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Description
3DFY.ai has developed an innovative framework that addresses the challenge of converting 2D images into 3D models across various sectors using artificial intelligence, allowing for the creation of high-quality 3D representations from just a handful of existing images. The task of generating detailed 3D models from minimal images is particularly difficult due to the absence of crucial information and issues such as self-occlusions. At 3DFY.ai, we tackle these challenges by training our AI models on specialized datasets for different categories, which empowers them to fill in missing details in a realistic way. Our proprietary technology provides a premium service that swiftly transforms 2D images into high-quality 3D models with unmatched speed and fidelity. Furthermore, 3DFY.ai Image significantly cuts down the time and expenses associated with converting product catalogs from 2D to 3D for retailers, integrating seamlessly into their studio production workflows. This advancement not only enhances the visual appeal of products but also streamlines the overall production process, making it more efficient and cost-effective.
Description
Recent advancements in the realm of text-to-image synthesis have emerged from diffusion models that have been trained on vast amounts of image-text pairs. To successfully transition this methodology to 3D synthesis, it would necessitate extensive datasets of labeled 3D assets alongside effective architectures for denoising 3D information, both of which are currently lacking. In this study, we address these challenges by leveraging a pre-existing 2D text-to-image diffusion model to achieve text-to-3D synthesis. We propose a novel loss function grounded in probability density distillation that allows a 2D diffusion model to serve as a guiding principle for the optimization of a parametric image generator. By implementing this loss in a DeepDream-inspired approach, we refine a randomly initialized 3D model, specifically a Neural Radiance Field (NeRF), through gradient descent to ensure its 2D renderings from various angles exhibit a minimized loss. Consequently, the 3D representation generated from the specified text can be observed from multiple perspectives, illuminated with various lighting conditions, or seamlessly integrated into diverse 3D settings. This innovative method opens new avenues for the application of 3D modeling in creative and commercial fields.
API Access
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API Access
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Pricing Details
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Free Trial
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Free Version
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Pricing Details
No price information available.
Free Trial
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Free Version
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Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
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Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
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Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
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Live Training (Online)
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In Person
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Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
3DFY.ai
Website
3dfy.ai/
Vendor Details
Company Name
DreamFusion
Website
dreamfusion3d.github.io