Moment-Based 3D Gaussian Splatting: Resolving Volumetric Occlusion with Order-Independent Transmittance

• URL: http://arxiv.org/abs/2512.11800v1
• Date: Fri, 12 Dec 2025 18:59:55 GMT
• Title: Moment-Based 3D Gaussian Splatting: Resolving Volumetric Occlusion with Order-Independent Transmittance
• Authors: Jan U. Müller, Robin Tim Landsgesell, Leif Van Holland, Patrick Stotko, Reinhard Klein,
• Abstract summary: 3D Gaussian Splatting (3DGS) has reshaped novel view by enabling real-time computation of high-quality radiance fields.<n>We extend rayization-based rendering of 3D Gaussian representations with a novel method for high-fidelity transmittance.
• Score: 5.202755118021748
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The recent success of 3D Gaussian Splatting (3DGS) has reshaped novel view synthesis by enabling fast optimization and real-time rendering of high-quality radiance fields. However, it relies on simplified, order-dependent alpha blending and coarse approximations of the density integral within the rasterizer, thereby limiting its ability to render complex, overlapping semi-transparent objects. In this paper, we extend rasterization-based rendering of 3D Gaussian representations with a novel method for high-fidelity transmittance computation, entirely avoiding the need for ray tracing or per-pixel sample sorting. Building on prior work in moment-based order-independent transparency, our key idea is to characterize the density distribution along each camera ray with a compact and continuous representation based on statistical moments. To this end, we analytically derive and compute a set of per-pixel moments from all contributing 3D Gaussians. From these moments, a continuous transmittance function is reconstructed for each ray, which is then independently sampled within each Gaussian. As a result, our method bridges the gap between rasterization and physical accuracy by modeling light attenuation in complex translucent media, significantly improving overall reconstruction and rendering quality.

Related papers

• Joint Semantic and Rendering Enhancements in 3D Gaussian Modeling with Anisotropic Local Encoding [86.55824709875598]
  We propose a joint enhancement framework for 3D semantic Gaussian modeling that synergizes both semantic and rendering branches.<n>Unlike conventional point cloud shape encoding, we introduce an anisotropic 3D Gaussian Chebyshev descriptor to capture fine-grained 3D shape details.<n>We employ a cross-scene knowledge transfer module to continuously update learned shape patterns, enabling faster convergence and robust representations.
  arXiv  Detail & Related papers  (2026-01-05T18:33:50Z)
• 3DGEER: Exact and Efficient Volumetric Rendering with 3D Gaussians [15.776720879897345]
  We introduce 3DGEER, an Exact and Efficient Volumetric Gaussian Rendering method.<n>Our method consistently outperforms prior methods, establishing a new state-of-the-art in real-time neural rendering.
  arXiv  Detail & Related papers  (2025-05-29T22:52:51Z)
• PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting [54.7468067660037]
  PF3plat sets a new state-of-the-art across all benchmarks, supported by comprehensive ablation studies validating our design choices.<n>Our framework capitalizes on fast speed, scalability, and high-quality 3D reconstruction and view synthesis capabilities of 3DGS.
  arXiv  Detail & Related papers  (2024-10-29T15:28:15Z)
• Subsurface Scattering for 3D Gaussian Splatting [10.990813043493642]
  3D reconstruction and relighting of objects made from scattering materials present a significant challenge due to the complex light transport beneath the surface. We propose a framework for optimizing an object's shape together with the radiance transfer field given multi-view OLAT (one light at a time) data. Our approach enables material editing, relighting and novel view synthesis at interactive rates.
  arXiv  Detail & Related papers  (2024-08-22T10:34:01Z)
• LightOctree: Lightweight 3D Spatially-Coherent Indoor Lighting Estimation [4.079873017864992]
  We present a lightweight solution for estimating spatially-coherent indoor lighting from a single RGB image. We introduce a unified, voxel octree-based illumination estimation framework to produce 3D spatially-coherent lighting.
  arXiv  Detail & Related papers  (2024-04-05T07:15:06Z)
• CVT-xRF: Contrastive In-Voxel Transformer for 3D Consistent Radiance Fields from Sparse Inputs [65.80187860906115]
  We propose a novel approach to improve NeRF's performance with sparse inputs. We first adopt a voxel-based ray sampling strategy to ensure that the sampled rays intersect with a certain voxel in 3D space. We then randomly sample additional points within the voxel and apply a Transformer to infer the properties of other points on each ray, which are then incorporated into the volume rendering.
  arXiv  Detail & Related papers  (2024-03-25T15:56:17Z)
• Analytic-Splatting: Anti-Aliased 3D Gaussian Splatting via Analytic Integration [49.004898985671815]
  3DGS is not alias-free, and its rendering at varying resolutions could produce severe blurring or jaggies. This is because 3DGS treats each pixel as an isolated, single point rather than as an area, causing insensitivity to changes in the footprints of pixels. We introduce this approximation in the two-dimensional pixel shading, and present Analytic-Splatting, which analytically approximates the Gaussian integral within the 2D-pixel window area.
  arXiv  Detail & Related papers  (2024-03-17T02:06:03Z)
• pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction [26.72289913260324]
  pixelSplat is a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time and memory-efficient rendering for scalable training as well as fast 3D reconstruction at inference time.
  arXiv  Detail & Related papers  (2023-12-19T17:03:50Z)
• GIR: 3D Gaussian Inverse Rendering for Relightable Scene Factorization [62.13932669494098]
  This paper presents a 3D Gaussian Inverse Rendering (GIR) method, employing 3D Gaussian representations to factorize the scene into material properties, light, and geometry. We compute the normal of each 3D Gaussian using the shortest eigenvector, with a directional masking scheme forcing accurate normal estimation without external supervision. We adopt an efficient voxel-based indirect illumination tracing scheme that stores direction-aware outgoing radiance in each 3D Gaussian to disentangle secondary illumination for approximating multi-bounce light transport.
  arXiv  Detail & Related papers  (2023-12-08T16:05:15Z)
• GPS-Gaussian: Generalizable Pixel-wise 3D Gaussian Splatting for Real-time Human Novel View Synthesis [70.24111297192057]
  We present a new approach, termed GPS-Gaussian, for synthesizing novel views of a character in a real-time manner. The proposed method enables 2K-resolution rendering under a sparse-view camera setting.
  arXiv  Detail & Related papers  (2023-12-04T18:59:55Z)

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.