DreamFusion
Text-to-3D using 2D Diffusion
VS
NVIDIA GET3D
Generates high-quality 3D textured shapes from images.
Detailed comparison
Criteria
DreamFusion
NVIDIA GET3D
Pricing
Free
Free
Plans & pricing
Free: Free
Free: Free
Free trial
No
No
Audience
b2c
b2b
Platforms
Web
—
API
No
No
Open Source
Proprietary
Proprietary
Categories
Creative, AI 3D Model Generator
Creative, AI 3D Model Generator
Popularity
Very High
Very High
Description
DreamFusion generates high-quality 3D objects from text prompts by distilling the prior from a 2D diffusion model into a 3D neural radiance field (NeR...
NVIDIA GET3D is a generative model developed by NVIDIA Research. It is designed to synthesize high-quality 3D textured shapes by learning from 2D imag...
Pricing
DreamFusion
Free
NVIDIA GET3D
Free
Plans & pricing
DreamFusion
Free: Free
NVIDIA GET3D
Free: Free
Free trial
DreamFusion
No
NVIDIA GET3D
No
Audience
DreamFusion
b2c
NVIDIA GET3D
b2b
Platforms
DreamFusion
Web
NVIDIA GET3D
—
API
DreamFusion
No
NVIDIA GET3D
No
Open Source
DreamFusion
Proprietary
NVIDIA GET3D
Proprietary
Categories
DreamFusion
Creative, AI 3D Model Generator
NVIDIA GET3D
Creative, AI 3D Model Generator
Popularity
DreamFusion
Very High
NVIDIA GET3D
Very High
Description
DreamFusion
DreamFusion generates high-quality 3D objects from text prompts by distilling the prior from a 2D diffusion model into a 3D neural radiance field (NeR...
NVIDIA GET3D
NVIDIA GET3D is a generative model developed by NVIDIA Research. It is designed to synthesize high-quality 3D textured shapes by learning from 2D imag...
Features
DreamFusion
Generates 3D objects from text prompts
Utilizes 2D diffusion models
Employs Score Distillation Sampling (SDS) loss function
Optimizes Neural Radiance Fields (NeRF)
NVIDIA GET3D
High-resolution 3D shape synthesis using Deep Marching Tetrahedra.
Extraction of triangular 3D models, materials, and lighting from images.
Efficient geometry-aware 3D Generative Adversarial Networks (EG3D).
Predictive lighting and material learning with a hybrid differentiable renderer (DIB-R++).
Modular primitives for high-performance differentiable rendering (Nvdiffrast).
Key differentiators
DreamFusion
- 3D objects from text prompts
- 2D diffusion prior to 3D NeRF
NVIDIA GET3D
- High-quality 3D textured shapes from 2D images
- Advanced 3D GANs (EG3D) for efficient geometry
- Predictive lighting & material learning
Other comparisons
FAQ: DreamFusion vs NVIDIA GET3D
DreamFusion: Text-to-3D using 2D Diffusion. NVIDIA GET3D: Generates high-quality 3D textured shapes from images.. Both tools take different approaches to address similar needs.
Both offer a free or freemium plan. DreamFusion is free and NVIDIA GET3D is free.
The best choice between DreamFusion and NVIDIA GET3D depends on your specific needs. Compare their features, pricing, and target audience on this page to find the tool that best fits your use case.
DreamFusion is primarily designed for individuals, while NVIDIA GET3D is built for individuals.
DreamFusion offers: Generates 3D objects from text prompts, Utilizes 2D diffusion models, Employs Score Distillation Sampling (SDS) loss function, Optimizes Neural Radiance Fields (NeRF). NVIDIA GET3D offers: High-resolution 3D shape synthesis using Deep Marching Tetrahedra., Extraction of triangular 3D models, materials, and lighting from images., Efficient geometry-aware 3D Generative Adversarial Networks (EG3D)., Predictive lighting and material learning with a hybrid differentiable renderer (DIB-R++)..
Based on our data, NVIDIA GET3D currently enjoys greater popularity. However, popularity isn't the only factor — compare features to find the right tool for your needs.