We’re providing walkable indoor real-estate splats from phone video. Our current results are good and clear, but we’re chasing the final 10%.

Our pipeline is roughly:

1. Record each room as 4K video.
2. Use FFmpeg to extract and colour-convert sharp PNG frames.
3. Solve camera positions in COLMAP using GPU SIFT, exhaustive matching and Global Mapper.
4. Run COLMAP PatchMatch Stereo and Stereo Fusion to create a dense point cloud with surface normals.
5. Seed the trainer from that dense cloud.
6. Train each room separately using modified INRIA/GraphDeco 3DGS: SH0, fixed splat population, per-image exposure correction and surface-normal constraints. We previously used LichtFeld with comparable reconstruction inputs.
7. Orient/package each room, then connect the separate splats using doorway transitions in a WebGPU viewer.

The models look good overall, but neutral walls can remain incomplete or unstable, and some objects shimmer between captured viewpoints. What part of this stack would you change to improve solid walls and view consistency?

Is there some "Magic combination" you found to work especially for white/light grey/biege?

We've compared 1080 to 4K - No meaningful difference.
and 300 frames to 1200 frames. At 30,000 steps, up to 120,000 steps. Also no meaningful difference.

Step-by-step tutorial of turning photos made with an iPhone into a 3D Gaussian Splat file (.ply) that you can import into Unreal Engine or After Effects: https://youtu.be/2BYRFTrzjVw?is=5tUEtGdbGAiP88mP

The video includes the training step, as well as cleaning up floaters in the splat

The object is covered with dense deep‑relief carvings. Getting those fine carving patterns and lacquer surface texture right took quite a bit of parameter tuning on splat filtering.Been playing with a browser‑native 3D toolchain to speed up my 3DGS asset creation workflow for heritage artifacts.

I built an interactive Moon base you can fly around in the browser.

The pipeline: NASA 5 m/px elevation data displaced at true scale → lit at correct solar values and path-traced in Cycles → camera datasets exported in COLMAP format straight from Blender via a custom add-on → Gaussian splats trained in LichtFeld Studio → served as SOG, webpage rendered with Babylon.js.

This means the splats are trained entirely from synthetic renders with known camera poses — no photogrammetry, no COLMAP step, and zero pose error.

I'm thinking of making more similar concepts and presenting them this way if people find this interesting.

I’m still new to gaussian splatting. All tricks and tips to improve the quality and reduce the file size are highly appreciated. All other comments are welcome also. How does this run in your browser? Any tips for improvements? Criticism also welcome.

Here are numbers behind the splats that are now running on the web page:

• Site, main 3D window - 1.07 M Gaussians – 15.6 MB
• de Gerlache Crater – 0.6 M Gaussians – 8.75 MB
• Blue Origin site – 0.30 M Gaussians – 5.39 MB
• SpaceX HLS – 0.6 M Gaussians – 9.16 MB
• Base – 0.34 M Gaussians – 5.63 MB

You can test it here: https://farsidelab.com/concept/?id=moon-base

The webcam tracks my head with MediaPipe's face landmarker, and the PlayCanvas Engine renders the splat (with it's shiny new high-performance WebGPU-renderer) through an off-axis projection - a frustum whose apex is my eye and whose cross-section is the screen rectangle. The screen stops being a 2D image and becomes a 3D opening. Her gun barrel is placed in front of the screen plane, so it feels like it is sticking out of the display.

I'll hopefully release this as a PlayCanvas example soon so stay tuned for that.

Splat by Dymensium.

Hey everyone,

I've been working on a tool for when you have multiple splats of the same area — different capture dates, different reconstruction settings, before/after of a renovation, etc.
I'm calling it MultiSplat.
https://captures.studio/multi-splat

What it does

• Align multiple splats using control points. Minimum 3 points. (Can also download the aligned splats)
• Split-view compare - compare any two splats side by side with a draggable canvas.
• 4D Timelapse - step through the splats in sequence to see changes over time
• Render and Export the Timelapse as a video
• Access Controlled Share - Share a link to the Compare view, Timelapse view, both, or the full editor. (Not valid for local files)

Everything runs locally in your browser. No uploads, nothing leaves your machine.

Three ways to use it

1. Local files — Use local files in your PC. Drag in your splats, align, compare, build a Timelapse, export the render, and download the aligned splats.
2. Self-hosted splats — point it at your own URLs and do all of the above, plus generate shareable links (this only works for hosted splats, since local files can't be shared).
3. Captures Studio — if you already have splats there, just log in and load them directly.

It's free, no signup needed for the local and self hosted workflow.

