Abstract
A few days ago I posted “ Gausify Orbit - I am building a web application to transform images into Gaussian Splats ”, and it was removed because the project wasn’t open source yet. It’s now released under the MIT license , so here it is again, with a lot of updates. What it does You give it a video that circles around a subject. That can be a clip from a video model (I mostly make mine in ComfyUI using Minimax H3 + 360 LoRA by pablodawson), a phone video, or a folder of images. You get back a 3D Gaussian Splat you can view, export or share. Running in the browser The web version runs the whole pipeline locally on WebGPU . Nothing to install, no Python, no CUDA, and your video never leaves your machine. After the first visit it even works offline. Here’s what happens in the tab: Frames: the browser decodes the video and keeps the sharpest frame in each window, spread evenly around the orbit. If the subject starts “melting” near the end (classic AI video problem), you can trim the range. Cutout (optional): SAM 2.1 on WebGPU. Draw a box or click a few points on one frame and it tracks the subject through the whole clip. Other options: RMBG-1.4 (opt-in, non-commercial license) and a chroma key with despill for green/blue screens. Masked training uses a random background, so you don’t get ghost silhouettes around the subject. Camera poses: a structure-from-motion I wrote for the browser, so no COLMAP needed: AKAZE features, matching in a WebGPU compute shader, and incremental reconstruction with bundle adjustment. Training: Brush compiled to WASM + WebGPU, with live previews in the 3D viewer while it trains. Export: .ply or compressed SOG , with optional merging of similar splats and SH trimming. Files typically end up 5–15× smaller. Share: an optional private, expiring link with a QR code. It opens in a viewer that works on phones and in VR/AR (WebXR). You need desktop Chrome or Edge with WebGPU. Speed depends on your GPU: in-browser training runs at roughly a third of native Brush speed, which is still very usable. New since the first post Refine angles the video never saw. The app renders the splat along a new camera path (from below, from above, a 360° turn at another height…), restores that clip with a video model in your ComfyUI, and fine-tunes the splat on the restored frames. This is the part I’m most excited about. ComfyUI integration with custom workflows: load your workflow exported with Export (API) , pick the input/output nodes, and expose fields like prompt, seed or LoRA strength to edit from the app. Project import/export: save everything as a .gorbit file, even mid-job, and reopen it later in the browser or the desktop app. Run each stage on its own: e.g., retrain with new settings without recomputing poses. You can also reject bad frames, and frames without a camera get a pose inferred from their neighbors. SAM 2.1 for subject isolation (described above). Image sequences or folders as input, not just video. Regarding Gaussian Splat refinement, I am running tests using LTX 2.5 + Decompression LoRA to fill in non-visible areas; while the results are good in some cases, using a LoRA specifically tailored to this scenario would certainly yield better results. The ComfyUI workflow for this refinement which can be integrated with Gausify Orbit , can be found here . Example of a trained Gaussian : https://orbit.gausify.com/s/5xAWaNiiO8ax App : https://orbit.gausify.com Repo : https://github.com/obraia/gausify-orbit submitted by /u/obraiadev to r/StableDiffusion [link] [comments]