$\alpha$ Surf

Note: This is a preliminary repo for submission of supplementary material only.

Setup

First create the virtualenv; we recommend using conda:

conda env create -f environment.yml
conda activate alphasurf

Then install pytorch with CUDA support via:

conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cudatoolkit=11.3 -c pytorch

Then install the C++/CUDA extension at root by simply running

pip install .

In the repo root directory.

If your CUDA toolkit is older than 11, then you will need to install CUB as follows: conda install -c bottler nvidiacub. Since CUDA 11, CUB is shipped with the toolkit.

Train and eval

An example script for training Plenoxels + our method is avaliable at train_eval.sh

Random tip (given by authors of Plenoxels): how to make pip install faster for native extensions

You may notice that this CUDA extension takes forever to install. A suggestion is using ninja. On Ubuntu, install it with sudo apt install ninja-build. Then set the environment variable MAX_JOBS to the number of CPUS to use in parallel (e.g. 12) in your shell startup script. This will enable parallel compilation and significantly improve iteration speed.