This repository contains the code release for the paper:
Binary Radiance Fields
Seungjoo Shin1, and Jaesik Park2
1 POSTECH, 2 Seoul National University
Conference on Neural Information Processing Systems (NeurIPS), New Orleans, 2023
We have tested on PyTorch==1.13.0
with CUDA==11.7
.
git clone https://github.com/SAITPublic/BiRF.git
cd BiRF
conda create --name birf -y python=3.8
conda activate birf
# install PyTorch==1.13.0 with CUDA==11.7
conda install pytorch==1.13.0 torchvision==0.13.0 torchaudio==0.12.0 cudatoolkit=11.7 -c pytorch
# install custom tiny-cuda-nn
pip install git+https://github.com/seungjooshin/tiny-cuda-nn/@bit#subdirectory=bindings/torch
# install requirements
pip install -r requirements.txt
We support three datasets for evaluation.
By default, we put the dataset under ./data/
as:
├── data
├── nerf_synthetic
├── chair
├── drums
├── ....
├── Synthetic_NSVF
├── Bike
├── Liferstyle
├── ....
├── TanksAndTemples
├── Barn
├── Caterpillar
├── ....
# python train.py ./config/{size}.gin --scene {scene} --n_features {n_features}
python train.py ./config/base.gin --scene chair --n_features 2
size
: the size of hash tablescene
: the scene to reconstructn_features
: the number of features- The result is saved as
{log_dir}/results_{seed}.json
.
# python test.py ./config/{size}.gin --scene {scene} --n_features {n_features} --log_dir {path_to_log_dir}
python test.py ./config/base.gin --scene chair --n_features 2 --log_dir ./logs/chair_f2_2023
size
: the size of hash tablescene
: the scene to reconstructn_features
: the number of featureslog_dir
: the path to log directory- The result is saved as
{log_dir}/results.json
.
By default, we save the log under ./logs/
.
├── logs
├── chair_b_2
├── imgs
├── 0000.png
├── 0001.png
├── ....
├── config.gin
├── encoding.npz
├── network.ckpt
├── occgrid.npz
├── results.json
├── chair_s_2
├── ....
If you find our code or paper useful, please consider citing our paper:
@inproceedings{
shin2023binary,
title={Binary Radiance Fields},
author={Seungjoo Shin and Jaesik Park},
booktitle={Advances in Neural Information Processing Systems},
year={2023}
}