Official repository of "LiDAR-based All-weather 3D Object Detection via Prompting and Distilling 4D Radar", ECCV2024. [Paper]
The code has been tested with
- python 3.8
- CUDA 11.1
- pytorch 1.10.1
- spconv-cu111 2.1.25
- open3d 0.15.2
- opencv-python 4.8.1.78
- matplotlib 3.5.3
- numba 0.53.0
- nms 0.1.6
https://drive.google.com/drive/folders/13JRwnTY_cupN13-gwpXWlfIsLmIAIaRZ?usp=sharing
# Train
python main_train_0.py
# Test
python main_cond_0.py
# Train
python main_train_student.py
# Test
python main_cond_student.py
If you find our work helpful, please consider citing our paper:
@inproceedings{Chae_2024_ECCV,
title={LiDAR-Based All-Weather 3D Object Detection via Prompting and Distilling 4D Radar},
author={Chae, Yujeong and Kim, Hyeonseong and Oh, Changgyoon and Kim, Minseok and Yoon, Kuk-Jin},
booktitle={European Conference on Computer Vision},
pages={368--385},
year={2024},
organization={Springer}
}
This work is developed based on the K-Radar dataset and codebase.