StochasticSplats: Stochastic Rasterization for Sorting-Free 3D Gaussian Splatting

• URL: http://arxiv.org/abs/2503.24366v1
• Date: Mon, 31 Mar 2025 17:46:18 GMT
• Title: StochasticSplats: Stochastic Rasterization for Sorting-Free 3D Gaussian Splatting
• Authors: Shakiba Kheradmand, Delio Vicini, George Kopanas, Dmitry Lagun, Kwang Moo Yi, Mark Matthews, Andrea Tagliasacchi,
• Abstract summary: 3D Gaussian splatting (3DGS) is a popular radiance field method, with many application-specific extensions.<n>Most variants rely on the same core algorithm: depth-sorting of Gaussian splats then rendering in primitive order.<n>We address the above limitations by combining 3D splatting with rendering.<n>Our method renders more than four times faster than sortedization.
• Score: 28.48846639700183
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 3D Gaussian splatting (3DGS) is a popular radiance field method, with many application-specific extensions. Most variants rely on the same core algorithm: depth-sorting of Gaussian splats then rasterizing in primitive order. This ensures correct alpha compositing, but can cause rendering artifacts due to built-in approximations. Moreover, for a fixed representation, sorted rendering offers little control over render cost and visual fidelity. For example, and counter-intuitively, rendering a lower-resolution image is not necessarily faster. In this work, we address the above limitations by combining 3D Gaussian splatting with stochastic rasterization. Concretely, we leverage an unbiased Monte Carlo estimator of the volume rendering equation. This removes the need for sorting, and allows for accurate 3D blending of overlapping Gaussians. The number of Monte Carlo samples further imbues 3DGS with a way to trade off computation time and quality. We implement our method using OpenGL shaders, enabling efficient rendering on modern GPU hardware. At a reasonable visual quality, our method renders more than four times faster than sorted rasterization.

Related papers

• Second-order Optimization of Gaussian Splats with Importance Sampling [51.95046424364725]
  3D Gaussian Splatting (3DGS) is widely used for novel view rendering due to its high quality and fast inference time. We propose a novel second-order optimization strategy based on Levenberg-Marquardt (LM) and Conjugate Gradient (CG) Our method achieves a $3times$ speedup over standard LM and outperforms Adam by $6times$ when the Gaussian count is low.
  arXiv  Detail & Related papers  (2025-04-17T12:52:08Z)
• Textured Gaussians for Enhanced 3D Scene Appearance Modeling [58.134905268540436]
  3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art 3D reconstruction and rendering technique. We propose a new generalized Gaussian appearance representation that augments each Gaussian with alpha(A), RGB, or RGBA texture maps. We demonstrate image quality improvements over existing methods while using a similar or lower number of Gaussians.
  arXiv  Detail & Related papers  (2024-11-27T18:59:59Z)
• 3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes [87.01284850604495]
  We introduce 3D Convexting (3DCS), which leverages 3D smooth convexes as primitives for modeling geometrically-meaningful radiance fields from multiview images. 3DCS achieves superior performance over 3DGS on benchmarks such as MipNeizer, Tanks and Temples, and Deep Blending. Our results highlight the potential of 3D Convexting to become the new standard for high-quality scene reconstruction.
  arXiv  Detail & Related papers  (2024-11-22T14:31:39Z)
• EVER: Exact Volumetric Ellipsoid Rendering for Real-time View Synthesis [72.53316783628803]
  We present Exact Volumetric Ellipsoid Rendering (EVER), a method for real-time differentiable emission-only volume rendering. Unlike recentization based approach by 3D Gaussian Splatting (3DGS), our primitive based representation allows for exact volume rendering. We show that our method is more accurate with blending issues than 3DGS and follow-up work on view rendering.
  arXiv  Detail & Related papers  (2024-10-02T17:59:09Z)
• GSFusion: Online RGB-D Mapping Where Gaussian Splatting Meets TSDF Fusion [12.964675001994124]
  Traditional fusion algorithms preserve the spatial structure of 3D scenes. They often lack realism in terms of visualization. GSFusion significantly enhances computational efficiency without sacrificing rendering quality.
  arXiv  Detail & Related papers  (2024-08-22T18:32:50Z)
• AGG: Amortized Generative 3D Gaussians for Single Image to 3D [108.38567665695027]
  We introduce an Amortized Generative 3D Gaussian framework (AGG) that instantly produces 3D Gaussians from a single image. AGG decomposes the generation of 3D Gaussian locations and other appearance attributes for joint optimization. We propose a cascaded pipeline that first generates a coarse representation of the 3D data and later upsamples it with a 3D Gaussian super-resolution module.
  arXiv  Detail & Related papers  (2024-01-08T18:56:33Z)
• CompGS: Smaller and Faster Gaussian Splatting with Vector Quantization [16.829825478946837]
  3D Gaussian Splatting (3DGS) is a new method for modeling and rendering 3D radiance fields. We show that our simple yet effective method can reduce the storage cost for 3DGS by 40 to 50x and rendering time by 2 to 3x with a very small drop in the quality of rendered images.
  arXiv  Detail & Related papers  (2023-11-30T00:29:13Z)
• Multi-Scale 3D Gaussian Splatting for Anti-Aliased Rendering [48.41629250718956]
  3D Gaussians have recently emerged as a highly efficient representation for 3D reconstruction and rendering. Despite its high rendering quality and speed at high resolutions, they both deteriorate drastically when rendered at lower resolutions or from far away camera position. We propose a multi-scale 3D Gaussian splatting algorithm, which maintains Gaussians at different scales to represent the same scene. Our algorithm can achieve 13%-66% PSNR and 160%-2400% rendering speed improvement at 4$times$-128$times$ scale rendering on Mip-NeRF360 dataset.
  arXiv  Detail & Related papers  (2023-11-28T03:31:35Z)
• SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering [24.91019554830571]
  We propose a method to allow precise and extremely fast mesh extraction from 3D Gaussian Splatting. It is however challenging to extract a mesh from the millions of tiny 3D gaussians as these gaussians tend to be unorganized after optimization.
  arXiv  Detail & Related papers  (2023-11-21T18:38:03Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.