Awesome
Exploring Dynamic Context for Multi-path Trajectory Prediction
DCENet Structure
Requiements
- python3
- keras-gpu 2.3.1
- tensorflow 2.1.0
- numpy ...
pip install -r requiements.txt
Data Preparation
- download raw data from directory /WORLD H-H TRAJ, and save in /processed_data
- run /scripts/trainer.py by setting arg.preprocess==True for data processing. Note: set arg.preprocess==False when you have already the processed data when you run /scripts/trainer.py to save time.
Test
You can get the results as reported in the paper using our pretrained model.
- Download pretrained model from /models/best.hdf5
Train
You also can train from sratch by /scripts/trainer.py
Bibtex
If you find our work useful for you, please cite it as:
@article{cheng2020exploring,
title={Exploring Dynamic Context for Multi-path Trajectory Prediction},
author={Cheng, Hao and Liao, Wentong and Tang, Xuejiao and Yang, Michael Ying and Sester, Monika and Rosenhahn, Bodo},
journal={arXiv preprint},
year={2020}
}