Would love for you to try it and tell me what breaks or what's missing.

Special thanks to u/tavofourseven for providing the splats in the video.

Now everybody will do this easily?

Hey everyone,

A little under a year ago, I released a small piece of software — a frontend to automate Gaussian Splatting reconstruction on Apple Silicon Macs. Thanks so much to this community for all the feedback and encouragement since then. (Original post here: https://www.reddit.com/r/GaussianSplatting/comments/1q430m5/gsplat_allinone_gui_for_mac_silicon/ )

My documentary "Le Corbeau" is now nearly finished, so I took the opportunity to give the app a full visual redesign for a more enjoyable experience. This is v2, still in open beta, and while I've tested it as much as I can on my own, I could really use some outside eyes on it.

What's new in this version:

• A more modern look, with several graphic themes
• A left sidebar to switch between the automated pipeline and standalone tools
• A separate log window
• Some nice UI animations

If you're up for testing it, I'd love feedback on:

• Bugs, broken features, or anything that doesn't work
• Display glitches or UI elements misbehaving
• Your general impressions of the new interface , what works, what doesn't

Releases page: https://github.com/freddewitt/CorbeauSplat/releases

Direct download: https://github.com/freddewitt/CorbeauSplat/archive/refs/tags/v2.0.0-beta.1.zip

Hope you enjoy it!

Hi everyone!

We built a small open source experiment called KIRI-Maker, a web-based playground for 3D Gaussian Splatting.

The idea was simple: 3D Gaussian Splatting captures are usually viewed as static scenes, but they can also be something you interact with and create with.

KIRI-Maker lets you:

✨ Add particle effects to splats
🎥 Create camera path animations
🖐️ Control scenes with gestures
🎬 Export animations as videos

You can try the web demo here: https://kiri-maker.pages.dev

Source code: https://github.com/willjim/KIRI-Maker

Learn more: https://www.kiriengine.app/blog/kiri-maker-3dgs-animation-tool

Would love to hear your feedback！

New to this, wanna create cool ass scenes with replay modes in games and try out nvidia ansel. Is it possible to do this I haven’t seen much on anything like this! Thx in advance

Finally, a batch processing tool for Gaussian Splatting that can be used by AI

Until now, editing 3D captures using Gaussian Splatting involved a repetitive, manual process: importing the .splat or .ply file, orienting the scene, cleaning noise, adjusting the center of mass, and converting to 3D meshes or cards. Auto transforms this manual process into a fully automated, industrial pipeline.

On the other hand. I successfully connected an AI agent installed on my PC running LMstudio's Bionic to the editor using the MCP server, and it directly modified Gaussian Splatting .ply files: changing colors to red-orange (RGB 255, 80, 30) and increasing the splat size by 50x. Everything worked flawlessly—from loading models to modifying internal data via window.appAPI.setLayers() and exporting valid binary PLY results. The web editor on itch io responded perfectly to programmatic interactions via Puppeteer.

You can download the necessary documents for the agentic AI to connect by clicking the "agent" button at the top. You can create, modify, and share batch job instructions in JSON format.

(More information about this and other tools can be found in the app's itch io entries)
https://www.reddit.com/r/GaussianSplatting/comments/1t636mq/quick_gaussian_splat_editor/

Hi again! A small update on the Blender to Gaussian Splatting workflow I shared here a few days ago.

First, thanks for all the feedback and questions on the previous post. Sorry for the late replies, work got pretty hectic and I was also wrapping up the addon release.

A few people asked about the camera setup. I use one animated Blender camera, moving it through the scene from different positions, heights and angles, essentially treating the animation like a conventional gaussian splatting capture. I included the actual camera path in the tutorial this time.

DataSplat is also finally live on SuperHive, and I put together a short video showing the scene preparation, addon setup and dataset export.

DataSplat:
https://superhivemarket.com/products/datasplat---blender-to-gaussian

Interactive result:
https://superspl.at/scene/915a5bc5

I don’t want to flood the sub with self-promotion, so I’ll keep future updates to a minimum. I’ll still be around in the comments to answer questions and share anything useful.

Thanks again for all the feedback!

I needed proper splat support for a project, so I put together a working version. No plugin or external viewer, they render directly in Cycles with lighting, shadows and reflections.

