Geometry Gaussians: Decoupling Appearance and Geometry in Gaussian Splatting

2026-06-03

AI Summary

This work addresses the inherent conflict in 3D Gaussian Splatting (3DGS) between jointly modeling appearance and geometry, where direct geometric extraction often degrades rendering quality. To resolve this, the authors propose a lightweight decoupling mechanism that assigns each Gaussian an independent geometric opacity parameter and employs an opacity-guided optimization strategy. Leveraging geometric priors from vision foundation models, this approach enables disentangled modeling of appearance and geometry. The method significantly improves both novel-view synthesis quality and geometric reconstruction accuracy across multiple datasets, demonstrating particularly strong performance in complex scenes containing transparent objects.

Abstract

After the success of 3D Gaussian Splatting (3DGS) for novel view synthesis, many works have explored how to also use it for geometric surface representation. However, extracting accurate geometric information directly from 3DGS remains challenging and can often reduce the appearance rendering quality. In this work, we show that 3DGS in its default form is inheritedly unsuited to represent texture and geometry at the same time, by training with complete ground-truth texture and geometry information. We also propose a simple solution by applying a single additional geometry opacity parameter to each splat, together with an optional transparency-curated optimization pipeline. Our experiments, both with ground-truth and vision foundation model geometric input, show that this change leads to improved rendering and geometry performance on a wide variety of dataset, and especially complex scenes with transparent objects benefit significantly from our method.

Problem

• 3D Gaussian Splatting
• geometry representation
• appearance rendering
• novel view synthesis
• transparent objects

Innovation

• Geometry Gaussians
• 3D Gaussian Splatting
• geometry-appearance decoupling
• opacity parameter
• novel view synthesis