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A CUDA-enhanced package for common NeRF model operations

Project description

nerfboost

nerfboost is a CUDA-accelerated Python package that enhances common operations required for Neural Radiance Fields (NeRF) models. It provides high-performance implementations of key functions such as positional encoding, stratified sampling, volume rendering, and more, to accelerate NeRF training and rendering.

Features

  • CUDA-accelerated functions for efficient neural rendering tasks.
  • Implements key operations for NeRF models like:
    • Positional encoding
    • Stratified, uniform, and hierarchical sampling
    • Volume rendering
    • MLP network processing
    • Rendering loss computation
  • Easy integration with PyTorch using custom CUDA kernels.

Installation

You can install nerfboost using the following command:

pip install nerfboost

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