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What is GET3D?
We develop a three-dimensional signed distance field (SDF) alongside a textured field using two latent codes. To extract a 3D surface mesh from the SDF, we utilize DMTet, sampling the texture field at surface points for color information. Our training process includes adversarial losses centered on 2D images, employing a rasterization-based differentiable renderer to generate both RGB visuals and silhouettes. To differentiate between real and generated inputs, we introduce two distinct 2D discriminators—one dedicated to RGB images and the other to silhouettes. The entire system is structured to enable end-to-end training. As various industries shift towards creating expansive 3D virtual environments, the necessity for scalable tools capable of generating large volumes of high-quality and diverse 3D content becomes increasingly evident. Our research aims to develop robust 3D generative models that produce textured meshes, facilitating their seamless integration into 3D rendering engines for immediate deployment in a range of applications. This strategy not only addresses the challenge of scalability but also opens up new avenues for innovative uses in fields like virtual reality and gaming. Moreover, by enhancing the quality and diversity of 3D content, we aim to push the boundaries of creativity and interactivity within these immersive environments.
What is AWS Thinkbox Sequoia?
AWS Thinkbox Sequoia is a specialized software application tailored for processing point clouds and generating meshes, compatible with Windows, Linux, and macOS operating systems. This application adeptly manages point cloud and mesh data across various popular formats, transforming point cloud information into a fast-access intermediate cache format. Sequoia features sophisticated workflows that emphasize the preservation of high-precision data, allowing users to visualize entire point clouds or selected segments using adaptive, view-dependent methods. Users can manipulate, trim, and modify point cloud data, generate meshes from these clouds, and improve the quality of the resulting meshes. Furthermore, the software supports the projection of images onto both points and meshes, creating mesh vertex colors, Ptex, or UV-based textures that are derived from the colors of the point clouds and these image projections. In addition, it provides the capability to export the created meshes to a range of industry-standard mesh file formats and integrates smoothly with Thinkbox Deadline, which facilitates the conversion, meshing, and export of point cloud data across network nodes. This integration significantly boosts productivity and efficiency in 3D modeling tasks. Ultimately, Sequoia not only streamlines the workflow but also empowers professionals to handle intricate spatial data with greater ease and precision, thereby enhancing their creative processes.
Integrations Supported
AWS Thinkbox Deadline
Amazon Web Services (AWS)
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
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
NVIDIA
Company Location
United States
Company Website
nv-tlabs.github.io/GET3D/
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/thinkbox-sequoia/