Project Title

stable-dreamfusion — A Python Implementation for Text-to-3D and Image-to-3D Generation with NeRF and Diffusion Models

Overview

Stable-dreamfusion is an open-source Python project that enables text-to-3D and image-to-3D generation using NeRF and diffusion models. It leverages the power of Stable Diffusion for text-to-2D models, offering a unique approach to 3D content creation. This project stands out for its integration of advanced AI techniques to facilitate the creation of 3D models from textual or visual inputs.

Key Features

Integration of Stable Diffusion for text-to-2D model generation.
Support for text-to-3D and image-to-3D conversion.
Utilization of NeRF for 3D rendering.
Implementation of diffusion models for generating 3D content.
Colab notebooks for easy setup and experimentation.

Use Cases

3D artists and designers can use stable-dreamfusion to create 3D models from textual descriptions or images, streamlining the design process.
Researchers in the field of AI and computer vision can leverage this project for experiments in 3D generation and neural rendering.
Content creators can utilize this tool to generate 3D assets for virtual reality, gaming, and other immersive experiences.

Advantages

Offers a cutting-edge approach to 3D content creation by combining text-to-2D and 3D generation.
Provides a flexible platform for experimenting with different 3D generation techniques.
Facilitates rapid prototyping and iteration in 3D modeling through its integration with Colab notebooks.

Limitations / Considerations

The project is work-in-progress and may not match the quality of results from the original paper.
Some prompts may still fail to generate satisfactory results.
The training process can be time-consuming due to the need for loss propagation back from the VAE's encoder part.

DreamFusion: The original implementation of the DreamFusion model, which stable-dreamfusion is based on. It differs in that it uses the Imagen model, which is not publicly available.
Stable Diffusion: A text-to-2D model that stable-dreamfusion uses as a replacement for Imagen. It operates in a latent space, which introduces additional training time.
Instant-NGP: A multi-resolution grid encoder used in stable-dreamfusion for implementing the NeRF backbone, enabling faster rendering.

Basic Information

GitHub: https://github.com/ashawkey/stable-dreamfusion
Stars: 8,731
License: Unknown
Last Commit: 2025-10-01

📊 Project Information

Project Name: stable-dreamfusion
GitHub URL: https://github.com/ashawkey/stable-dreamfusion
Programming Language: Python
⭐ Stars: 8,731
🍴 Forks: 765
📅 Created: 2022-10-06
🔄 Last Updated: 2025-10-01

🏷️ Project Topics

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📚 Documentation

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stable-dreamfusion

Project Description