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ease
features
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support

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Description

The open-source platform designed for the processing and editing of 3D triangular meshes offers an array of tools for various tasks, such as editing, cleaning, healing, inspecting, rendering, texturing, and converting these meshes. It includes capabilities for handling raw data generated by 3D digitization devices and for preparing models suitable for 3D printing applications. In the latest update, support has been added for multiple file formats (.gltf, .glb, .nxs, .nxz, .e57), along with the introduction of a new plugin dedicated to precise mesh boolean operations. A critical phase in the workflow for handling 3D scanned data is the 3D data alignment process, often referred to as registration. MeshLab equips users with robust tools to align various meshes within a unified reference framework, effectively managing extensive sets of range maps. Additionally, it features a finely-tuned Iterative Closest Point (ICP) algorithm for one-to-one alignment, which is complemented by a global bundle adjustment step to optimize error distribution. Users can perform this alignment on both meshes and point clouds obtained from a variety of sources, including active scanners, whether they operate over short or long ranges. This versatility enhances the overall functionality and effectiveness of the tool in 3D data processing.

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

Sketchfab

Integrations

Sketchfab

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

MeshLab

Country

3D Rendering

Website

www.meshlab.net

Vendor Details

Company Name

Text2Mesh

Website

threedle.github.io/text2mesh/

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