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Models, splats and video

Gaussian splats and level of detail

Stand inside a photoreal Gaussian splat capture (PLY or SPZ), draw it through a level-of-detail tree that keeps large captures fast, turn it into a real point cloud, or mesh it into a three-level glTF chain for a game engine.

Where File › Open… · File › Export splats for a game engine… · Process › Merge splat captures… Tier Free + Pro CLI splat-lod

Viewing, measuring and converting are free. The glTF level-of-detail chain is Pro.

Part of Gaussian splatting software, Benchmarks, Gaussian splatting to mesh.

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.

When to use it

To review and present a splat capture on the desktop, to measure in it, to bring it into the same scene as a scan, or to hand a game engine something it can actually open.

Step by step

  1. Open a .ply (a Gaussian splat file is told apart from a plain cloud on load) or a .spz with File › Open….
  2. Navigate as with any scene; fly mode works inside it. Splats re-sort in the background as you move, so navigation never waits on a depth sort.
  3. Large captures are drawn through the level-of-detail tree automatically. The per-frame budget is 2,000,000 splats; set N3D_SPLAT_BUDGET to change it.
  4. To work on points (segment, classify, export), use Process › Convert to point cloud…: oriented disc sampling, 5 million points by default.
  5. To merge a second capture of the same place, use Process › Merge splat captures… (see align and merge).
  6. For a game engine, File › Export splats for a game engine… meshes the splats at three resolutions and writes _LOD0.glb, _LOD1.glb and _LOD2.glb.
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.

What it was measured at

Measured

About 60 FPS at 2 million splats. On a 1.92 million splat capture the level-of-detail tree draws 2.4x faster at a 500,000-splat budget and 4.6x faster at 150,000, at a quality that cannot be picked out in a still. The tree’s merged Gaussians cost 1.14x the source.

Why a replacement tree

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 every node of the splat tree carries merged Gaussians standing in for its subtree, moment-matched and conserving alpha mass, and each frame draws a cut through the tree at the budget.

From the command line

n3d-render-cli splat-lod --input room.ply --out room.glb --levels 3        # room_LOD0.glb ... (Pro)
n3d-render-cli splat-tree --input room.ply --budget 500000                 # LOD statistics
n3d-render-cli export-cloud --input room.ply --out room_cloud.ply --samples 4000000   # (Pro)

Limits, stated

  • The splat tree is not yet out of core: the whole tree is uploaded, so it makes big scenes fast, not scenes larger than video memory possible.
  • There is no automatic metric scale for a splat capture; rescale it by hand in the reposition window.
  • Merging captures drops higher-order spherical harmonics.

Related questions

Can it stream splat scenes larger than video memory?

Not yet. The splat level-of-detail tree makes large captures fast (2.4 times faster at a 500,000-splat budget), but the whole tree is uploaded to the GPU. Point clouds, by contrast, stream beyond video memory already.

Can it put a splat capture at metric scale automatically?

No. Automatic metric anchoring needs a seven-parameter solve that is not built. A capture can be rescaled by hand in the layer’s Reposition window.

More in the FAQ.

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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