Monopriors

A library to easily get monocular priors such as scale-invariant depths, metric depths, or surface normals. Using Rerun viewer, Pixi and Gradio for easy use

Installation

Easily installable via Pixi.

git clone https://github.com/pablovela5620/monoprior.git
cd monoprior
pixi run app

Demo

Hosted Demos can be found on huggingface spaces

To run the gradio frontend

pixi run app

To see all available tasks

pixi task list

Acknowledgements

Thanks to the following great works!

DepthAnything

@inproceedings{depthanything,
      title={Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data}, 
      author={Yang, Lihe and Kang, Bingyi and Huang, Zilong and Xu, Xiaogang and Feng, Jiashi and Zhao, Hengshuang},
      booktitle={CVPR},
      year={2024}
}

Unidepth

@inproceedings{piccinelli2024unidepth,
    title     = {{U}ni{D}epth: Universal Monocular Metric Depth Estimation},
    author    = {Piccinelli, Luigi and Yang, Yung-Hsu and Sakaridis, Christos and Segu, Mattia and Li, Siyuan and Van Gool, Luc and Yu, Fisher},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    year      = {2024}
}

Metric3D V2

@article{hu2024metric3dv2,
  title={Metric3D v2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation},
  author={Hu, Mu and Yin, Wei and Zhang, Chi and Cai, Zhipeng and Long, Xiaoxiao and Chen, Hao and Wang, Kaixuan and Yu, Gang and Shen, Chunhua and Shen, Shaojie},
  journal={arXiv preprint arXiv:2404.15506},
  year={2024}
}