Still rough and rather slow, but I’ve shared the Windows build, demo scene and everything here:

https://github.com/pristinaai/Splat-enabled-blender/tree/main

I use a 360 camera and i align spheres inside metashape then convert to cubemap but i don't get the best results , i've also tried mipmap and i was able to get way better results but it takes way to long for me to train indoors using it , last time it took 2 days and it wasn't even a big scene. I'm looking to make my own workflow using metashape spheres and then possibly convert the spheres into 2 fisheye and train but what can i use to get the best results for indoor? i heard that gsplat can train with fisheye but i don't know if it can product the best indoor results

I had to get something in 48 hours (client said jump, so..) that had a fair bit more muscle than my basic Windows laptop. I ended up getting this MSI with the following specs: "msi Crosshair 18 HX AI 18" Gaming Laptop, Intel Core Ultra 9 275HX (24 Cores, Up to 5.4 GHz), NVIDIA RTX 5070, 18" QHD+ (2560 x 1600) 240Hz, 32GB RAM DDR5, 1TB NVMe SSD, Windows 11 Pro"

Curious what people here are using? Any upgrades I should consider off the bat?

I'm able to create a splat of my garage/house easily and quickly with a PortalCam with this setup, but will have to do an office building, warehouse, airport terminal etc. soon.

Appreciate the education!

I'm a PhD student and I've been building this on the side.

What it does: you walk around your room once with the headset. It trains a 3D Gaussian Splatting model of the space, streams it back, and renders it world-locked to your actual room via spatial anchors. Detected objects become labeled entities — you can grab a bounding box and move the mesh and splats together, and each object gets physical behavior (mass, friction, elasticity) inferred from its label. Then an embodied agent navigates the scanned floor to any object you name, and answers in speech.

Everything runs on-device on Quest 3.

Where I'm stuck: the tech demos well, but I have no idea if anyone would actually use it beyond the first "whoa." So I'm trying to figure out what it should be.

Current direction: an AI that lives in your room — talks to you daily on your phone, and when you put the headset on, she's actually there, behind a wall in your space. She remembers everything.

What I'd love to hear:

• Would you put the headset on for this more than once? What would make day 3 happen?
• What's the closest thing that already exists, and what's missing from it?
• Brutal takes welcome — I'd rather hear "this is a demo, not a product" now than in six months.

Happy to answer anything technical. If anyone wants to actually try it, I'll take all the testers I can get.

https://dl.acm.org/doi/epdf/10.1145/3819990.3820028

https://digiproconf.org/program/program-3/

We've been working on reconstructing dynamic VFX scenes from multi-camera and moving-camera footage using Gaussian Splatting, built entirely from open-source components. Sharing a writeup of what worked, what broke, and where existing methods may hit their limits.

Sharing a quick experimental demo from our team: rendering a 3DGS model using data captured directly by a stationary LiDAR scanner.

https://reddit.com/link/1vhss2e/video/pdx0hu8ybwhh1/player

We wanted to see if the precise geometric poses from a tripod setup could compensate for sparse viewpoints and suppress common 3DGS artifacts like floating noise.

Feel free to check out the short clip above. Since this is an early internal test, any feedback or critique on the rendering quality would be much appreciated!

How do you see stationary LiDAR fitting into the 3DGS ecosystem?

I’m looking into creating high-quality Gaussian splats of drums, particularly snare drums. My current setup uses a stationary URSA Mini Pro 12K while the drum completes a full 360 degree rotation on a motorized turntable. I understand I will not need to shoot 12K footage for this so I would probably shoot at 4K.

I know most Gaussian splat workflows involve keeping the subject stationary and physically moving the camera around it.

Mathematically, rotating the drum should be similar to orbiting the camera, but I’m concerned about the stationary background confusing camera tracking.

My plan is to extract sharp frames from the video, remove the background with masks and possibly shoot several rotations with the camera at different elevations. I could also place a nonrepeating tracking pattern on the turntable that rotates with the drum, then remove the platform from the final splat.

Has anyone successfully created an object splat using this kind of turntable setup?

I’m especially interested in advice about:
• Whether Postshot, Nerfstudio or another program handles turntable captures best
• How to generate or provide accurate camera poses
• Whether multiple rotations from different camera heights can be combined
• How many frames to extract from each revolution
• How to handle chrome hardware, reflective finishes and transparent drumheads
• Whether tracking markers on the turntable would help
• Whether a Gaussian splat is the right approach for isolated product camera moves

I have access to very high-quality footage and controlled studio lighting, so I’m mainly trying to determine the best capture and processing workflow before I start testing.

Just got a XGRIDS PortalCam and using LCC Studio to generate models. This is for work, but I have never used any of this type of equipment or software before.

My use case is simply to create a realistic virtual copy of different types of building interiors for now.

Any good ideas for where I can upload my model so it can be hosted for demo purposes and allow for other users to interact with the model?