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Mitsuba icon

Mitsuba

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Mitsuba is a research-oriented rendering system for forward and inverse light transport simulation. It consists of a core library and a set of plugins that implement functionality ranging from materials and light sources to complete rendering algorithms.

Mitsuba screenshot 1

License model

  • FreeOpen Source

Platforms

  • Mac
  • Windows
  • Linux
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Mitsuba information

  • Developed by

    Realistic Graphics Lab
  • Licensing

    Open Source and Free product.
  • Written in

  • Alternatives

    52 alternatives listed
  • Supported Languages

    • English

AlternativeTo Category

Photos & Graphics

GitHub repository

  •  2,270 Stars
  •  265 Forks
  •  95 Open Issues
  •   Updated Mar 21, 2025 
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Mitsuba was added to AlternativeTo by nbendala on Dec 23, 2010 and this page was last updated Mar 27, 2023.
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What is Mitsuba?

Mitsuba is a research-oriented rendering system for forward and inverse light transport simulation. It consists of a core library and a set of plugins that implement functionality ranging from materials and light sources to complete rendering algorithms.

Main Features

  • Retargetable: this means that the underlying implementations and data structures can transform to accomplish various different tasks.
  • Differentiation: Mitsuba is a differentiable renderer, meaning that it can compute derivatives of the entire simulation with respect to input parameters such as camera pose, geometry, BSDFs, textures, and volumes.
  • Spectral & Polarization: Mitsuba can be used as a monochromatic renderer, RGB-based renderer, or spectral renderer. Each variant can optionally account for the effects of polarization if desired.
  • High performance: The underlying Dr.Jit compiler fuses rendering code into kernels that achieve state-of-the-art performance using an LLVM backend targeting the CPU and a CUDA/OptiX backend targeting NVIDIA GPUs with ray tracing hardware acceleration.
  • Python first: Mitsuba is deeply integrated with Python. Materials, textures, and even full rendering algorithms can be developed in Python, which the system JIT-compiles (and optionally differentiates) on the fly. This enables the experimentation needed for research in computer graphics and other disciplines.
  • Cross-platform: Mitsuba has been tested on Linux (x86_64), macOS (aarch64, x86_64), and Windows (x86_64).

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