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v2x-graph's Introduction

Learning Cooperative Trajectory Representations for Motion Forecasting

Hongzhi Ruan, Haibao Yu, Wenxian Yang, Siqi Fan, Yingjuan Tang, Zaiqing Nie

Paper

Introduction

This is the project repository for V2X-Graph and V2X-Traj.

V2X-Graph is the first interpretable and end-to-end learning framework for cooperative motion forecasting. It is a SOTA method on V2X-Seq.

V2X-Traj is the first real-world vehicle-to-everything (V2X) motion forecasting dataset.

The code and data will be released once the paper is accepted.

Citation

Please use the following citation if you find our repo or our paper useful:

@article{ruan2023learning,
title={Learning Cooperative Trajectory Representations for Motion Forecasting}, 
author={Hongzhi Ruan and Haibao Yu and Wenxian Yang and Siqi Fan and Yingjuan Tang and Zaiqing Nie},
journal={arXiv preprint arXiv:2311.00371},
year={2023},
}

v2x-graph's People

Contributors

hzrynn avatar haibao-yu avatar

Stargazers

 avatar Ruiyang Hao avatar catonetwo avatar Tang chengchen avatar  avatar  avatar  avatar Zewei Zhou avatar Ehsan Ahmadi avatar Xuanlin Zeng avatar  avatar Jifeng Wang avatar HONGYU OUYANG avatar Steve Mao avatar WenxianYang avatar  avatar

Watchers

Li Bin avatar  avatar

Forkers

hzrynn

v2x-graph's Issues

about experiment set

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您好,很棒的工作,有一些细节想要了解一下,请问论文中PPVIC和V2X-Graph测试是在50000协同数据中的自车下测试的吗?PP-VIC在V2X-graph中的效果要比在V2X-seq效果好很多,是更改了什么设置吗?还是只是将V2X-seq中的CBMOT融合数据上的测试换成了协同数据中的自车下测试效果就会变好吗?

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