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What is Mitsuba?

Mitsuba 2 is a versatile rendering system designed for research purposes, implemented in portable C++17 and utilizing the Enoki library, which was developed by the Realistic Graphics Lab at EPFL. It features multiple variants to support different color formats, including RGB, spectral, and monochrome, and offers various vectorization methods such as scalar, SIMD, and CUDA, alongside options for differentiable rendering. The system consists of a streamlined set of core libraries and is enhanced by a wide range of plugins that add functionalities like different materials, lighting options, and advanced rendering algorithms. Mitsuba 2 is designed to ensure continuity with its predecessor, Mitsuba 0.6, facilitating an easy transition for existing users. Additionally, the rendering engine is supported by a comprehensive automated testing framework developed in Python, and its continuous development is bolstered by several integration servers that compile and validate updates across different operating systems and compilation settings, including both debug and release configurations as well as single and double precision. This rigorous testing system not only boosts the software's reliability but also makes it an indispensable asset for researchers engaged in graphics studies, enabling them to explore cutting-edge rendering techniques with confidence. Overall, the collaborative effort behind Mitsuba 2 reflects a commitment to advancing the field of computer graphics through robust and flexible tools.

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

Mitsuba

Company Website

www.mitsuba-renderer.org

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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