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VQRF

★ 318 Open GitHub ↗

Official implementation of our CVPR 2023 paper "Compressing Volumetric Radiance Fields to 1 MB"

// repository documentation

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# Compressing Volumetric Radiance Fields to 1 MB (CVPR2023)

Lingzhi Li*, Zhen Shen*, Zhongshu Wang, Li Shen, Liefeng Bo

Alibaba Group

:+1:**Update**: We Released [VQ-TensoRF](https://github.com/Spark001/VQ-TensoRF)  :+1:

Citation:
```
@inproceedings{li2023compressing,
  title={Compressing volumetric radiance fields to 1 mb},
  author={Li, Lingzhi and Shen, Zhen and Wang, Zhongshu and Shen, Li and Bo, Liefeng},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={4222--4231},
  year={2023}
}
```

![compression](https://raw.githubusercontent.com/AlgoHunt/VQRF/master/figures/teaser.png)

![Pipeline](https://raw.githubusercontent.com/AlgoHunt/VQRF/master/figures/pipeline.png)

**Note**: This repository only contain VQ-DVGO.

## Setup

- Download datasets:
        [NeRF](https://drive.google.com/drive/folders/128yBriW1IG_3NJ5Rp7APSTZsJqdJdfc1)
        [NSVF](https://dl.fbaipublicfiles.com/nsvf/dataset/Synthetic_NSVF.zip),  [T&T (masked)](https://dl.fbaipublicfiles.com/nsvf/dataset/TanksAndTemple.zip)

- Install required libraries
```
pip install -r requirements.txt
cd lib/cuda
python setup.py install
```

Please  install the correct version of [Pytorch](https://pytorch.org/) and [torch_scatter](https://github.com/rusty1s/pytorch_scatter) for your machine.

## Directory structure for the datasets

## Training

```
# for nerf_synthetic datasets
python autotask_final.py -g "0 1 2 3 4 5 6 7"  --configname syn_4096code

# for Synthetic_NSVF datasets
python autotask_final.py -g "0 1 2 3 4 5 6 7"  --configname nsvf_4096code --dataset nsvf

# for TanksAndTemple datasets
python autotask_final.py -g "0 1 2 3 4 5 6 7"  --configname tnt_4096code  --dataset tnt
```

Fixing TanksandTemples dataset following this [issue](https://github.com/sunset1995/DirectVoxGO/issues/4)

Set `-g` option according to the availible gpu on your machine.

## Testing

```
# for nerf_synthetic datasets
python autotask_eval_only.py -g "0 1 2 3 4 5 6 7"  --configname syn_4096code

# for Synthetic_NSVF datasets
python autotask_eval_only.py -g "0 1 2 3 4 5 6 7"  --configname nsvf_4096code --dataset nsvf

# for TanksAndTemple datasets
python autotask_eval_only.py -g "0 1 2 3 4 5 6 7"  --configname tnt_4096code  --dataset tnt
```

VQRF

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