Ever wanted to train a NeRF model of a fox in under 5 seconds? Or fly around a scene captured from photos of a factory robot? Of course you have!
Here you will find an implementation of four neural graphics primitives, being neural radiance fields (NeRF), signed distance functions (SDFs), neural images, and neural volumes. In each case, we train and render a MLP with multiresolution hash input encoding using the tiny-cuda-nn framework.
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding Thomas Müller, Alex Evans, Christoph Schied, Alexander Keller arXiv [cs.GR], Jan 2022 [ Project page ] [ Paper ] [ Video ]
We also recommend installing CUDA and OptiX in /usr/local/ and adding the CUDA installation to your path. For example, if you have CUDA 11.4, add the following to your ~/.bashrc
If the build succeeded, you can now run the code via the build/testbed executable or the scripts/run.py script described below.