Gaussian splatting is a fancy word for pointcloud but with coloured shapes instead of points.
Its been around for ages, but It was never used because if you have a million points in a point cloud, you'd need to artistically manipulate a million points.
Its like 3d hair, its pretty simple, just render a billion hairs, but in practice its hard to make it look good.
Here we tell a machine learning model to adjust the angle, colour, shape and size of a million primitives (ie a square, circle, triangle etc.) so that it looks like a the photos we provide.
It's a little bit more than that. Gaussians are view-dependent, which means that they can capture the full radiance field of the scene, rather than just the color and geometry of the objects. All the light bouncing around from different objects can be reproduced, including reflections etc.
Also maybe worth mentioning that the 2nd author of the InstantNGP paper is also a cofounder of and lead tech guy at Media Molecule, Alex Evans. I've been a huge fan of his work since 90s demoscene and briefly got to work with him at Lionhead Studios, guy's a legit genius.
Its been around for ages, but It was never used because if you have a million points in a point cloud, you'd need to artistically manipulate a million points.
Its like 3d hair, its pretty simple, just render a billion hairs, but in practice its hard to make it look good.
Here we tell a machine learning model to adjust the angle, colour, shape and size of a million primitives (ie a square, circle, triangle etc.) so that it looks like a the photos we provide.