Skip to content

This repo contains the projects: 'Virtual Normal', 'DiverseDepth', and '3D Scene Shape'. They aim to solve the monocular depth estimation, 3D scene reconstruction from single image problems.

License

Notifications You must be signed in to change notification settings

andy500/AdelaiDepth

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

60 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

AdelaiDepth

Open In Colab

AdelaiDepth is an open source toolbox for monocular depth prediction. Relevant work from our group is open-sourced here.

AdelaiDepth contains the following algorithms:

News:

  • [Jun. 13, 2021] Our "Learning to Recover 3D Scene Shape from a Single Image" work is in the CVPR'21 Best Paper Finalist.
  • [Jun. 6, 2021] We have made the training data of DiverseDepth available.

Results and Dataset Examples:

  1. 3D Scene Shape

You may want to check this video which provides a very brief introduction to the work:

RGB Depth Point Cloud

Depth

  1. DiverseDepth

Results examples.

Depth

DiverseDepth dataset examples. DiverseDepth dataset

BibTeX

@inproceedings{Yin2019enforcing,
  title={Enforcing geometric constraints of virtual normal for depth prediction},
  author={Yin, Wei and Liu, Yifan and Shen, Chunhua and Yan, Youliang},
  booktitle= {The IEEE International Conference on Computer Vision (ICCV)},
  year={2019}
}

@inproceedings{Wei2021CVPR,
  title     =  {Learning to Recover 3D Scene Shape from a Single Image},
  author    =  {Wei Yin and Jianming Zhang and Oliver Wang and Simon Niklaus and Long Mai and Simon Chen and Chunhua Shen},
  booktitle =  {Proc. IEEE Conf. Comp. Vis. Patt. Recogn. (CVPR)},
  year      =  {2021}
}

@article{yin2021virtual,
  title={Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Prediction},
  author={Yin, Wei and Liu, Yifan and Shen, Chunhua},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year={2021}
}

@article{yin2020diversedepth,
  title={DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data},
  author={Yin, Wei and Wang, Xinlong and Shen, Chunhua and Liu, Yifan and Tian, Zhi and Xu, Songcen and Sun, Changming and Renyin, Dou},
  journal={arXiv preprint arXiv:2002.00569},
  year={2020}
}

Contact

Wei Yin: [email protected]

License

The 3D Scene Shape code is under a non-commercial license from Adobe Research. See the LICENSE file for details.

Other depth prediction projects are licensed under the 2-clause BSD License - see the LICENSE file for details. For commercial use, please contact Chunhua Shen.

About

This repo contains the projects: 'Virtual Normal', 'DiverseDepth', and '3D Scene Shape'. They aim to solve the monocular depth estimation, 3D scene reconstruction from single image problems.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 93.2%
  • Jupyter Notebook 6.8%