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What is Text2Mesh?

Text2Mesh creates complex geometric shapes and vibrant colors from different source meshes, all driven by a text prompt provided by the user. Our stylization method skillfully merges unique and often disparate text inputs, effectively reflecting both general meanings and detailed features tailored to specific parts of the mesh. This innovative system enhances a 3D model by predicting appropriate colors and fine geometric details that resonate with the given text prompt. We utilize a disentangled representation of a 3D object, incorporating a static mesh as content alongside a neural network that we call the neural style field network. To modify the style, we assess a similarity score between the descriptive text of the style and the resulting stylized mesh, utilizing CLIP’s powerful representational strengths. What distinguishes Text2Mesh is its capability to function without relying on any prior generative model or a dedicated dataset of 3D meshes. Additionally, it can adeptly handle lower-quality meshes, which may include problematic non-manifold structures and various topological complexities, all without requiring UV parameterization. This remarkable versatility positions Text2Mesh as a valuable resource for artists and developers eager to effortlessly produce stylized 3D models, opening up new avenues for creative exploration. Ultimately, Text2Mesh not only enhances the artistic process but also streamlines the workflow for 3D model creation, making artistic expression more accessible than ever before.

What is Manifold?

Manifold is a cutting-edge application tailored for field documentation and 3D scanning, specifically designed for contractors and field teams. By harnessing the power of LiDAR technology, the app allows users to swiftly scan physical spaces and generate detailed floor plans in under 30 seconds. It captures complex 3D data with remarkable precision, enabling accurate measurements to within half an inch, as well as the creation of digital twins, X-ray views, and immersive 360° virtual experiences. The cloud-based nature of Manifold streamlines the processing of scans, organizing them into a structured digital layout and eliminating the tedious process of manual point cloud registration. Moreover, the application boasts comprehensive photo documentation capabilities, automatically categorizing images by GPS location, timestamps, and user details, while also providing features for annotation, tagging, and unlimited cloud storage. Teams can work together efficiently in real-time with tools designed for project timelines, comments, and task management, fostering enhanced communication and collaboration among all members. In addition, the platform’s user-friendly interface ensures that individuals of all technical skills can navigate and utilize its functionalities with ease, making it an invaluable tool in the field. This ensures that every team member, regardless of their background, can contribute effectively to project success.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$16 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Text2Mesh

Company Website

threedle.github.io/text2mesh/

Company Facts

Organization Name

Manifold

Date Founded

2020

Company Location

Canada

Company Website

www.scanmanifold.com

Categories and Features

Categories and Features

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