▲ 219 r/GaussianSplatting+1 crossposts

I am building a web application to transform images into Gaussian Splats

I’ve been playing with orbit-style videos from video models (lately Minimax H3 in ComfyUI) and kept thinking they’d make great input for Gaussian Splatting. The catch was that the usual pipeline means installing COLMAP, a trainer, CUDA and so on. That’s a lot of friction just to try one idea.

So I built Gausify Orbit: https://orbit.gausify.com/

You drop in your video and the whole thing runs locally in your browser on WebGPU:

  • Pulls frames from the video
  • Optional background removal with RMBG-1.4 (BRIA), running through ONNX Runtime Web
  • Camera poses from a small structure-from-motion step
  • Trains the splat with Brush
  • Preview the result and export it as PLY or SOG

No Python, no CUDA, no account. Your video never leaves your machine. The models download once, and after that the app works offline too. If you want to show someone a result, you can share a temporary private link that opens in a viewer (it even supports WebXR).

Since it all runs on your GPU, how fast it goes depends on your hardware. You also need a browser with WebGPU (recent Chrome or Edge work best). AI videos aren’t perfectly 3D-consistent either, so some generations reconstruct much better than others. Slow, steady orbits around one centered subject give the best results.

Tip for better results: I’ve been using this LoRA by pablodawson to get cleaner orbits out of Minimax H3: https://huggingface.co/pablodawson/MiniMax-H3-360-Orbit-LoRA

It makes the camera move in a much smoother, more consistent 360° orbit around the subject. That helps a lot here, because the reconstruction step relies on the camera following a predictable path. In my tests, videos made with it got better camera poses and noticeably sharper splats than plain prompting. Highly recommend it if you’re generating orbit videos for this.

ComfyUI Workflow: https://github.com/obraia/ComfyUI/blob/main/workflows/minimax-h3-gausify-orbit.json

u/obraiadev — 4 days ago
▲ 84 r/comfyui+1 crossposts

My first attempts with MiniMax-H3

https://reddit.com/link/1ve314z/video/c0hmw55s53hh1/player

I'm running it on an RTX 4070 Ti Super + 128 GB DDR5.

https://preview.redd.it/edisqx6m53hh1.png?width=2011&format=png&auto=webp&s=c39caa8fe81cbac24e5c88180b8fa168ae1bd04d

I ran the first video right after starting ComfyUI, and it took 429.94 seconds at a resolution of 864 x 480; the second one took 18 minutes and consumed 80 GB of RAM.

Prompts:

Ultra-realistic cinematic military aviation sequence. A modern multirole fighter jet performs an extremely low high-speed pass over a pristine tropical beach at golden hour. Crystal-clear turquoise water, white sand, dramatic coastline, realistic atmospheric haze, physically accurate lighting, photorealistic textures, subtle film grain, IMAX-quality visuals, ultra-high dynamic range.

SHOT 1:
A wide aerial establishing shot reveals the peaceful coastline from above. The distant fighter jet rapidly approaches from the horizon at extremely low altitude. The camera slowly tracks sideways while ocean waves gently move under warm sunset light.

SHOT 2:
The jet roars directly above the shoreline at nearly supersonic speed. The powerful jet wash violently disturbs the ocean surface, creating expanding ripples, mist, spray, and realistic pressure waves across the shallow water. Sand is blown into the air while palm trees bend naturally from the blast. The camera shakes subtly from the immense force.

SHOT 3:
An ultra-slow-motion side tracking shot follows the aircraft only meters above the water. Heat distortion shimmers behind the engines, sunlight reflects off the fuselage, and the water erupts beneath the passing aircraft with highly detailed turbulence and spray.

SHOT 4:
A drone-style chase shot follows behind the fighter as it accelerates over the coastline before sharply climbing into the sky. Long vapor trails briefly form over the wings while the disturbed ocean slowly settles below.

Camera:
ARRI Alexa 65, IMAX anamorphic lenses, cinematic motion blur, shallow depth of field where appropriate, stabilized aerial tracking, realistic exposure, natural color grading.

Audio:
Thunderous military jet engine roar, deep sub-bass vibrations, realistic wind shear, crashing waves, airborne sand, distant seagulls fading under the overwhelming engine noise, subtle camera vibration, immersive cinematic surround sound.



