A plain-language guide to the technology behind Splatoo — what it is, how it differs from older 3D methods, and why it makes real places explorable on any screen.
Gaussian splatting captures a real place in 3D as millions of tiny, soft points of light — not flat polygons.
Each point is a "splat": a position in space, a colour, a softness that decides how it fades at the edges, a level of transparency, and a shape — it can stretch and tilt to hug the surface it sits on. On its own a single splat is just a fuzzy blob. Stack a few million of them and the original scene reappears, with true depth, fine detail, and the exact light and atmosphere of the place it was captured in.
Under the hood it's a radiance field — a model of how light leaves every point of a scene in every direction. The first radiance fields (NeRFs) hid that information inside a neural network and had to compute each pixel on demand. Gaussian splatting stores it out in the open, as the splats themselves. There's nothing to infer at view time, so it draws fast — fast enough to explore smoothly in a browser, on a phone, with no app to install.
The remarkable part is that you don't model anything by hand. You photograph or film the space, and an optimiser rebuilds it for you.
Walk the space with a camera or even a phone, covering it from many overlapping angles. A few hundred frames is often enough for a room; larger spaces simply need more coverage.
Structure-from-motion software studies the frames, works out where each photo was taken, and lays down a rough starting cloud of points to build from.
Every point becomes a 3D Gaussian. The system renders the scene, compares it against the real photos, and nudges each splat's position, colour, size and opacity to close the gap — millions of tiny corrections, repeated until the render is hard to tell from the photographs. Along the way it adds splats where the scene is still blurry and deletes ones that aren't earning their place.
To draw a frame, the splats are projected onto your screen, sorted by depth and blended front-to-back. No neural network runs at view time — which is the whole reason it hits smooth, real-time framerates on ordinary hardware.
Training takes minutes rather than the hours older neural methods needed. And because the result is explicit — a literal set of splats rather than a black-box network — the scene can be moved, recoloured, trimmed or combined with others. That editability is what we build on.
Every earlier way of capturing reality trades something away. Gaussian splatting is the first that keeps photoreal quality and real-time speed at the same time.
It also clears the bar set by two older shortcuts. Raw LiDAR and point-cloud scans capture accurate geometry but look flat and lifeless without real lighting baked in. Plain video looks real but traps the viewer on a single fixed path. Splatting gives you both at once — the look of video with the freedom to move anywhere inside it.
The short version: it's the first method that looks like the real place and runs anywhere.
It's worth being straight about where the technique shines today and where it's still maturing.
Most of these are active research fronts moving quickly — and several are exactly where our capture and Unreal pipeline fill in the missing pieces.
A render shows someone what a space could look like. A scan lets them stand inside what it actually is. That difference is the whole point: people decide faster, trust what they're seeing more, and genuinely remember a place they've moved through rather than one they've only glanced at.
For a business, that turns into fewer wasted site visits, shorter sales cycles, and a single asset that works on a website, a sales call and an on-site screen alike. One capture, many places it can live.
And it's no longer experimental. Real-estate platforms have begun handing buyers splat tours, the technique has found its way into major film and visual-effects production, and capture apps are putting it in everyday hands. The industry calls this a "JPEG moment for spatial computing" — the point where 3D capture stops being a novelty and becomes ordinary.
The field is moving unusually fast. Four fronts matter most for where this goes next:
The direction is clear: spatial capture is becoming as casual as taking a photo — and as easy to share. We're building Splatoo for that world.
A raw scan is beautiful but passive. Splatoo turns it into something people can use.
We capture the place, clean it up, then layer a wayfinding system on top — points of interest, routes, services and content — so the space isn't just viewable, it's navigable. With our Unreal pipeline we can also bring in objects and scenes that don't physically exist yet, so reality becomes the starting point rather than the limit. The finished experience publishes straight to the web and to on-site kiosks, and quietly reports back on how visitors actually move through it.
One capture becomes a presentation, a sales tool, a guide and a touchpoint — all at once.
Reading about it only goes so far. Open a real walkthrough in the demo archive and move through a captured space yourself — drag the points, switch scenes, and see how it feels in the browser.
The plain-language explanation above is grounded in the primary research and reporting below.
We'll scan it, layer it, and hand you a walkthrough that runs anywhere.