Gaussian splatting is one of the most significant advances in 3D scene representation in recent years — and it’s moving fast from research papers to practical pipelines. If you work in 3D capture, VR/AR development, visual effects, or digital twins, it’s worth understanding what it is, what it does better than existing methods, and where it fits alongside established technologies like photogrammetry and structured light scanning.
The short version: Gaussian splatting produces photorealistic 3D scenes from photographs — faster and with better visual fidelity than previous methods — but it works differently from traditional 3D scanning and produces a different kind of output.
What Is Gaussian Splatting?
Gaussian splatting (more precisely, 3D Gaussian Splatting, or 3DGS) is a method for representing a 3D scene as a collection of small, overlapping 3D Gaussian functions — “splats” — each with its own position, size, orientation, opacity, and color that varies with viewing direction. When rendered, these splats combine to reproduce the appearance of the scene from any viewpoint with high visual quality.
The scene is built from photographs, similar to photogrammetry, but the underlying representation is fundamentally different. Photogrammetry produces a polygon mesh with textures. Gaussian splatting produces a cloud of splats that encode both geometry and view-dependent appearance. This allows it to reproduce effects like reflections, translucency, and complex lighting that traditional mesh-based representations handle poorly.
The training process — converting a set of photographs into a Gaussian splat scene — is fast compared to Neural Radiance Field (NeRF) methods, which were the previous state-of-the-art for photorealistic novel view synthesis. And the resulting scenes render in real time, which opens up interactive applications that NeRF couldn’t support efficiently.
What Gaussian Splatting Does Better Than Photogrammetry
For photorealistic visualization, Gaussian splatting has clear advantages over traditional photogrammetry:
- Visual quality at challenging surfaces. Reflective surfaces, transparent materials, fine hair and vegetation, and complex lighting effects are reproduced more faithfully by splat-based representations than by meshes with textures. The view-dependent color model in Gaussian splatting captures how surfaces look different from different angles in ways that textures can’t.
- No mesh reconstruction required. Photogrammetry needs to reconstruct a polygon mesh from point cloud data — a process that can struggle with complex geometry, thin features, and surfaces that don’t photograph cleanly. Gaussian splatting sidesteps this entirely.
- Real-time rendering. Gaussian splat scenes can be rendered in real time at high quality, making them suitable for interactive applications including VR, AR, and web-based visualization.
What Gaussian Splatting Doesn’t Replace
Gaussian splatting is a visualization technology, not a measurement technology. This distinction matters enormously for engineering and manufacturing applications.
A Gaussian splat scene doesn’t produce dimensional data. You can’t extract accurate measurements from it, use it to drive CNC toolpaths, compare it against a CAD model for inspection, or use it as the basis for reverse engineering. The “geometry” in a Gaussian splat is implicit — encoded in the splats’ positions and sizes — not the kind of explicit surface geometry that engineering workflows require.
For applications where dimensional accuracy matters — reverse engineering, quality inspection, digital twin development, custom fabrication — structured light scanning and laser scanning remain the appropriate tools. Our 3D scanning services produce the kind of dimensionally accurate geometry that engineering and manufacturing workflows depend on. Gaussian splatting doesn’t compete with that; it serves a different purpose.
Where Gaussian Splatting Fits in Real-World Pipelines
The most natural applications for Gaussian splatting are where photorealistic visualization matters more than dimensional accuracy:
Product and real estate visualization. Capturing a product, space, or environment for interactive viewing — where the goal is visual quality and the ability to explore from any angle, not dimensional verification. Gaussian splatting can produce compelling results from a smartphone video walkthrough.
Virtual production and entertainment. Background environments and set captures for visual effects work, where the quality bar is high and the requirement is visual plausibility rather than engineering accuracy.
Heritage and cultural documentation. Capturing the visual appearance of artifacts, spaces, and sites for public access and archival — where the priority is preserving and communicating the visual experience. Our heritage and restoration work increasingly involves both dimensional scanning (for fabrication and conservation work) and visualization outputs for institutional clients.
VR and AR experiences. Environments for immersive experiences where photorealism matters. Gaussian splatting’s real-time rendering capability makes it viable for VR and AR pipelines in a way that heavier reconstruction methods aren’t.
The Bigger Picture: Complementary Technologies
The right mental model is that Gaussian splatting, photogrammetry, and structured light scanning occupy different positions in the broader landscape of 3D capture and representation. They’re not direct competitors — they answer different questions. A project might use structured light scanning for dimensional engineering work and Gaussian splatting for the client-facing visualization of the same object. Knowing which tool to reach for — and when to use more than one — is the skill that matters.
If you’re working on a project that involves 3D capture and aren’t sure which approach — or combination of approaches — is right for your application, reach out to our team. We work with the full range of scanning and capture technologies and can help you match the method to what the project actually needs.
