GET3D (Nvidia) is an AI tool that generates textured 3D meshes directly from 2D image collections. Developed by Nvidia, it produces models with complex topology and high-quality geometry, outputting assets that integrate directly with standard 3D rendering engines. The tool separates geometry controls from texture latent codes, which allows users to alter surface patterns without modifying the underlying 3D shape or to adapt a single texture across various geometric models. It also supports unsupervised material and lighting generation, smooth latent space shape interpolation, and text-guided 3D generation. GET3D is designed for game developers, 3D artists, metaverse architects, and industrial designers who need to rapidly prototype and populate environments with diverse 3D objects, such as vehicles, furniture, or buildings. By learning entirely from image sets, it reduces the manual labor required to craft detailed textured meshes from scratch. The pricing model for GET3D is not specified.
Problem: Game developers often need a massive variety of high-quality 3D assets, like cars and furniture, which are time-consuming and expensive to model manually.
Solution: GET3D allows developers to generate diverse, high-fidelity textured meshes that can be directly imported into standard rendering engines.
Example: A developer generates 50 unique car models for a racing game background in minutes instead of weeks.
Problem: Creating large-scale metaverse environments requires a vast quantity of unique assets to avoid repetitive visuals.
Solution: The tool's ability to generate shapes with arbitrary topology and rich geometric details makes it ideal for scaling 3D content creation.
Example: Building a virtual city populated with unique buildings and street props generated from image datasets.
Problem: Designers need to iterate quickly on different textures and shapes for products like footwear or furniture.
Solution: GET3D features disentangled geometry and texture latent codes, allowing designers to swap textures on a specific shape or vice versa.
Example: A shoe designer exploring hundreds of color and material variations on a single 3D sneaker model.
Problem: Users without 3D modeling expertise often struggle to create custom 3D assets for creative projects.
Solution: Using text-guided shape generation via CLIP, users can generate complex 3D assets simply by providing a written description.
Example: A content creator typing "medieval stone chair" to instantly generate a 3D model for a social media post.
Target audience: Best for: Game developers, 3D artists, Metaverse architects, and Industrial designers
Pricing: Unknown · Categories: 3D
Tags: 3D
GET3D is a generative AI model developed by Nvidia that synthesizes 3D textured meshes from 2D image collections. It creates high-fidelity 3D shapes with arbitrary topology, offering direct compatibility with standard 3D rendering pipelines and software.
The model generates textured 3D meshes with disentangled geometry and texture controls. It supports text-guided 3D generation, unsupervised material and lighting generation, and smooth shape interpolation in latent space, enabling rapid asset production for game design and virtual worlds.
GET3D is built for game developers, 3D artists, metaverse creators, and industrial designers. It assists professionals who require large collections of varied 3D assets, such as vehicles or furniture, without modeling each object manually.
To install and run GET3D, follow the instructions and dependency guidelines outlined in the project repository at https://nv-tlabs.github.io/GET3D/.
Yes, GET3D features disentangled geometry and texture latent codes. This separation allows users to swap materials and textures across different geometric shapes or preserve an existing shape while generating new surface appearances.