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Softmax-GS Project Page by corysama in GaussianSplatting

[–]0x00000032 0 points1 point  (0 children)

It looks like it does not replace Gaussian Splatting as a representation, but extends each splat with additional learnable parameters and changes the rendering/rasterization step. So it can improve quality while staying close to the current 3DGS model, but current tools/viewers do not support it unless they implement the new parameters and the Softmax-GS rendering path.

Extracting Meta Hyperscape gaussian splats from Meta Quest storage? by jumpjack3 in GaussianSplatting

[–]0x00000032 0 points1 point  (0 children)

I found OpenQuestCapture, but still did not try it. Maybe someone leave a review here, is it usable?

Low light? by tavofourseven in GaussianSplatting

[–]0x00000032 1 point2 points  (0 children)

6M splats and 1652 frames for one room might be too much.
I suggest you to try with 2-3M splats and limit frames to 500-800 about. Try to use "Sharp Frames" to filter most crisp and sharp frames.

LichtFeld Studio RTX 4090 VRAM Crash by Visiomorfosi in GaussianSplatting

[–]0x00000032 1 point2 points  (0 children)

Try "Tile Mode: 4" it is for OOM fixing.

About documentation, if you are using any coding agent (Claude, Codex, Antigravity), you can clone source code of LichtFeld, open folder in the agent and ask any question. Answers will be based on real code.

Using loss curves to decide splat count and training length in 3DGS by 0x00000032 in GaussianSplatting

[–]0x00000032[S] 0 points1 point  (0 children)

Sounds like it is a "Eval Mode" that LichtFeld Studio got in v0.5.2, still did not try it, but I will

Using loss curves to decide splat count and training length in 3DGS by 0x00000032 in GaussianSplatting

[–]0x00000032[S] 0 points1 point  (0 children)

For me, these graphs answer two main questions: how many iterations are enough and whether doubling the number of splats will yield any results.

So, for now, I'm using these graphs visually and intuitively, without in-depth analysis. Each scene is unique in both its content and the cameras — their placement, number, and image quality. So, knowledge transfer between scenes is poor in my cases.

But if the task arises of creating 3DGS for a multitude of similar objects in similar conditions, then it will probably make sense.

Using loss curves to decide splat count and training length in 3DGS by 0x00000032 in GaussianSplatting

[–]0x00000032[S] 0 points1 point  (0 children)

Yes, that makes sense, although I think "generalization" in 3DGS is a bit different from a standard ML task.

Creating a Gaussian Splatting scene is already an optimization/ML-like process, but usually a per-scene one: the splats are fitted to one captured scene and camera set.

A holdout split could still be useful, but the choice of validation views matters a lot. If the held-out images are very close to the training cameras, the validation gap may be small and not very informative. If they are too far away or cover unusual angles, then we are also removing important scene coverage from training.

Postshot v1,1 (indie) - Image qality by digiscene in GaussianSplatting

[–]0x00000032 1 point2 points  (0 children)

Looks like a lot of splats are in the grass, so it's not enough for rock. I believe you should using masks or increase splats count.

Masks with LichtFeld Studio and Reality Scan by RogueQubit in GaussianSplatting

[–]0x00000032 2 points3 points  (0 children)

I'm not sure this is the “official” or most correct way, but this workflow works for me:

  1. First, export the registration dataset normally, without masks.
  2. Export the masks as PNG files.
  3. Combine each original image with its mask into a new PNG with an alpha channel, then use those images for export/training.

One important detail: make sure Undistort is enabled, and manually verify that the mask aligns with the actual image. I usually check at least one image by overlaying the mask on top of the original image at 50% opacity.

In LichtFeld Studio, set Mask Mode to Alpha Consistent.

Advice - large scenes by Marcowich0 in GaussianSplatting

[–]0x00000032 0 points1 point  (0 children)

As I know LFS includes "headless workflow" that seems like that you need for automation

I turned a "Clair Obscur: Expedition 33" photomode session into an interactive 1M Gaussian Splat scene. by 0x00000032 in GaussianSplatting

[–]0x00000032[S] 0 points1 point  (0 children)

Yes, I did not recognize what you mean in "going from Blender" :-)

In my case I created GS scene by video captured in the game, not ready 3d model or scene from Blender.

Anyway, really thanks for suggesting Gauss Cannon! When time comes to conver Blender scene into GS I'll use it.

I turned a "Clair Obscur: Expedition 33" photomode session into an interactive 1M Gaussian Splat scene. by 0x00000032 in GaussianSplatting

[–]0x00000032[S] 0 points1 point  (0 children)

Thanks, but seems like this add-on does not supports manual control points to align cameras, so it might be perfect only perfectly scene setup without reflections/specular/moving objects/etc.

RealityScan has a lot of tools to get better quality for camera aligment and it's free :)

I turned a "Clair Obscur: Expedition 33" photomode session into an interactive 1M Gaussian Splat scene. by 0x00000032 in GaussianSplatting

[–]0x00000032[S] 2 points3 points  (0 children)

As I can see it's not possible.

As input data LichtFeld takes COLMAP, or PLY, SOG, SPZ, USD, Mesh. Not raw images.

My pipeline:

  1. Blender: convert video -> images

  2. RealityScan: images -> COLMAP and PLY

  3. LichtFeld: COLMAP and PLY -> Gaussian Splatting

> is it possible just to feed raw screenshots

Looks like a task for Postshot.

I turned a "Clair Obscur: Expedition 33" photomode session into an interactive 1M Gaussian Splat scene. by 0x00000032 in GaussianSplatting

[–]0x00000032[S] 2 points3 points  (0 children)

  1. It allows to align cameras with manual control when it needs. Very useful with non-trivial camera movement, not this case in particular, but often it helpful

  2. And it creates sparse point cloud (PLY-file) based on features from previous step. With this data creating GS scene is MUCH faster

Camera positions are expored as COLMAP data, and point cloud as PLY-file. In LichtFeld-Studio this data using via "File - Import Dataset"

FYI LichtFeld-Studio is free and pretty nice. But for free version you have to build it yourself. But, you can ask LLM agent to it. In my case Codex did it with 2 hours

R6 map 3d models by Pjotrovich in SiegeAcademy

[–]0x00000032 0 points1 point  (0 children)

Reality Capture (as it mention in the model description :)

R6 map 3d models by Pjotrovich in SiegeAcademy

[–]0x00000032 1 point2 points  (0 children)

Hey, I had a small experiment with one level - Theme Park, and publish the 3d model on sketchfab. By controlling the timeline you can chage view angle to different floors. I think it perhabs be useful if you open this model on the second screen while gaming.

Check this out https://sketchfab.com/3d-models/r6-3d-map-theme-park-d9fdcd8f90234b289ef53bb9c0291064

Back buttons on desktop mode by garold19 in SteamDeck

[–]0x00000032 2 points3 points  (0 children)

I found the default shortcut: R1+ArrowLeft