S-attack library:
A library for evaluating trajectory prediction models
This library contains two research projects to assess the trajectory prediction models, Scene-attack which evaluates the scene-understanding of models and Social-attack which evaluates social understanding of them.
Vehicle trajectory prediction works, but not everywhere, CVPR 2022
M. Bahari, S. Saadatnejad, A. Rahimi, M. Shaverdikondori, A. Shahidzadeh, S. Moosavi-Dezfooli, A. Alahi
Website         Paper         Citation         Code
Are socially-aware trajectory prediction models really socially-aware?, TR_C 2022
S. Saadatnejad, M. Bahari, P. Khorsandi, M. Saneian, S. Moosavi-Dezfooli, A. Alahi
Website         Paper         Citation         Code
For citation:
@InProceedings{bahari2022sattack,
author = {Bahari, Mohammadhossein and Saadatnejad, Saeed and Rahimi, Ahmad and Shaverdikondori, Mohammad and Shahidzadeh, Amir-Hossein and Moosavi-Dezfooli, Seyed-Mohsen and Alahi, Alexandre},
title = {Vehicle trajectory prediction works, but not everywhere},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2022},
}
@article{saadatnejad2022sattack,
author = {Saeed Saadatnejad and Mohammadhossein Bahari and Pedram Khorsandi and Mohammad Saneian and Seyed-Mohsen Moosavi-Dezfooli and Alexandre Alahi},
title = {Are socially-aware trajectory prediction models really socially-aware?},
journal = {Transportation Research Part C: Emerging Technologies},
volume = {141},
pages = {103705},
year = {2022},
issn = {0968-090X},
doi = {https://doi.org/10.1016/j.trc.2022.103705},
}