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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
Rayfront is a versatile toolkit that operates independently of platforms, offering a user-friendly graphical interface for the lighting simulation software Radiance. It can function both as an extension to programs like Autocad or Intellicad, in conjunction with the 3Dsolar building modeller, or as a standalone application. Radiance serves as the premier raytracing engine in the industry, known for delivering physically accurate lighting simulations. Although Radiance can be obtained for free from LBNL, it is tools like Rayfront that allow everyday users to harness its capabilities seamlessly on personal computers and within local networks. Furthermore, Rayfront is compatible with a wide array of CAD and modeling applications, as it supports all DXF file formats and comes equipped with translators for numerous other data formats. You can easily choose either a free or commercial geometry modeler that suits your needs, and rest assured that there will be a method to integrate its output data with Rayfront effectively. This flexibility makes Rayfront an invaluable asset for those looking to enhance their architectural and lighting design workflows.
API Access
Has API
No
API Access
Has API
No
Integrations
Radiance
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
DreamFusion
Website
dreamfusion3d.github.io
Vendor Details
Company Name
schorsch.com
Country
Germany
Website
www.schorsch.com/en/software/rayfront/