Ultra-realistic cinematic first-person POV sequence set in the American Wild West during the late 1800s. The viewer experiences everything through the eyes of a lone gunslinger standing in the middle of a dusty frontier town. Wooden buildings, swinging saloon doors, horses tied outside, tumbleweeds rolling through the empty street, intense midday sunlight, realistic dust particles floating in the air, authentic period details.

SHOT 1:
The camera slowly walks into the center of the deserted street. The viewer's gloved hands hang naturally near a weathered Colt Single Action Army revolver in a worn leather holster. Across the street, another gunslinger waits silently, his hand hovering near his revolver.

SHOT 2:
Extreme tension builds. The camera breathes subtly with realistic body movement. Wind whistles through the empty town as dust drifts across the street. Tiny movements from the opponent hint that the duel is about to begin.

SHOT 3:
The opponent reaches for his revolver. Instantly, the viewer draws the Colt in one smooth motion. The revolver fills the foreground in stunning detail while the camera naturally follows the movement. A realistic muzzle flash erupts, thick smoke expands, and the weapon recoils with authentic mechanical motion.

SHOT 4:
Time briefly slows. The smoke drifts through warm sunlight while spent dust lifts from the ground. The opposing gunslinger reacts naturally and falls out of frame. The viewer slowly lowers the revolver while the town returns to silence.

Camera:
True first-person body-mounted perspective, natural head movement, realistic breathing motion, subtle handheld stabilization, cinematic depth of field, ARRI Alexa 65 image characteristics, anamorphic lenses, high dynamic range.

Lighting:
Harsh midday desert sun, warm natural tones, physically accurate shadows, volumetric dust illuminated by sunlight.

Audio:
Leather creaking, boots on dirt, distant horse sounds, wooden signs gently knocking in the wind, slow breathing, revolver hammer cocking, authentic Colt gunshot, realistic echo across the town, lingering silence after the duel.

Style:
Photorealistic, historically authentic, immersive POV, Hollywood western cinematography, physically accurate smoke, realistic weapon mechanics, ultra-detailed textures, 8K, no HUD, no game interface, no CGI look.
Style:
Photorealistic, physically accurate, documentary-level realism, Hollywood military cinematography, no CGI look, no cartoon style, no exaggerated physics, ultra-detailed, 8K.
u/obraiadev — 2 months ago

Gausify - Trying to create a platform and player focused on Gaussian Splatting for VR/AR

I am a developer and recently bought a Quest 3; since then, I’ve been creating projects to use with it. This platform generates volumetric images and videos that can be viewed in mixed or virtual reality.

https://preview.redd.it/5keuwldh6aeh1.png?width=654&format=png&auto=webp&s=b276a9a29627b9acb2b4cfed43c660abf898fc77

One of the challenges I'm currently facing is optimizing the player to achieve higher frame rates for smoother playback.

u/obraiadev — 3 months ago
▲ 14 r/GaussianSplatting+1 crossposts

Gausify - Free image/video to Gaussian Splats using WebGPU

I've been working on gausify.com, a browser-based platform for generating Gaussian Splats from images and videos.

https://preview.redd.it/21129rvr3vdh1.png?width=665&format=png&auto=webp&s=187857f651840d9f7fce9551bf465d2b79822b2e

https://reddit.com/link/1uzgz1p/video/e0y1gpq1tvdh1/player

The main idea is to make Gaussian Splat creation as simple as possible while keeping everything fully local in your browser using WebGPU.

Right now, the generation pipeline uses Apple's ML-SHARP model converted to ONNX, so the entire process happens on your own device.

Some features I've added so far:

  • Generate Gaussian Splats from images and videos.
  • Everything runs locally in the browser.
  • Uses WebGPU for acceleration.
  • Chrome's File System Access API lets you save and reopen projects without the usual browser download limitations.
  • Support for the compressed .SOG format, which produces files around 10–20x smaller than traditional .ply files (but this comes at the cost of generation time).
  • A decimation option that reduces the number of splats, making playback much smoother on lower-end devices while keeping good visual quality (this also comes with a small cost in terms of generation time).

Generation time depends on your hardware and the optimization settings you choose. As a reference, the current performance shown in my testing is on an RTX 4070 Ti SUPER.

My long-term goal is building a player that's optimized for mobile devices and AR/VR headsets like the Quest 3, making it easier to view and share Gaussian Splats anywhere.

Built with and inspired by:

reddit.com
u/obraiadev — 3 months ago