Stable-X/Stable3DGen

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1274 stars · 92 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Stable3DGen is a modular Python framework for generating 3D assets from images, adapted from Microsoft's TRELLIS with NVIDIA library dependencies removed for commercial use. It implements Hi3DGen, a high-fidelity 3D geometry generation approach using normal bridging, and includes a local Gradio-style demo app.

Use cases

• generate 3d models from a single image
• create 3d meshes from photos for games
• commercial 3d asset generation without nvidia-only dependencies
• high-fidelity geometry generation from images
• run a local demo to turn images into 3d assets
• research on image-to-3d generation pipelines

When to choose

• you need MIT-licensed, commercially usable image-to-3d generation
• you want a modular framework built on TRELLIS without kaolin/nvdiffrast dependencies
• you have a CUDA GPU and want local 3D asset generation

When to avoid

• you need a production-ready, polished tool (project is marked WIP)
• you have no GPU or CUDA environment
• you need text-to-3d rather than image-to-3d generation

Facets

framework · maturity active

machine-learning deep-learning image-processing graphics simulation artificial-intelligence deep-learning graphics computer-vision python cross-platform 3d-generation image-to-3d 3d-mesh generative-ai trellis hi3dgen normal-bridging commercial-friendly gpu linux

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markdown · JSON · MCP: product_card(name="Stable-X/Stable3DGen")