This repository contains the official implementation of the following paper:
Multi-Space Neural Radiance Fields
Ze-Xin Yin, Jiaxiong Qiu, Ming-Ming Cheng, Bo Ren*
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
[Arxiv] [Project Page] [Dataset] [Checkpoints]
- [√] Release the training and evaluation code for Mip-NeRF 360-based experiments.
- Integrate the Mip-NeRF and NeRF -based code into the Jax version of implementation.
- Re-implement a PyTorch version of the codebase.
We build our code on top of MultiNeRF, please check the code in jax/
.
We are working on this...
If you find our repo useful for your research, please consider citing our paper:
@InProceedings{Yin_2023_CVPR,
author = {Yin, Ze-Xin and Qiu, Jiaxiong and Cheng, Ming-Ming and Ren, Bo},
title = {Multi-Space Neural Radiance Fields},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023},
pages = {12407-12416}
}
And the codebase is heavily borrowed from MultiNeRF, please consider also cite this repository:
@misc{multinerf2022,
title={{MultiNeRF}: {A} {Code} {Release} for {Mip-NeRF} 360, {Ref-NeRF}, and {RawNeRF}},
author={Ben Mildenhall and Dor Verbin and Pratul P. Srinivasan and Peter Hedman and Ricardo Martin-Brualla and Jonathan T. Barron},
year={2022},
url={https://github.com/google-research/multinerf},
}
Licensed under a Creative Commons Attribution-NonCommercial 4.0 International for Non-commercial use only. Any commercial use should get formal permission first.
We thank for some wonderful nerf repos, including mipnerf, multinerf, nerf-pytorch , nerfren, and nerf_pl. We heavily borrow codes from these projects.