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Description
S-FRAME empowers users to model, analyze, and design any type of structure, accommodating a wide range of geometric complexities, material specifications, loading scenarios, nonlinear behaviors, and design code stipulations. The platform features automated framework generators that facilitate rapid model creation and offers seamless integration with BIM and DXF formats, allowing users to enhance their efficiency with built-in design tools for concrete and steel, which support design, optimization, code adherence, and report generation. Through S-FRAME, users can swiftly define structures with advanced modeling automation, enabling the generation of regular framework structures and both standard and custom trusses, while clone tools allow for the easy replication of entire models or specific sections. Moreover, the ability to import existing BIM and DXF models significantly reduces modeling time, further improving productivity. The sophisticated meshing capabilities of S-FRAME create a detailed finite element mesh, equipping users to derive comprehensive analysis results tailored to their areas of interest. Lastly, users have the flexibility to delve deeper into their analysis by converting members into multi-shell models, enhancing their understanding and evaluation of structural performance.
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
Integrations
AutoCAD
Revit
Tekla Structures
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
Altair
Country
United States
Website
www.altair.com/s-frame
Vendor Details
Company Name
Text2Mesh
Website
threedle.github.io/text2mesh/
