DELTAR: Depth Estimation from a Light-weight ToF Sensor And RGB Image

Project Page | Paper

DELTAR: Depth Estimation from a Light-weight ToF Sensor And RGB Image
Yijin Li, Xinyang Liu, Wenqi Dong, Han Zhou, Hujun Bao, Guofeng Zhang, Yinda Zhang, Zhaopeng Cui
ECCV 2022

Download Link

We provide the download link [google drive, baidu(code: 1i11)] to

• pretrained model trained on NYU.
• ZJUL5 dataset.
• demo data.

Run DELTAR

Installation

conda create --name deltar --file requirements.txt

Prepare the data and pretrained model

Download from the above link, and place the data and model as below:

deltar
├── data
│   ├── demo
│   └── ZJUL5
└── weights
    └── nyu.pt

Evaluate on ZJUL5 dataset

python evaluate.py configs/test_zjuL5.txt

Run the demo

python evaluate.py configs/test_demo.txt
python scripts/make_gif.py --data_folder data/demo/room --pred_folder tmp/room

Citation

If you find this code useful for your research, please use the following BibTeX entry.

@article{deltar,
  title={DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image},
  author={Li Yijin and Liu Xinyang and Dong Wenqi and Zhou han and Bao Hujun and Zhang Guofeng and Zhang Yinda and Cui Zhaopeng},
  booktitle={European Conference on Computer Vision (ECCV)},
  year={2022}
}

Acknowledgements

We would like to thank the authors of Adabins, LoFTR and Twins for open-sourcing their projects.