293-lighting-up-nerf-via-unsupervised-decomposition-and-enhancement

https://github.com/szu-advtech-2023/293-lighting-up-nerf-via-unsupervised-decomposition-and-enhancement

Science Score: 18.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (9.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: SZU-AdvTech-2023
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 2.04 MB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed over 2 years ago
Metadata Files
Citation

https://github.com/SZU-AdvTech-2023/293-Lighting-up-NeRF-via-Unsupervised-Decomposition-and-Enhancement/blob/main/

##  How to run

1.  **Setup the environment:** We provide the exported conda yaml file `environment.yml`. Please make sure you installed `conda` and run:

  ```shell
  conda env create -f environment.yml
  conda activate llnerf
  ```
  Note that this repo requires `jax` and `flax`. We use `cuda 11.7` and `cudnn 8.2`. If you need to set up the Python environment with a different version of cuda+cudnn, we suggest you manually install jax, jaxlib, and flax to ensure compatibility with your cuda environment. Please refer to their official documentation for installation instructions. If you encounter any issues during the jax installation, please consult their official documentation for troubleshooting.


2.  **Download the dataset:** dataset is [here](https://drive.google.com/drive/folders/1h-u8DkvuaIvcHZihYIWcqwpURiM32_u3?usp=sharing). Please download and unzip it.

3.  **Training:** Please modify `scripts/train.sh` first by replacing the dataset path and scene name with yours, and run `bash scripts/train.sh`.

4.  **Rendering:** Please modify `scripts/render.sh` first by replacing the dataset path and scene name with yours, and run `bash scripts/render.sh`.

##  Cite This Paper

```bibtex
@inproceedings{wang2023lighting,
  title={Lighting up NeRF via Unsupervised Decomposition and Enhancement},
  author={Haoyuan Wang, Xiaogang Xu, Ke Xu, and Rynson W.H. Lau},
  booktitle={ICCV},
  year={2023}
}
```

Owner

  • Name: SZU-AdvTech-2023
  • Login: SZU-AdvTech-2023
  • Kind: organization

Citation (citation.txt)

@inproceedings{REPO293,
    author = "Wang, Haoyuan and Xu, Xiaogang and Xu, Ke and Lau, Rynson WH",
    booktitle = "Proceedings of the IEEE/CVF International Conference on Computer Vision",
    pages = "12632--12641",
    title = "{Lighting up NeRF via Unsupervised Decomposition and Enhancement}",
    year = "2023"
}

GitHub Events

Total
Last Year