Official implementation of "RVMDE : Radar Validated Monocular Depth Estimation for Robotics", https://arxiv.org/abs/2109.05265v1.
- Python >= 3.7 (Recommend to use Anaconda or Miniconda)
- PyTorch >= 1.9
-
Clone repo
git clone https://github.com/MI-Hussain/RVMDE
-
Install dependent packages
pypardiso
tensorboardX
nuscenes-devkitDownload nuScenes dataset (Full dataset (v1.0)) into data/nuscenes/
rvmde/
data/
nuscenes/
annotations/
maps/
samples/
sweeps/
v1.0-trainval/
dataloader/
list/
result/
model/
Please follow external repos (https://github.com/lochenchou/DORN_radar) for Height Extension and (https://github.com/longyunf/rc-pda) for RVMDE with MER's to generte the dataset for training and evaluation.
Download pre-trained weights
Modifying dataset path in valid_loader.py, evalutation list path in data_loader.py, pretrained_weights path in Evalutation_rvmde.py file to evalute.
For evaluation of day,night,rain change the list path first. The evaluation lists are saved in .\list directory.
Evaluation_rvmde.ipynb #EvaluationPlease visit this work (https://github.com/longyunf/rc-pda) for detail information of data prepration of training and evaluation sets.
Download pre-trained RVMDE with MERs weights
Evaluation_RVMDE_with_MERS.ipynb #Evaluation@Article{hussain2021rvmde,
title={RVMDE : Radar Validated Monocular Depth Estimation for Robotics},
author={Muhammad Ishfaq Hussain, Muhammad Aasim Rafique and Moongu Jeon},
journal={arXiv:2109.05265v1},
year={2021}
}
The following works have been used by RVMDE:
@InProceedings{Long_2021_CVPR,
author = {Long, Yunfei and Morris, Daniel and Liu, Xiaoming and Castro, Marcos and Chakravarty, Punarjay and Narayanan, Praveen},
title = {Radar-Camera Pixel Depth Association for Depth Completion},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2021},
pages = {12507-12516}
}
@INPROCEEDINGS{9506550,
author={Lo, Chen-Chou and Vandewalle, Patrick},
booktitle={2021 IEEE International Conference on Image Processing (ICIP)},
title={Depth Estimation From Monocular Images And Sparse Radar Using Deep Ordinal Regression Network},
year={2021},
pages={3343-3347},
doi={10.1109/ICIP42928.2021.9506550}
}
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent