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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 Fujiyama?

Fujiyama is an open-source ray-tracing renderer designed for high-quality image production with an emphasis on distributed processing. It employs a multi-threaded approach that efficiently allocates tile rendering tasks across various threads, thereby significantly improving performance. Users can track their rendering progress through the fbview preview tool, which enhances usability. The renderer's region rendering capability accelerates the distribution pipeline, and it utilizes advanced tile-based rendering methods. It includes three unique Volume Filling Procedures: the Pyroclastic clouds, Spline wisps, and Surface wisps procedures, each offering different effects. The system also supports on-demand mipmap reading, ensuring a vast range of texture options is available. With the pluggable shader DSO, users can develop custom shaders in C/C++, benefiting from integrated subsurface scattering within the framework. Bump mapping is achieved by adjusting normals based on mipmap data, while primitive groups enable the assignment of multiple shaders to a single triangle mesh. Furthermore, Fujiyama features Gaussian and Box pixel filters capable of handling filter widths greater than one pixel, which contributes to its flexibility. Its adaptive grid pixel sampling refines pixel subdivisions based on color thresholds, thus producing superior rendering quality. With all these features combined, Fujiyama stands out as an exceptional choice for diverse rendering tasks across various projects.

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

Pricing not provided.
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

NVIDIA

Company Location

United States

Company Website

nv-tlabs.github.io/GET3D/

Company Facts

Organization Name

Fujiyama

Date Founded

2011

Company Location

Japan

Company Website

tsubo164.github.io/Fujiyama-Docs/

Categories and Features

Categories and Features

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