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NVIDIA GET3D

A Generative Model of High Quality 3D Textured Shapes Learned from Images.

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Overview

GET3D (Generate Explicit Textured 3D) is a research project and AI model developed by NVIDIA. It is trained on 2D images to generate high-fidelity 3D shapes with complex topology, detailed geometry, and high-quality textures. The generated models are directly usable in standard 3D rendering engines and applications, aiming to democratize 3D content creation for virtual worlds.

✨ Key Features

  • Generates high-quality 3D textured meshes
  • Learns from 2D image collections
  • Creates models with complex topology and rich geometric details
  • Outputs meshes directly usable in 3D applications
  • Can generate ~20 shapes per second on a single GPU

🎯 Key Differentiators

  • Generates explicit, textured meshes, not just point clouds or NeRFs
  • High-speed generation
  • Integration into NVIDIA's ecosystem (Omniverse)

Unique Value: A significant leap in AI-powered 3D content creation, capable of generating high-quality, textured 3D models at scale directly from 2D images.

🎯 Use Cases (4)

Populating virtual worlds for gaming and metaverse applications. Asset creation for robotics simulations Architectural visualization Research in 3D generative models

✅ Best For

  • Generating diverse 3D objects like cars, chairs, and animals from 2D image datasets.

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Direct commercial use by individual creators (it's a research model, not a product)
  • Text-to-3D generation (it's primarily image-based)

🏆 Alternatives

Google DreamFusion OpenAI Shap-E

Unlike models that produce implicit representations (NeRFs) or untextured point clouds, GET3D generates explicit, textured meshes that are immediately compatible with standard graphics pipelines.

💻 Platforms

Code library (Python)

✅ Offline Mode Available

🔌 Integrations

NVIDIA Omniverse

💰 Pricing

Contact for pricing
Free Tier Available

Free tier: The code and model are available for research purposes on GitHub.

Visit NVIDIA GET3D Website →