V3D: Video Diffusion Models are Effective 3D Generators
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View abstract on PubMed
Summary
This summary is machine-generated.V3D enhances 3D generation by using video diffusion models for detailed object creation. This approach generates high-quality 3D models and novel views efficiently from single images.
Area Of Science
- Computer Vision
- 3D Computer Graphics
- Artificial Intelligence
Background
- Automatic 3D generation is gaining traction, but current methods often sacrifice detail for speed.
- Limited model capacity and 3D data hinder the creation of highly detailed objects.
Purpose Of The Study
- To leverage pre-trained video diffusion models for improved 3D generation.
- To introduce a geometrical consistency prior for multi-view consistent 3D generation.
- To enable high-quality 3D object and scene generation from limited input.
Main Methods
- V3D fine-tunes state-of-the-art video diffusion models for 3D generation.
- A geometrical consistency prior is integrated to ensure multi-view consistency.
- The model generates $360^{\circ }$ orbit frames from a single image, enabling reconstruction of meshes or 3D Gaussians.
Main Results
- High-quality 3D meshes and 3D Gaussians are generated within 3 minutes.
- The method achieves superior generation quality and multi-view consistency compared to existing approaches.
- Scene-level novel view synthesis is enabled with precise camera path control.
Conclusions
- V3D effectively utilizes video diffusion models for advanced 3D content creation.
- The proposed approach significantly improves detail and consistency in 3D generation.
- V3D offers a fast and versatile solution for generating 3D objects and scenes.
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