InAction (ECCV 2022)

Implementation of the ECCV work "InAction" for interpretable driving behavior prediction.

Data

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• BDD-OIA
• PSI

Dependencies

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• Python 3.6
• Pytorch 1.1

Training

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Evaluation

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• Single-label Benchmarks (PSI)

Driving action prediction: Accuracy & Class-wise average accuracy

Explanation: F1 score & Class-wise average F1 score

• Multiple-label Benchmarks (BDD-OIA)

Driving action prediction: F1 score & Class-wise average F1 score

Explanation: F1 score & Class-wise average F1 score

Citation

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If you think this work is interesting, please cite:

Taotao Jing1, Haifeng Xia1, Renran Tian2, Haoran Ding2, Xiao Luo2, Joshua
Domeyer3, Rini Sherony3, and Zhengming Ding1

@InProceedings{Jing_2021_InAction,
author = {Jing, Taotao and Xia, Haifeng and Tian, Renran and Ding, Haoran and Luo, Xiao and Domeyer, Joshua and Sherony, Rini and Ding, Zhengming},
title = {InAction: Interpretable Action Decision Making for Autonomous Driving},
booktitle = {European conference on computer vision},
year = {2022}
}

Contact

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If you have any questions about this work, feel free to contact

• tjing@tulane.edu