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Description
Mesh Security represents an advanced cybersecurity solution grounded in Cybersecurity Mesh Architecture (CSMA), designed to consolidate fragmented security data, tools, and infrastructure into a cohesive, real-time adaptive defense system that aids organizations in the ongoing assessment, prioritization, and reduction of risks across various domains, including identities, endpoints, data, cloud, SaaS, CI/CD, and networks. This platform offers comprehensive posture management that persistently detects and contextualizes significant risks and vulnerabilities throughout the enterprise, converts diverse security signals into a dynamic asset graph for enhanced visibility, and facilitates cross-domain threat detection along with automated responses through AI-enhanced anomaly detection and pre-configured detection rules. Additionally, Mesh Security seamlessly integrates with existing security frameworks in just minutes, streamlining remediation processes and minimizing the attack surface without necessitating new infrastructure investments, while also centralizing policy management, playbook execution, and compliance enforcement in hybrid environments. By providing these capabilities, Mesh Security empowers organizations to maintain robust security postures in an increasingly complex threat landscape.
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
Amazon Web Services (AWS)
Box
GitHub
Google Cloud Platform
HiBob
Jira
Microsoft 365
Microsoft Azure
Netskope
Okta
Integrations
Amazon Web Services (AWS)
Box
GitHub
Google Cloud Platform
HiBob
Jira
Microsoft 365
Microsoft Azure
Netskope
Okta
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
Mesh Security
Founded
2022
Country
United States
Website
mesh.security/
Vendor Details
Company Name
Text2Mesh
Website
threedle.github.io/text2mesh/
Product Features
SIEM
Application Security
Behavioral Analytics
Compliance Reporting
Endpoint Management
File Integrity Monitoring
Forensic Analysis
Log Management
Network Monitoring
Real Time Monitoring
Threat Intelligence
User Activity Monitoring