alt Hacker NewsIt will be interesting to see the first AAA game that uses these methods instead of rendering a 3D world. Even if made from CGI worlds, it would be a very interesting approach and with somewhat predictable performances.
Reminds me of Ecstatica [1], a 1994 game that had intense visuals with a very odd/different rendering engine made of 3D ellipsoids; in a way really crude splats in gouraud shading.
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There was this FPS demo recently https://playcanv.as/p/qxGSuzYq/
People have also converted some small sections of Unreal 5 demos into splats https://superspl.at/scene/692c4f91
Or perhaps use a real world scan - it was suggested this one would make an ideal setting for zombies https://superspl.at/scene/6359774f
Many years ago there was a game called Casebook[1], a small little detective game where you investigated rooms for clues. But unlike similar FMV games where you jumped from point to point, it had photorealistic environments that could be smoothly walk around in, much like later lightfield or gaussian splatting experiments.
This is "rendering a 3D world". It's basically the exact same techniques that traditional rendering uses, just with a different primitive that's not triangles. Everything else pretty much carries over.
If you mean the technique of splatting specifically, Dreams for PS4 [1] is prior art.
If you mean pre-rendering, there's Myst and games like the original FF7 for PS1.
Dreams for PS4 used point splatting and has a very unique look as a result. The splats were created from distance fields instead of being scanned, so they don't look like modern gaussian splats. They have a painterly look instead. https://youtu.be/2ltgkcoQzow
Note that the first published work of rendering Gaussian Volumes was in this 1991 paper (https://articles.tomasparks.name/publications/Westover1991.p...) - so 3DGS is really a rehash of an old method from the 90s!
The contributions of 3DGS lie in how fast you can make them in modern GPU hardware (tiling + sorting with threads), and how to make the pipeline differentiable so that you can fit the Gaussian splats with photogrammetry data. Similar to the history of deep learning, it became technically feasible once the GPU hardware was powerful enough.