GET-UP

Pytorch implementation of GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsampling (Accepted by WACV 2025)

Paper link: https://arxiv.org/abs/2409.02720

Models have been tested using Python 3.7/3.8, Pytorch 1.10.1+cu111

Setting up dataset

To set up the dataset, please refer to the CaFNet repo.

Training GET-UP

To train GET-UP on the nuScenes dataset, you may run:

python main.py arguments_train_nuscenes.txt

Download trained model

You can download the model weights from the link: model.

After downloading the model, put the file into the folder 'saved_models'. Then it is able to evaluate the model.

Evaluating GET-UP

To evaluate GET-UP on the nuScenes dataset, you may run:

python main_test.py arguments_test_nuscenes.txt

You may replace the path dirs in the arguments files.

Acknowledgement

Our work builds on and uses code from radar-camera-fusion-depth, bts. We'd like to thank the authors for making these libraries and frameworks available.

Citation

If you use this work, please cite our paper:

@misc{getup,
      title={GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsampling}, 
      author={Huawei Sun and Zixu Wang and Hao Feng and Julius Ott and Lorenzo Servadei and Robert Wille},
      year={2024},
      eprint={2409.02720},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2409.02720}, 
}