Here is the code for our paper on DirectVoxGO++
Use the docker image
sudo docker build -t dvgopp .
sudo nvidia-docker run -it --rm --volume /:/host --workdir /host$PWD dvgopp
To download the dataset, go to https://drive.google.com/file/d/1cCU35cIur-PXPKRqQxD6aKHWQmuEanoN/view?usp=share_link
All config files to reproduce our results:
$ ls configs/*
configs/llff:
africa.py ship.py basket.py torch.py
The code base is origined from DirectVoxGO, we thank the authors for releasing their awesome code! We are standing on the shoulders of giants!:)
If you find this work helps you, please cite:
@article{perazzo2023directvoxgo++,
title={DirectVoxGO++: Grid-based fast object reconstruction using radiance fields},
author={Perazzo, Daniel and Lima, Jo{\~a}o Paulo and Velho, Luiz and Teichrieb, Veronica},
journal={Computers \& Graphics},
year={2023},
publisher={Elsevier}
}