IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertainty

Official implementation of the paper

IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertainty
BMVC 2022
Gwangbin Bae, Ignas Budvytis, and Roberto Cipolla
[arXiv] [demo] [project page]

Summary

• We use surface normal to propagate depth between pixels.
• We formulate depth refinement/upsampling as classification of choosing the neighboring pixel to propagate from.

Getting Started

We recommend using a virtual environment.

python3.6 -m venv --system-site-packages ./venv
source ./venv/bin/activate

Install the necessary dependencies by

python3.6 -m pip install -r requirements.txt

Go to this google drive, and

• Download *.pt and place them under ./checkpoints.
• Download and unzip examples.zip as ./examples.

Testing

# test on scannet images, using the model trained on scannet
python test.py --train_data scannet --test_data scannet

# test on nyuv2 images, using the model trained on nyuv2
python test.py --train_data nyuv2 --test_data nyuv2

# test on your own images, using the model trained on scannet
python test.py --train_data scannet --test_data custom

• This generates output visualizations under ./examples/output/dataset_name/.
• Comment out unnecessary visualization scripts to speed things up.
• When testing on your own images, you should place the images under ./examples/data/custom/. We support .png and .jpg files. If you wish to provide the camera intrinsics, add a file named img_name.txt. The file should contain fx, fy, cx and cy. See ./examples/data/custom/ex01.txt as an example.

Citation

If you find our work useful in your research please consider citing our papers:

@InProceedings{Bae2022,
    title   = {IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertainty}
    author  = {Gwangbin Bae and Ignas Budvytis and Roberto Cipolla},
    booktitle = {British Machine Vision Conference (BMVC)},
    year = {2022}                         
}

@InProceedings{Bae2021,
    title   = {Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation}
    author  = {Gwangbin Bae and Ignas Budvytis and Roberto Cipolla},
    booktitle = {International Conference on Computer Vision (ICCV)},
    year = {2021}                         
}