Compression of 3D Gaussian Splatting Data Using GPU-friendly Graphics Texture Coding

2026-07-16 · Source: Computer Vision and Pattern Recognition · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Computer Graphics & Rendering · Depth: Expert, quick

Summary

A new method addresses the significant memory demands of 3D Gaussian Splatting (3DGS) scenes, which arise from spherical harmonic (SH) coefficients used for view-dependent color. Current compression techniques for 3DGS often fail to utilize modern Graphics Processing Units (GPUs) for parallel decoding and rendering. This proposed approach compresses SH color coefficients by employing GPU-friendly texture compression schemes, such as BC1 and BC7 formats, which benefit from dedicated hardware acceleration. The method achieves more effective compression than 2D textures by grouping and reordering primitives locally based on color. It also incorporates a bit-rate control strategy that maintains random access, crucial for large-scale parallelization without impacting rendering performance. Experimental results demonstrate that GPU-based decompression yields negligible or imperceptible visual quality degradation in rendered 3DGS scenes.

Key takeaway

For Computer Vision Engineers and AI Scientists optimizing 3D Gaussian Splatting (3DGS) scenes, this method provides a critical approach to significantly reduce memory requirements for view-dependent color data. By adopting GPU-friendly texture compression formats like BC1 or BC7, you can achieve efficient parallel decoding with dedicated hardware acceleration. This allows for substantial memory savings and improved scalability for large 3DGS scenes, ensuring high-quality rendering performance with negligible visual degradation. You should evaluate integrating these texture compression schemes into your 3DGS pipelines.

Key insights

Compressing 3D Gaussian Splatting's spherical harmonic coefficients with GPU-optimized texture formats significantly reduces memory while preserving visual quality.

Principles

• Exploit GPU hardware acceleration for parallel decoding.
• Group and reorder primitives locally by color for better compression.
• Maintain random access for parallelization via bit-rate control.

Method

Compress spherical harmonic color coefficients using GPU-friendly texture compression schemes (e.g., BC1, BC7), exploiting local primitive grouping by color and a random-access preserving bit-rate control strategy.

In practice

• Apply BC1 or BC7 texture formats for 3DGS color data.
• Implement local primitive reordering for compression efficiency.

Topics

• 3D Gaussian Splatting
• GPU Acceleration
• Texture Compression
• Spherical Harmonics
• Computer Graphics
• Memory Optimization

Best for: Research Scientist, AI Scientist, Computer Vision Engineer, AI Hardware Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Computer Vision and Pattern Recognition.