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antimatter15
splat
JavaScript2023–2025
antimatter15 / splat

splat

WebGL 3D Gaussian Splat Viewer

Creative & Media
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7Distinct people
7Mentions
0Explicit recommenders
3.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

WebGL 3D Gaussian Splat Viewer

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month7 dated mentions

Observed mentions: 2023-09-11 19:22:55 UTC to 2025-05-08 19:27:27 UTC.

012342023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 commentsSep 20232023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-02-01 00:00:00 UTC to 2024-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-03-01 00:00:00 UTC to 2024-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-04-01 00:00:00 UTC to 2024-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-05-01 00:00:00 UTC to 2024-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-06-01 00:00:00 UTC to 2024-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-01 00:00:00 UTC to 2024-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJul 20242024-08-01 00:00:00 UTC to 2024-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-01 00:00:00 UTC to 2024-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-01 00:00:00 UTC to 2024-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-01 00:00:00 UTC to 2024-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-12-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2025-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-02-01 00:00:00 UTC to 2025-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-03-01 00:00:00 UTC to 2025-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-04-01 00:00:00 UTC to 2025-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-05-01 00:00:00 UTC to 2025-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsMay 2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC413
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC101
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC000
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC101
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC000
Feb 20242024-02-01 00:00:00 UTC2024-03-01 00:00:00 UTC000
Mar 20242024-03-01 00:00:00 UTC2024-04-01 00:00:00 UTC000
Apr 20242024-04-01 00:00:00 UTC2024-05-01 00:00:00 UTC000
May 20242024-05-01 00:00:00 UTC2024-06-01 00:00:00 UTC000
Jun 20242024-06-01 00:00:00 UTC2024-07-01 00:00:00 UTC000
Jul 20242024-07-01 00:00:00 UTC2024-08-01 00:00:00 UTC000
Aug 20242024-08-01 00:00:00 UTC2024-09-01 00:00:00 UTC000
Sep 20242024-09-01 00:00:00 UTC2024-10-01 00:00:00 UTC000
Oct 20242024-10-01 00:00:00 UTC2024-11-01 00:00:00 UTC000
Nov 20242024-11-01 00:00:00 UTC2024-12-01 00:00:00 UTC000
Dec 20242024-12-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
Jan 20252025-01-01 00:00:00 UTC2025-02-01 00:00:00 UTC000
Feb 20252025-02-01 00:00:00 UTC2025-03-01 00:00:00 UTC000
Mar 20252025-03-01 00:00:00 UTC2025-04-01 00:00:00 UTC000
Apr 20252025-04-01 00:00:00 UTC2025-05-01 00:00:00 UTC000
May 20252025-05-01 00:00:00 UTC2025-06-01 00:00:00 UTC101

What Hacker News says

7 sources
kragen·May 8, 2025
The particular kind of pathology I see here is a strong centralization of the Rust community under the control of an unaccountable leadership caste. The point of free-software licensing is to minimize the control "owners" of software have over their users, protecting those users from abuses by leaders. Somehow Rust users seem to have, to a significant extent, abdicated the rights guaranteed to them by the software license. For example, in your example of "inserting two mandatory ads to be watched during each Java compiler run", the OpenJDK license guarantees your right to remove those ads from your copy of javac, and to redistribute that copy of javac as the official Debian or Ubuntu version of javac. F-Droid does this routinely to such "antifeatures" in open-source Android applications, and of course Android itself exists because the
Read the rest
open-source licenses of projects like Harmony, IDEA, and Eclipse protect Google from such malfeasance. I'm not sure what the "average open-source project" is. Maybe something like https://github.com/justinasr/FantilatorOS/, the firmware for a redundant array of 64 inexpensive muffin fans that someone set up at CERN? https://web.archive.org/web/20231010215437/https://onlyfans.... Or https://github.com/antimatter15/splat, a Gaussian splat renderer in WebGL? I think those are both "non-average" in that they have a very above-average number of forks and stars. But, like the overwhelming majority of open-source projects, neither of them has a community in any meaningful sense, so I think the question doesn't make sense, given that it's a question about community dynamics.
In Matt Godbolt sold me on Rust by showing me C++
mk_stjames·Dec 21, 2023
Oof, the dependency tree on this. It uses diff-gaussian-rasterization from the original gaussian splatting implementation (which, is a linked submodule on the git, so if you are trying to git clone that dependency remember to use --recursive to actually download it). But that is written in mostly pure CUDA. That part is just used to display the resulting gaussian splatt'd model, and there have been other cross-platform implementations to render splats – there was even that web demo a few weeks ago, that was using WebGL [0] – and if that was used as a display output in place of the original implementation there is no reason people couldn't use this on non-Nvidia hardware, I think. edit: also device=cuda is hardcoded in the torch portions of the training code (sigh!). This doesn't have to be the case. pytorch could push this onto mps (met
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al) probably just fine. [0] https://github.com/antimatter15/splat?tab=readme-ov-file
In Splatter Image: Ultra-Fast Single-View 3D Reconstruction
teucris·Oct 14, 2023
I hacked in a weighted stochastic method into a WebGPU solution[0] and it worked surprisingly well. Essentially, given each pixel of a splat, pick a pseudo-random number from zero to one and if it’s lower than the alpha value for the pixel, draw over whatever is in the frame buffer at full opacity. The next step I wanted to try was to super-sample (eg render at double resolution) and linearly down sample. I imagine this would give a slightly noisy result that I think would be pretty visually pleasing. 0: https://github.com/antimatter15/splat
In Gsplat: CUDA accelerated rasterization of gaussians with Python bindings
Lichtso·Sep 11, 2023
Really cool, I am also working on a port of gaussian-splatting [0] but to WebGPU. Like all the other implementations I have seen so far, this also makes the same mistake when projecting the ellipsoids in a perspective: First you calculate the covariance in 3D and then project that to 2D [1]. This approach only works with parallel / orthographic projections and applying it to perspectives leads to incorrect results. That is because perspective projections have three additional effects: - Parallax movements (that is the view plane moves parallel to the ellipsoids) change the shape of the projected ellipse. E.g. a sphere only appears circular when in center of the view, once it moves to the edges it becomes stretched into an ellipse. This effect is manually counter balanced by this matrix I believe [2]. - Rotating an ellipse can change the p
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osition it appears at, or in other words creates additional translation. This effect is zero if the ellipse has one of its three axes pointing straight at the view (parallel to the normal of the view plane). But, if it is rotated 45°, then the tip of the ellipse that is closer to the view plane becomes larger through the perspective while the other end becomes smaller. Put together, this slightly shifts the center of the appearance away from the projected center of the ellipsoid. - Conic sections can not only result in ellipses but also parabola and hyperbola. This however is an edge case that only happens when the ellipsoid intersects with the view plane and can probably be ignored as one would clip away such ellipsoids anyway. The last two effects are not accounted for in these calculations in any of the implementations I have seen so far. What would be correct to do instead? Do not calculate the 3D covariance. Instead calculate the bounding cone around the ellipsoid which has its vertex at the camera position (perspective origin). Then intersect that with the view plane and the resulting conic section is guaranteed to be the correct contour of the perspective projection of the ellipsoid. [0]: https://github.com/graphdeco-inria/gaussian-splatting [1]: https://github.com/antimatter15/splat/blob/3695c57e8828fedc2... [2]: https://github.com/antimatter15/splat/blob/3695c57e8828fedc2...
In Show HN: Real-Time 3D Gaussian Splatting in WebGL

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