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DreamFusion

Categories: Text & Writing, Image Generation, Research  |  Pricing: Freemium  |  Official Website ↗

DreamFusion: Text-to-3D using 2D Diffusion, 2022.

DreamFusion: Text-to-3D using 2D Diffusion, 2022.

Key Features

• Text-to-3D generation
• Neural Radiance Field (NeRF) optimization
• Score Distillation Sampling (SDS)
• 2D diffusion model as a prior
• Relightable 3D object output
• Mesh export via marching cubes
• High-quality normals and surface geometry

Pros

• Generates relightable 3D objects from text prompts
• Leverages pretrained 2D diffusion models (e.g., Imagen)
• Requires no 3D training data
• Exports 3D models to meshes for external use
• Produces high-fidelity appearance, depth, and normals

Cons

• Optimization process can be computationally intensive
• Relies on a DeepDream-like procedure, potentially slow
• Quality can vary based on prompt complexity
• Limited to objects and scenes representable by NeRFs

Use Cases

• Generating custom 3D models for games or simulations
• Creating virtual objects for AR/VR applications
• Prototyping 3D designs from text descriptions
• Populating virtual scenes with unique assets
• Research and development in generative AI for 3D

Best For

• 3D artists and designers
• Researchers in AI and computer graphics
• Game developers
• Content creators needing 3D assets

Platforms: web

Watch demo on YouTube ↗

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