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Gaussian splatting

Desktop Gaussian splatting software

Neurones 3D is desktop Gaussian splatting software: open a splat capture (PLY or SPZ), stand inside it at interactive frame rates, put it in the same scene as a laser scan, convert it to a real point cloud, or mesh it into a level-of-detail chain a game engine can open. On your own machine, with no upload.

By Dr. Florent Poux, 3D Geodata Academy · Updated

Photoreal interior of an abandoned room with wood panelling and green wallpaper, rendered from 3D Gaussian splats
Standing inside a Gaussian splat scene: no mesh, no textures.

At a glance

Short statements, each one checkable. Where there is a number, it was measured, and the guides say on what.

  • N3D opens PLY (INRIA convention, told apart from a plain cloud on load) and SPZ (Niantic) splat files.
  • It renders with a true EWA rasteriser (screen-space covariance, anti-aliased, back-to-front), at about 60 FPS at 2 million splats.
  • A level-of-detail tree for splats draws a 1.92 million splat capture 2.4 times faster at a 500,000-splat budget and 4.6 times faster at 150,000.
  • The tree’s merged Gaussians cost 1.14 times the source, and conserve alpha mass rather than thinning the scene.
  • Splats convert to a point cloud by oriented surface sampling, so segmentation, classification and export apply.
  • Export splats for a game engine writes a three-level glTF chain, _LOD0 to _LOD2.
  • Two captures of one place can be registered and merged into one scene.

How splats are drawn and used

A splat is a piece of surface

A point is a sample of a surface; a splat is a piece of surface. Thinning splats the way a point cloud is thinned makes the scene transparent rather than coarse, so N3D’s splat tree is a replacement hierarchy: every node carries merged Gaussians, moment-matched and conserving alpha mass, standing in for its subtree, and each frame draws a cut through the tree at the budget.

Sorting that never blocks

Splats must be drawn back to front. N3D sorts them on the CPU in parallel and in the background, so navigation never waits on a sort, and the per-frame budget (N3D_SPLAT_BUDGET, 2 million by default) keeps the frame rate steady.

From splats to survey data

Because splats convert to points, a splat capture can be segmented, classified, measured and exported like a scan, or placed beside one for comparison.

A Gaussian splat capture drawn through the level-of-detail tree at a reduced splat budget
1.92 million splats through the level-of-detail tree.
Photoreal room rendered from native 3D Gaussian Splatting data
Native 3D Gaussian splatting, EWA and anti-aliased.

Questions

Which Gaussian splatting formats does N3D open?

PLY in the INRIA convention, detected automatically, and Niantic’s compressed SPZ.

How fast is it?

About 60 FPS at 2 million splats. On a 1.92 million splat capture the level-of-detail tree is 2.4 times faster at a 500,000-splat budget, at a quality that cannot be picked out in a still.

Can I turn splats into a mesh or a point cloud?

Both. Convert to point cloud samples the splats’ surfaces; Export splats for a game engine meshes them at three resolutions into glTF files (Pro).

Can it stream splat scenes larger than video memory?

Not yet. The level-of-detail tree makes large captures fast, but the whole tree is uploaded to the GPU. Point clouds already stream beyond video memory.

Does N3D train Gaussian splats from photos?

No. It opens, renders, converts, merges and meshes splat captures made elsewhere. Its own video reconstruction produces point clouds, not splats.

The guides behind it

Each guide gives the menu path, the steps, the command-line equivalent and the limits.

See also

About

Why Neurones 3D exists.

Standing inside a 43.5 million point indoor laser scan rendered by Neurones 3D

I have spent years working with point clouds, and for most of them the software got in the way. I wanted one tool I would actually reach for every day: fast enough to enjoy, honest about what it does, and calm to use.

Neurones 3D started in Python, the way most of my research does. It worked, but it was heavy, and heavy tools quietly discourage you from opening them. So I rebuilt everything in Rust, from the file readers to the renderer, with one rule: stay frugal. A single small file, no cloud, no telemetry, billions of points on a laptop that is ten years old. In an age where every tool reaches for a data center, I wanted the opposite.

The goal is simple to say and hard to earn. One package that carries you from capture to understanding to deliverable, without exporting to five other programs along the way. Load a scan, a splat, a building, a phone video. See it, classify it, measure it, and send out something real. Together, in one place.

This is the tool I always wanted. I hope it becomes yours too.

Dr. Florent Poux 3D Geodata Academy

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