Gaussian Point Splatting

It 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.

[1] https://ecstatica.fandom.com/wiki/Ecstatica

I really wantt to get into splatting and I have the tools: good camera, v comfy in blender, comfy with graphics programming ideas, 4080. But I haven't found a good 'all in one intro' to it yet. Possibly because I'm foss-biased and have dismissed proprietary options. But does anyone know of a good 'vertical tutorial' on this stuff?

It seems like there are fairly regular posts on HN about splatting, and most appear to be fairly technical or proof-of-concept level. While the outputs look nice, I’m not sure that I could distinguish them from a nice ray-traced scene. What I think I’m missing is the “why?” of splatting. What are the material benefits of this area of research?

When looking at their linked interactive viewer it looks like they need 128 spp for the image quality to equal 3dgs. Maybe you can reduce that with some temporal tricks and noise reduction filtering, but that's still a lot of samples.

Can someone point to a resource/tutorial for learning point splatting (the 90s rendering technique)? Gaussian Splatting has completely over taken the search results, and the original technique is now near impossible to find.

I love this site design. It uses the entire width of the monitor rather than a slender column of pixels down the middle with large blocks of unused space on either side, with a font for my old man eyes.

<3

Could this be a new direction for Google Streetview perhaps?

Did not read the paper (sorry) but I wonder how this compares to mesh splatting (https://meshsplatting.github.io/). I feel like mesh splatting can produce higher quality results because triangles are very good at representing sharp features, and gaussians aren't.

My dumb idea... do outdoor scans, and then convert the contents into 1m^2 blocks... And then, just dumbly stitch them together.

Kind of like Minecraft... but with user-generated gaussian-splat blocks.

Really nice idea for 3DGS rendering - though the main problem is the noise (an unfortunate issue for all Monte-Carlo based methods).

I think future papers would probably continue improving on this method and focus on how to sample the points more efficiently while being unbiased (similar to how ray-tracing solved their performance issues). Or maybe... we can just add a deep-learning based denoiser and call it a day!

Video overview of the technology: https://www.youtube.com/watch?v=X8yRlA7jqEQ

Ordinarily I don't prefer video, but the visuals are helpful here.

Also, an online interactive, but it seems to only work in Chrome: https://superspl.at/scene/ff1d0393

This feels like Monte Carlo rendering applied to rasterization. I'm wondering if it's a brand-new or a well established methodology

Sorting the gaussians is the compute heavy part in gaussian splatting. So, Im guessing this will give only marginal improvement in terms rendering speed.

Their point splatting method is orthogonal to level-of-detail rendering (they reference a few papers which try to do this), so both point splatting and LoD could be combined in the future for an even greater performance gain during rendering. They already implement occlusion and frustum culling.

Point splatting does introduce a lot of noise though, and their denoiser introduces ghosting, but they say a more sophisticated denoiser would give considerably better quality.

> millions of threads

Really?! What OSs can handle that many native threads?

Also, this seems quite similar to stochastic progressive drawing of pointclouds for realtime that has been done for > 15 years in the VFX industry with GPU shaders in a tiled/bucketed fashion, unless this isn't progressive maybe? (The fact it's been accepted for Siggraph likely indicates it's slightly different).