Yiwei Lin; Hu Chuan; Baixuan Zhao; Hao Jiang; Yonghang Shan; Taojun Ding; Xi Zhang*
This repo contains the code for our paper:Anchor-based Multi-modal Transformer Network for Pedestrian Trajectory and Intention Prediction. The paper is accepted by CVCI2023 conference.
The code is mainly based on bitrap implementation.
Our network architecture:
Usage:
- Download the dataset from JAAD official website.
- Clone the repo and install the requirements.
- Change the dataset path in configs/gtppo_tr_JAAD.yml
- Run the code:
python tools/train.py --config_file configs/gtppo_tr_JAAD.yml
# or
python tools/test.py --config_file configs/gtppo_tr_JAAD.yml --CKPT_DIR your_weights.pth
- if set VISUALIZATION: True and USE_WANDB: True in configs/gtppo_tr_JAAD.yml, the results will be visualized. ffmpeg and full dataset videos are required for visualization.