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SniperJake945

@tearsofjake.bsky.social
290 followers 68 following 69 posts

Computer Graphics Investigator (CGI)

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SniperJake945 @tearsofjake.bsky.social · 16/06/2026
Hope you're doing alright!!!
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SniperJake945 @tearsofjake.bsky.social · 18/02/2026
VoroNERF is coming along better now that i fixed a huge bug with my Top K selection of sites! It's still not perfect of course, lots of bugs and stuff to fix. This is with 60k voronoi sites, using the 16 closest sites around any sampling position along the render rays.
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SniperJake945 @tearsofjake.bsky.social · 25/01/2026
voronoi based NERF training isn't going incredibly well... 😂20k iterations with 80k voronoi sites takes about 10 hours to train. And it still looks dog water. Definitely need more sites and some better approach to accelerating sampling....
voronerf outputground truth lego from the back
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SniperJake945 @tearsofjake.bsky.social · 17/01/2026
Voronoi implicit but this time in 3d. It's not fully NERF mode yet, as I'm not doing any kind of sampling along rays, this is just trying to learn volumetric data. 30,000 Voronoi sites. Probably not enough for the pighead, but it's just a fun first test.
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SniperJake945 @tearsofjake.bsky.social · 10/01/2026
Lebronsketball 2
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SniperJake945 @tearsofjake.bsky.social · 10/01/2026
Lebronsketball 1
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SniperJake945 @tearsofjake.bsky.social · 10/01/2026
*morphs your cat*
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SniperJake945 @tearsofjake.bsky.social · 04/01/2026
Gaboronoi (top) vs Anisotropic Voronoi (bottom), with 5000 Sites. I feel like the anisotropic voronoi's artifacts are more aesthetically pleasing. Gaboronoi is faster to train by a lot! I've compiled all of my recent voronoi experiments into a collab: colab.research.google.com/github/jaker...
Gaboronoi (top) vs Anisotropic Voronoi (bottom)
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SniperJake945 @tearsofjake.bsky.social · 04/01/2026
Assuming uniform weights and frequencies, and random colors and anisotropy directions, this is what an example gaboronoi diagram would look like.
example gaboronoi
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SniperJake945 @tearsofjake.bsky.social · 04/01/2026
I'm once again making neural implicits of my cats. This time we're back to the voronoi. Gabor noise style. We weight the result of the softmax at any site i by sin(F_i*(x_i-x_j)•u_i) where F_i is learned frequency and u_i is a learned anisotropy direction. I call it Gaboroni
cat neural implicitgaboronoi tesselation
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SniperJake945 @tearsofjake.bsky.social · 31/12/2025
These are the noise layers that are all summed up to get the predicted image. each noise layer is colored with two colors, and each layer has a circular mask associated with it as well. I scaled the values here by a factor of ten so that they're easier to see.
noise layers
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SniperJake945 @tearsofjake.bsky.social · 31/12/2025
Wanted to make a neural implicit that's just layers of anisotropic simplex noise. Turns out it works pretty well. With 24 layers of simplex noise each with a 96x96 texture of anisotropy data we can get this kind of result! It's not at all a good compression method but it's fun and cool :)
predicted catsground truth cats
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SniperJake945 @tearsofjake.bsky.social · 27/12/2025
They like to hug now that they're older
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SniperJake945 @tearsofjake.bsky.social · 26/12/2025
Here's the aforementioned paper: sphericalvoronoi.github.io All credit to Lucky Lyinbor for the idea to apply this to euclidean voronoi. Also here's the ground truth image
Ground truth cats
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SniperJake945 @tearsofjake.bsky.social · 26/12/2025
I had the idea to incorporate anisotropy into the recent Spherical Voronoi paper. And when we apply their ideas to euclidean problems (not Spherical) the results are pretty great when anisotropy is used. This is 3000 anisotropic sites vs 3000 isotropic sites. Same learning rates for both
Learned anisotropic repLearned isotropic repAnisotropic voronoiIsotropic voronoi
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SniperJake945 @tearsofjake.bsky.social · 12/12/2025
For the snow on the hedge maze in Zootopia 2, we cast rays upwards from each leaf and if it didn't collide with anything we instanced a snow chunk onto it. We made a few variants of the snow chunks to add extra variation.
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SniperJake945 @tearsofjake.bsky.social · 29/07/2025
The least obvious part of all of this is how to construct that metric tensor G from a given vector, but it turns out it's super straight forward. The attached example shows how to do so for a 3D metric tensor. In our paper we outline specific bounds for the sizing of this metric.
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SniperJake945 @tearsofjake.bsky.social · 29/07/2025
Just to elucidate the idea a bit more, on the left we have the original perlin noise algorithm, and on the right we have the steerable version, with the changes underlined in red. We simply add a second set of weights, and incorporate our metric into the original dot product step
showing the difference between algorithms.
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SniperJake945 @tearsofjake.bsky.social · 29/07/2025
New at #SIGGRAPH2025: Can we make Perlin Noise stretch along some underlying vector field? Well it turns out it's possible with two simple additions to the original method! No need for advection or convolutions. Find the paper and implementations here: github.com/jakericedesi...
Anisotropic perlin noise on Suzanne
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SniperJake945 @tearsofjake.bsky.social · 04/01/2025
Distances to LP Voronoi Edges :) shadertoy.com/view/MXVyz1
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SniperJake945 @tearsofjake.bsky.social · 18/12/2024
Distances to the boundary of voronoi in L4. shadertoy.com/view/lfKfWV Hopefully it doesn't crash webgl on your device! :)
vowonoi
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