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Models, splats and video

Video to 3D (experimental)

Walk through a place with a camera and get the place back as a coloured point cloud, on your own machine, with a choice of reconstruction engine. Experimental - how well it works depends on the capture.

Where File › Video to 3D (Experimental)… Tier Free
Doll-house view of a room reconstructed from a phone video, rendered as a point cloud
A room from a phone video, back as a point cloud.

When to use it

For a quick 3-D record of a room or a small site when no scanner is at hand. It is not a survey: there is no scale control and no accuracy statement, and the result should not be measured as if it were a laser scan.

Step by step

  1. Open File › Video to 3D (Experimental)….
  2. Choose an engine: Geometry only (the default: no model and no GPU, pure Rust, needs nothing else), Depth Anything 3 (handles shakier footage and wider turns) or VGGT (the densest result, for a room walked slowly). An engine not included in your build is shown as Not in this build.
  3. Press Choose a video… and pick an mp4, mov, mkv, webm, avi or m4v file.
  4. Wait for the reconstruction. Long clips are processed in windows and glued with a Sim(3) pose graph, then oriented so gravity points down.
  5. The result opens as a point cloud: segment it, classify it, voxelise it or export it like any other.
The Video to 3D window: the three engines VGGT, Depth Anything 3 and Geometry only, and Choose a video
Three engines; the one that needs nothing else is the default.

What it was measured at

Measured

Depth Anything 3 running through the pure-Rust tract engine on the CPU takes about 23 s a frame. The default build links no C at all; the ONNX Runtime engines are opt-in builds.

Limits, stated

  • Experimental. Results depend heavily on the capture: slow, steady, well-lit walks work best.
  • No metric scale: the reconstruction’s size is arbitrary until you rescale it by hand.
  • Which engines are present depends on the build; the default build ships the engine that needs nothing else.

Related questions

Does classification need a powerful GPU?

No. The classifiers, segmentation, decomposition and the ground filter run on the CPU, on your machine. The GPU draws the scene.

Does my data leave my machine?

No. Files are opened, processed and written locally. N3D has no upload, no cloud service and no account.

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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