iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splatting

In volume visualization, users can interactively explore the three-dimensional data by specifying color and opacity mappings in the transfer function (TF) or adjusting lighting parameters, facilitating meaningful interpretation of the underlying structure. However, rendering large-scale volumes demands powerful GPUs and high-speed memory access for real-time performance. While existing novel view synthesis (NVS) methods offer faster rendering speeds with lower hardware requirements, the visible parts of a reconstructed scene are fixed and constrained by preset TF settings, significantly limiting user exploration. This article introduces inverse volume rendering via Gaussian splatting (iVR-GS), an innovative NVS method that reduces the rendering cost while enabling scene editing for interactive volume exploration. Specifically, we compose multiple iVR-GS models associated with basic TFs covering disjoint visible parts to make the entire volumetric scene visible. Each basic model contains a collection of 3D editable Gaussians, where each Gaussian is a 3D spatial point that supports real-time scene rendering and editing. We demonstrate the superior reconstruction quality and composability of iVR-GS against other NVS solutions (Plenoxels, CCNeRF, and base 3DGS) on various volume datasets. The code is available at https://github.com/TouKaienn/iVR-GS.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-05-06
DOI
https://doi.org/10.1109/tvcg.2025.3567121
Citations
7
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
24.78
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article

iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splatting

Chaoli Wang, Siyuan Yao, Kaiyuan Tang
7 citations
IEEE Transactions on Visualization and Computer Graphics
Computer Graphics and Visualization Techniques
24.78
article

iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splatting

Chaoli Wang, Siyuan Yao, Kaiyuan Tang
article en
7 citations

Abstract

In volume visualization, users can interactively explore the three-dimensional data by specifying color and opacity mappings in the transfer function (TF) or adjusting lighting parameters, facilitating meaningful interpretation of the underlying structure. However, rendering large-scale volumes demands powerful GPUs and high-speed memory access for real-time performance. While existing novel view synthesis (NVS) methods offer faster rendering speeds with lower hardware requirements, the visible parts of a reconstructed scene are fixed and constrained by preset TF settings, significantly limiting user exploration. This article introduces inverse volume rendering via Gaussian splatting (iVR-GS), an innovative NVS method that reduces the rendering cost while enabling scene editing for interactive volume exploration. Specifically, we compose multiple iVR-GS models associated with basic TFs covering disjoint visible parts to make the entire volumetric scene visible. Each basic model contains a collection of 3D editable Gaussians, where each Gaussian is a 3D spatial point that supports real-time scene rendering and editing. We demonstrate the superior reconstruction quality and composability of iVR-GS against other NVS solutions (Plenoxels, CCNeRF, and base 3DGS) on various volume datasets. The code is available at https://github.com/TouKaienn/iVR-GS.

IEEE Transactions on Visualization and Computer GraphicsVol. 31(6)
University of Notre Dame (US)
Openalex Percentile: Top 1%
Computer Graphics and Visualization Techniques
24.78
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iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splatting — Chaoli Wang, Siyuan Yao, et al. · IEEE Transactions on Visualization and Computer Graphics (2025) | TGRS Research Map | TGRS