizable and implement it using custom CUDA kernels. By integrating emerging neural rendering pipelines with holographic display technology, our Gaussian-based CGH framework paves the way for next-generation holographic displays.
title Gaussian Wave Splatting for Computer-Generated Holography
topic Graphics
Computational Physics
Optics
url https://arxiv.org/abs/2505.06582