smkim7-kr / DeepAccident

Code for the benchmark - DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving.

DeepAccident

The official implementation of the paper DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving.

Installation

Please check installation for installation and data_preparation for preparing the nuScenes dataset.

Getting Started

Please check getting_started for training, evaluation, and visualization of DeepAccident.

Task Visualization

Task Visualization.

V2XFormer for perception & prediction

Acknowledgement

This project is mainly based on the following open-sourced projects: BEVerse, Fiery, open-mmlab.

Bibtex

If this work is helpful for your research, please consider citing the following BibTeX entry.

@article{Wang_2023_DeepAccident,
  title = {DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving},
  author = {Wang, Tianqi and Kim, Sukmin and Ji, Wenxuan and Xie, Enze and Ge, Chongjian and Chen, Junsong and Li, Zhenguo and Ping, Luo},
  journal = {arXiv preprint arXiv:2304.01168},
  year = {2023}
}