Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Ambient Mesh is a modern service mesh architecture designed to eliminate the complexity of traditional sidecar-based approaches. It secures, observes, and connects cloud-native workloads with minimal intrusion and resource consumption. Ambient Mesh delivers zero-trust security using workload identity, encryption, and automated certificate management. Teams gain deep visibility into traffic flows through distributed tracing, logs, and performance metrics. Advanced traffic control features support safe deployments, intelligent routing, and seamless failover. The platform improves resilience with circuit breaking, zone-aware load balancing, and retry policies. Ambient Mesh enables organizations to migrate existing sidecar workloads with zero downtime. A free migration tool provides automated analysis and step-by-step guidance. This approach reduces operational risk while maintaining compliance and control. Ambient Mesh simplifies service mesh adoption while lowering infrastructure costs.
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
Yes
API Access
Has API
No
Integrations
Amazon EKS
Yes
Amazon EKS Anywhere
Yes
Amazon Web Services (AWS)
Yes
Azure Kubernetes Service (AKS)
Yes
Cilium
Yes
Envoy
Yes
Google Cloud Platform
Yes
Google Kubernetes Engine (GKE)
Yes
GraphQL
Yes
Hubble
Yes
Integrations
Amazon EKS
No
Amazon EKS Anywhere
No
Amazon Web Services (AWS)
No
Azure Kubernetes Service (AKS)
No
Cilium
No
Envoy
No
Google Cloud Platform
No
Google Kubernetes Engine (GKE)
No
GraphQL
No
Hubble
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Ambient Mesh
Founded
2017
Country
United States
Website
ambientmesh.io
Vendor Details
Company Name
Text2Mesh
Website
threedle.github.io/text2mesh/