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Sample datasets

Every process in Neurones 3D can be tried without data of your own. The demo scenes are generated inside the app on the spot, so there is nothing to download.

The Demo scenes menu of Neurones 3D: indoor room, terrain city, powerline corridor, streetscape, factory pipework and sculpture, and two pairs of clouds for comparison and transfer
Every process can be tried on data generated on the spot.

Built into the app

Open File › Demo scenes. Each scene is generated when you pick it.

SceneGood for trying
Indoor room (point cloud)Indoor classification, decomposition, meshing, measurement
Terrain city (point cloud)Ground filter, terrain products, the Outdoor model
Powerline corridor (point cloud)The Powerlines model and instances, height above ground
Streetscape (point cloud)The Streetscape model
Factory pipework (point cloud)Cylinders in the decomposition
Sculpture (mesh)Mesh display, conversion to a point cloud

Under Two clouds at once:

  • Two surveys of one site (compare & detect change): a 2024 and a 2026 survey with a building demolished and one built, a 120 mm and a 10 mm settlement patch, and a stockpile grown by 1.5 m, with 8 mm of noise, so the level of detection is about 15 mm. Try M3C2 on it, and a volume on the stockpile.
  • Full scan + labelled subsample (transfer a column): a one-in-twenty subsample carrying a classification, to carry across to the full scan.

Public data the numbers were measured on

The figures on this site were measured on data anyone can obtain, so they can be checked.

  • S3DIS, Area 4: an indoor laser scan of about 43.5 million points from the Stanford 3D Indoor Scene Dataset. The indoor classifier, the decomposition, the scene graph and the floor plan figures use it. Available from its publishers under their own terms.
  • IGN LiDAR HD: France's national aerial LiDAR programme, published openly by the Institut national de l'information géographique et forestière. The ground filter's F1 of 90.3 % was measured against a tile's own production ground class, and the Outdoor model's 86.2 % against held-out tiles.

Customer data never appears on this site, in a figure or in a number.

Your own data

Anything in the format matrix opens by drag and drop. Nothing is uploaded: files are read, processed and written on your machine.

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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