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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.
Description
Introducing Mobile Diffusion, a groundbreaking image generator that utilizes cutting-edge AI technology to transform your creative ideas into reality. This application allows users to craft breathtaking images from their own text prompts without the necessity of an internet connection, operating seamlessly offline directly on your device. Powered by the Stable Diffusion v2.1 model, Mobile Diffusion enhances image generation capabilities, benefiting from CoreML optimization that makes it up to twice as fast as competing apps. After a one-time download of the 4.5 GB model, you can enjoy offline functionality, providing the freedom to create anywhere and at any time. The app empowers users to refine their results by specifying both positive and negative prompts, ensuring the generated images align perfectly with their vision. Sharing your creations is straightforward, and the app is entirely free to access. Designed primarily for research and development, it showcases the potential of running a diffusion model on mobile devices while maintaining acceptable performance levels, highlighting the future of mobile creativity. With its user-friendly interface and powerful features, Mobile Diffusion is set to revolutionize the way we think about image generation on the go.
API Access
Has API
API Access
Has API
Integrations
Stable Diffusion
Pricing Details
No price information available.
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
DreamFusion
Website
dreamfusion3d.github.io
Vendor Details
Company Name
N1 RND
Website
apps.apple.com/pl/app/mobile-diffusion