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Description
Copilot 3D is an innovative, AI-driven application found within Microsoft’s Copilot Labs that allows users to transform a single 2D image (either JPG or PNG, with a maximum size of 10 MB) into a complete 3D model (in GLB format) without needing any technical skills. Focusing on ease of use for creative individuals, the tool requires merely the upload of an image and produces a 3D file that users can download. This service is available worldwide at no additional cost to those with a personal Microsoft account, making it a valuable resource for various fields such as game development, animation, 3D printing, virtual and augmented reality, and digital content creation. Although Copilot 3D is particularly effective at generating models of typical inanimate objects like furniture and everyday items, it encounters challenges when dealing with intricate subjects, including animals or human representations. Additionally, the system incorporates safeguards to block the creation of copyrighted or sensitive content, and it retains user-generated models for a period of 28 days. Overall, the tool serves as a gateway for many users to explore the fascinating world of 3D modeling effortlessly.
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
Has API
API Access
Has API
Integrations
Microsoft 365
Microsoft Copilot
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
copilot.microsoft.com/labs/experiments/3d-generations
Vendor Details
Company Name
DreamFusion
Website
dreamfusion3d.github.io