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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
Pony Diffusion is a dynamic text-to-image diffusion model that excels in producing high-quality, non-photorealistic images in a variety of artistic styles. With its intuitive interface, users can easily input descriptive text prompts, resulting in vibrant visuals that range from whimsical pony-themed illustrations to captivating fantasy landscapes. To enhance relevance and maintain aesthetic coherence, this finely-tuned model utilizes a dataset comprising around 80,000 pony-related images. Additionally, it employs CLIP-based aesthetic ranking to assess image quality throughout the training process and features a scoring system that helps optimize the quality of the generated outputs. The operation is simple; users craft a descriptive prompt, execute the model, and can then save or share the resulting image with ease. The service emphasizes that the model is designed to create SFW content and operates under an OpenRAIL-M license, enabling users to freely utilize, redistribute, and adjust the outputs while adhering to specific guidelines. This ensures both creativity and compliance within the community.
API Access
Has API
API Access
Has API
Integrations
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Integrations
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Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
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
Pony Diffusion
Country
United States
Website
ponydiffusion.com