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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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

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

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
Animation
Annotations
Bill of Materials
Character Modeling
Collaboration Tools
Component Library
Data Import / Export
For 3D Printing
For Architects
For Manufacturers
Reference Management
Simulation

Computer Vision

Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration

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