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2DGaussianSplatting

Video (Youtube)

A picture of Carl Friedrich Gauss approximated by 2000 2D Gaussian functions.

This repository contains a Jupyter Notebook (colab) that showcases how to reconstruct an image using 2D Gaussian functions with learned means, covariances and RGBA tints. It is based on the theory presented in 3D Gaussian Splatting for Real-Time Radiance Field Rendering.

Note that the purpose of the code is to only provide a bare bones version of the methodology, which omits basically all optimizations and bells & whistles. It's just for the fun of playing with this exciting technology.

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