GRTX: Efficient Ray Tracing for 3D Gaussian-Based Rendering
Junseo Lee, Sangyun Jeon, Jungi Lee, Junyong Park, Jaewoong Sim
Abstract
3D Gaussian Splatting has gained widespread adoption across diverse applications due to its exceptional rendering performance and visual quality. While most existing methods rely on rasterization to render Gaussians, recent research has started investigating ray tracing approaches to overcome the fundamental limitations inherent in rasterization. However, current Gaussian ray tracing methods suffer from inefficiencies such as bloated acceleration structures and redundant node traversals, which greatly degrade ray tracing performance.
In this work, we present GRTX, a set of software and hardware optimizations that enable efficient ray tracing for 3D Gaussian-based rendering. First, we introduce a novel approach for constructing streamlined acceleration structures for Gaussian primitives. Our key insight is that anisotropic Gaussians can be treated as unit spheres through ray space transformations, which substantially reduces BVH size and traversal overhead. Second, we propose dedicated hardware support for traversal checkpointing within ray tracing units. This eliminates redundant node visits during multi-round tracing by resuming traversal from checkpointed nodes rather than restarting from the root node in each subsequent round. Our evaluation shows that GRTX significantly improves ray tracing performance compared to the baseline ray tracing method with a negligible hardware cost.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 0e65ee0e-a852-48cd-ba83-51de831370b1Builds on35
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 5,687 citations
- Instant neural graphics primitives with a multiresolution hash encodingThomas Müller, Alex Evans, Christoph Schied, Alexander KellerSIGGRAPH 2022 · 4,089 citations
- Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance FieldsJonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan et al.CVPR 2022 · 1,603 citations
- Plenoxels: Radiance Fields without Neural NetworksSara Fridovich-Keil, Alex Yu, Matthew Tancik, Qinhong Chen et al.CVPR 2022 · 1,237 citations
- Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields ReconstructionCheng Sun, Min Sun, Hwann-Tzong ChenCVPR 2022 · 859 citations
Related papers
- GauTracer: Extending Ray Tracing Accelerator for Gaussian-Based Scene RepresentationLizhou Wu, Kunchen Zou, Yuzheng Lin, Chixiao Chen et al.ISCA 2026
- GHPT: Real-Time Relightable Gaussian Splatting using Hybrid Path TracingJinyang Bo, Fan Dou, Wenrui Quan, Shangxun Liu et al.CVPR 2026
- GSCore: Efficient Radiance Field Rendering via Architectural Support for 3D Gaussian SplattingJunseo Lee, Seokwon Lee, Jungi Lee, Junyong Park et al.ASPLOS 2024 · 77 citations
- Radiant Foam: Real-Time Differentiable Ray TracingShrisudhan Govindarajan, Daniel Rebain, Kwang Moo Yi, Andrea TagliasacchiICCV 2025 · 14 citations
- Faster-GS: Analyzing and Improving Gaussian Splatting OptimizationFlorian Hahlbohm, Linus Franke, Martin Eisemann, Marcus A. MagnorCVPR 2026 · 16 citations
