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3D Gaussian Splatting is a rasterization technique described in 3D Gaussian Splatting for Real-Time Radiance Field Rendering that allows real-time rendering of photorealistic scenes learned from small samples of images. This article will break down how it works and what it means for the future of graphics.

That's a very brief overview of what 3D Gaussian Splatting is. Next, let's walk through the full procedure described in the paper.

The first step is to use the Structure from Motion (SfM) method to estimate a point cloud from a set of images. This is a method for estimating a 3D point cloud from a set of 2D images. This can be done with the COLMAP library.

Next, each point is converted to a gaussian. This is already sufficient for rasterization. However, only position and color can be inferred from the SfM data. To learn a representation that yields high quality results, we need to train it.

The training procedure uses Stochastic Gradient Descent, similar to a neural network, but without the layers. The training steps are:

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