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https://github.com/dvlab-research/EfficientNeRF
The official code for "Efficient Neural Radiance Fields" in CVPR2022.
https://github.com/dvlab-research/EfficientNeRF
Last synced: about 22 hours ago
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The official code for "Efficient Neural Radiance Fields" in CVPR2022.
- Host: GitHub
- URL: https://github.com/dvlab-research/EfficientNeRF
- Owner: dvlab-research
- Created: 2022-03-25T11:51:10.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-07-13T13:00:29.000Z (over 2 years ago)
- Last Synced: 2023-11-07T17:15:02.434Z (about 1 year ago)
- Language: Python
- Size: 43 KB
- Stars: 145
- Watchers: 11
- Forks: 10
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
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README
## The official code for "[EfficientNeRF: Efficient Neural Radiance Fields](https://arxiv.org/abs/2206.00878)" in CVPR2022.
### Environment (Tested)
- Ubuntu 18.04
- Python 3.7
- CUDA 11.x
- Pytorch 1.9.1
- Pytorch-Lightning 1.6.4
### Install via Anaconda
```
$ conda create -n EfficientNeRF python=3.8
$ conda activate EfficientNeRF
$ pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
$ pip install -r requirements.txt
```
### Training
```
$ DATA_DIR=/path/to/lego
$ python train.py \
--dataset_name blender \
--root_dir $DATA_DIR \
--N_samples 128 \
--N_importance 5 --img_wh 800 800 \
--num_epochs 16 --batch_size 4096 \
--optimizer radam --lr 2e-3 \
--lr_scheduler poly \
--coord_scope 3.0 \
--warmup_step 5000\
--sigma_init 30.0 \
--weight_threashold 1e-5 \
--exp_name lego_coarse128_fine5_V384
```
### Visualization
```
$ tensorboard --logdir=./logs
```
### Question
- Q1. Different hyperparameters from the original paper
* A1. There are many combinations between these hyperparameters. You are free to balance the training speed and accuracy by modify them.
- Q2. When will NeRF-Tree released?
* A2. Hard to say a specific date. The data structure NeRF-Tree is closed to Octree.
### Progress
More scenes and applications will be suported soon. Stay tune!
### Acknowledgement
Our initial code was borrowed from
- [nerf-pl:https://github.com/kwea123/nerf_pl](https://github.com/kwea123/nerf_pl)
### Citation
If you find our code or paper helps, please cite our paper:
```
@InProceedings{Hu_2022_CVPR,
author = {Hu, Tao and Liu, Shu and Chen, Yilun and Shen, Tiancheng and Jia, Jiaya},
title = {EfficientNeRF Efficient Neural Radiance Fields},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2022},
pages = {12902-12911}
}
```