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Description
Our cutting-edge geometric deep learning technology seamlessly connects tangible objects with digital programming. We are revolutionizing the landscape of engineering, industrial design, and procurement, empowering innovators and creators through the transformation of each 3D model. Leveraging unique algorithms alongside sophisticated geometric deep learning, Physna translates 3D models into comprehensive data that can be interpreted by various software applications. By allowing 3D models to be analyzed and manipulated like traditional code, Physna’s innovation effectively closes the divide between the physical realm and the software-centric digital domain. The platform evaluates CAD and other types of 3D models, producing a codified version known as the “Physna DNA” of each model. This digital representation enables Physna to highlight intricate differences and similarities across models, even those that are incomplete or formatted differently. Furthermore, it provides visibility into all components within complex assemblies, including parts nested within other parts, which enhances the understanding of intricate designs. Ultimately, this technology opens new avenues for collaboration and efficiency in various industries.
Description
Text2Mesh generates intricate geometric and color details across various source meshes, guided by a specified text prompt. The results of our stylization process seamlessly integrate unique and seemingly unrelated text combinations, effectively capturing both overarching semantics and specific part-aware features. Our system, Text2Mesh, enhances a 3D mesh by predicting colors and local geometric intricacies that align with the desired text prompt. We adopt a disentangled representation of a 3D object, using a fixed mesh as content integrated with a learned neural network, which we refer to as the neural style field network. To alter the style, we compute a similarity score between the style-describing text prompt and the stylized mesh by leveraging CLIP's representational capabilities. What sets Text2Mesh apart is its independence from a pre-existing generative model or a specialized dataset of 3D meshes. Furthermore, it is capable of processing low-quality meshes, including those with non-manifold structures and arbitrary genus, without the need for UV parameterization, thus enhancing its versatility in various applications. This flexibility makes Text2Mesh a powerful tool for artists and developers looking to create stylized 3D models effortlessly.
API Access
Has API
No
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
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
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
Yes
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Physna
Founded
2015
Country
United States
Website
physna.com
Vendor Details
Company Name
Text2Mesh
Website
threedle.github.io/text2mesh/
Product Features
3D Modeling
2D Drawing
No
Animation
No
Annotations
No
Bill of Materials
No
Character Modeling
No
Collaboration Tools
No
Component Library
No
Data Import / Export
No
For 3D Printing
No
For Architects
No
For Manufacturers
No
Reference Management
No
Simulation
No
Computer Vision
Blob Detection & Analysis
No
Building Tools
No
Image Processing
No
Multiple Image Type Support
No
Reporting / Analytics Integration
No
Smart Camera Integration
No