openai/point-e
point-e
Point cloud diffusion for 3D model synthesis
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OpenAI
openai • ai-lab
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798
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Created
Dec 6, 2022
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README Summary
Point-E is a system for generating 3D point clouds from text prompts using diffusion models. It first generates a single synthetic view from text, then produces a 3D point cloud conditioned on that image. The approach is faster than optimization-based methods while producing diverse 3D shapes.
AI Dev Skills
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Diffusion ModelsText-to-3D GenerationPoint Cloud ProcessingMultimodal Deep Learning3D Computer VisionGenerative AIText-to-Image Generation3D Mesh ProcessingNeural Network Architecture Design
Tags
Diffusion ModelsText-to-3D GenerationPoint Cloud ProcessingMultimodal Deep Learning3D Computer VisionGenerative AIText-to-Image Generation3D Mesh ProcessingNeural Network Architecture DesignCloudRapid 3D PrototypingMulti-view SynthesisDigital Twin CreationDigital ArtAnimationVR/AR3D Printing3D3D Content GenerationProduct DesignGamingMultimodal AIArchitectureConditional GenerationImage-to-3D Model GenerationImageText-to-3DImage-to-3D GenerationTextSelf-hostedEntertainmentText-to-3D Model GenerationGame Asset CreationPython
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Updated 1 years ago
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research- Quality
- medium
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- research
Categories
Other AI / MLPrimaryGenerative MediaMultimodal AIComputer VisionFoundation Models
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Languages
Python100.0%
Timeline
- Project created
- Dec 6, 2022
- Forked
- Mar 14, 2026
- Your last push
- 1 years ago
- Upstream last push
- 1 years ago
- Tracked since
- Jul 4, 2024
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