VAST-AI-Research/TripoSG

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1755 stars · 196 forks observed · 2026-08-28

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

TripoSG is an open-source image-to-3D generation foundation model that produces high-fidelity 3D meshes from single images using large-scale rectified flow transformers and an SDF-based VAE. It ships as a Python library with inference code, pretrained 1.5B parameter checkpoints on Hugging Face, and interactive demos.

Use cases

• generate a 3d mesh from a single image
• convert photos into 3d models
• create 3d assets from sketches or cartoons
• reconstruct 3d shapes from images for games
• prototype 3d shapes from scribbles with a text prompt
• run image-to-3d generation locally with a gpu

When to choose

• you need high-fidelity 3d meshes from single images
• you want an open-source, MIT-licensed image-to-3d model you can self-host
• your inputs span photorealistic images, cartoons, and sketches
• you want to build on a state-of-the-art 3d generative foundation model

When to avoid

• you need textured, production-ready assets with materials rather than geometry
• you have no gpu available for inference
• you need real-time 3d generation in a production pipeline
• you want a polished end-user application rather than a model and inference code

Facets

library · maturity active

machine-learning deep-learning image-processing graphics simulation artificial-intelligence deep-learning computer-vision graphics machine-learning python cross-platform image-to-3d 3d-generation rectified-flow mesh-generation generative-ai sdf diffusion-models gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="VAST-AI-Research/TripoSG")