LichtFeld Studio
v0.1.0High-performance C++/CUDA 3D Gaussian Splatting implementation with real-time viewer and training capabilities
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Overview
Best for
High-performance 3D Gaussian Splatting training and real-time viewing in C++ environments, or scenarios where Python overhead is unacceptable
Not ideal for
Rapid research prototyping and experimentation with novel 3DGS variants — Python-based tools like gsplat and Nerfstudio offer faster iteration cycles and a larger ecosystem of research extensions
Strengths
- C++ and CUDA implementation eliminates Python interpreter overhead, enabling potentially faster training and rendering throughput for large-scale 3DGS scenes compared to Python-based alternatives
- Standalone binary deployment eliminates the need for Python environments, conda, pip, or PyTorch installation — critical for production deployment, embedded systems, and integration into existing C++ pipelines
- Integrated real-time viewer with interactive camera controls enables immediate visual inspection of trained 3DGS models without external visualization tools
- Active development by the MrNeRF group, which is well-established in the neural rendering community for systematic benchmarking and analysis of 3DGS methods
- Clean C++ codebase serves as a reference implementation for understanding 3DGS at the systems level rather than through the abstraction layers of Python and PyTorch
Limitations
- GPL-3.0 license imposes copyleft requirements — all derivative works must also be open-sourced under GPL, which may be prohibitive for commercial applications where gsplat (Apache-2.0) or Nerfstudio (Apache-2.0) are preferred
- Significantly harder to modify for research experimentation compared to Python-based alternatives — changing C++/CUDA code requires recompilation and has a higher skill barrier than modifying Python/PyTorch code
- Smaller community and fewer research extensions compared to the Nerfstudio/gsplat ecosystem, which benefits from a large Python ML research community and rapid publication-to-implementation cycles
- Requires NVIDIA GPU with CUDA — no CPU fallback, no AMD GPU support, no Apple Silicon support, limiting hardware compatibility
- CMake-based C++ build process with CUDA dependencies can be complex to set up, particularly on Windows, compared to the simple pip install workflow of Python alternatives
Background
LichtFeld Studio is a C++ and CUDA implementation of 3D Gaussian Splatting (3DGS), the neural rendering technique that represents scenes as millions of oriented 3D Gaussians for real-time novel view synthesis. Developed by MrNeRF (Tobias Fischer) and contributors, it provides an alternative to the dominant Python-based 3DGS ecosystem by implementing the entire training and rendering pipeline in native C++ and CUDA, eliminating Python interpreter overhead.
The name 'LichtFeld' is German for 'light field,' referencing the light field rendering concept that 3DGS extends to achieve real-time radiance field rendering. The project's C++ architecture enables faster throughput for large-scale scenes compared to Python-centric alternatives like the original INRIA implementation, gsplat, or Nerfstudio. It includes an integrated real-time viewer with interactive camera controls for inspecting trained 3DGS models, and supports the standard COLMAP-based input pipeline for training from multi-view photographs.
While the C++ codebase offers significant deployment advantages — standalone binaries without Python dependencies, easier integration into C++ production pipelines, and reduced runtime overhead — it trades away the rapid prototyping flexibility that makes Python-based tools preferred in the ML research community. LichtFeld Studio is particularly relevant for production scenarios where Python overhead is unacceptable, where integration with existing C++ infrastructure is required, or where deploying a standalone application without a Python runtime is necessary.
Quick Start
Visit the repository for installation instructions for LichtFeld Studio.
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Performance Benchmarks
No benchmark data available for LichtFeld Studio yet.
Benchmarks will be added as more renderers are tested across our standard scene suite.
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