Threestudio is a 3D generative AI framework designed to create three-dimensional assets from text prompts and images. It provides specialized pipelines for text-to-3D generation and image-to-3D reconstruction, utilizing a neural radiance field trainer to produce geometry and textures. The framework is distinguished by its support for hybrid geometry backends, including signed distance functions, tetrahedra grids, and volume grids. It employs score distillation sampling to guide the generation process and features a modular plugin system for loading custom modules and nodes. The system covers
Shap-E is a generative 3D modeling system that creates three-dimensional digital assets from natural language descriptions or two-dimensional images. It functions as a generative model capable of producing three-dimensional implicit functions and assets. The project includes a 3D latent encoder that converts trimeshes and 3D models into latent representations using point clouds and multiview renders. It utilizes an image-to-3D generator to produce assets from synthetic view images and a text-to-3D generator to build shapes from text prompts. The system implements a pipeline involving latent
TRELLIS is a 3D generative AI model and latent diffusion framework designed to transform natural language descriptions or reference images into textured 3D assets. It operates as a text-to-3D asset generator that utilizes structured latent representations to produce high-quality 3D meshes, Gaussians, and Radiance Fields. The system functions as a multi-format 3D decoder, converting internal representations into standard exchange formats such as GLB and PLY. It also serves as a 3D asset editing tool, enabling the modification of specific regions of generated objects through targeted text or im
Modly is a local AI 3D model generator that converts two-dimensional images into three-dimensional meshes. It is a privacy-focused tool that processes data directly on the host graphics card using GPU-accelerated inference. The system serves as an extensible AI model framework, allowing the integration of external model extensions and runtime files from remote repositories. It utilizes a manifest-driven plugin architecture to add new generation methods by loading metadata and files from external version control systems. The toolset includes a command-line interface for triggering generation
This is the implementation of NeurIPS 2020 paper "Generative 3D Part Assembly via Dynamic Graph Learning" created by Jialei Huang , Guanqi Zhan , Qingnan Fan , Kaichun Mo , Lin Shao , Baoquan Chen , Leonidas Guibas and Hao Dong .
The main features of hyperplane-lab/generative-3d-part-assembly are: Generative 3D Modeling.
Open-source alternatives to hyperplane-lab/generative-3d-part-assembly include: openai/shap-e — Shap-E is a generative 3D modeling system that creates three-dimensional digital assets from natural language… threestudio-project/threestudio — Threestudio is a 3D generative AI framework designed to create three-dimensional assets from text prompts and images.… nv-tlabs/get3d — GET3D is a generative 3D mesh model and rendering framework designed to synthesize high-quality textured shapes and… lightningpixel/modly — Modly is a local AI 3D model generator that converts two-dimensional images into three-dimensional meshes. It is a… microsoft/trellis — TRELLIS is a 3D generative AI model and latent diffusion framework designed to transform natural language descriptions… coplaydev/unity-mcp — Unity MCP is a plugin that connects the Unity Editor to AI assistants through the Model Context Protocol, enabling…