UniForge3D Studio, a local web app built around UniForge3D, the new open-source model from Peking University, HKUST and Math Magic. You drop in two or more photos of an object from any angles, no camera positions needed, and get back a textured GLB. The model keeps what the photos show and generates the hidden sides in the same 3D space, so the back stays true to the real object. What's in the box: One command: docker run --gpus all -p 8091:8091 camenduru/uniforge3d-studio, then open localhost:8091 in your browser Fully offline: every model is already inside the image, so there's no Hugging Face login and nothing gets downloaded or sent anywhere while it runs Simple web UI: upload photos (PNG, JPG or WebP), pick a seed, hit Generate and check the result in the built-in 3D viewer. Background removal runs automatically Optimize for games: meshoptimizer's gltfpack is built in, so you can cut the triangle count (to 25% by default), compress the mesh and convert textures to WebP Low-VRAM mode: moves some stages to the CPU so a run fits on a 24 GB card The catch is size. The image is a 36 GB download (around 55 GB unpacked), it needs an NVIDIA GPU with about 18 GB of free VRAM, and one model takes roughly 10 minutes on an RTX 3090, coming out near 50 MB before optimization. It's a community wrapper by camenduru rather than the authors' release, and some bundled weights, like the RMBG-2.0 background remover, are non-commercial, so commercial use is still unclear. No big GPU? There's a community demo on Hugging Face. github: https://github.com/camenduru/UniForge3D   submitted by   /u/SuspiciousHunter1359   to   r/TopologyAI [link]   [comments]