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