S-attack library. Official implementation of two papers "Are socially-aware trajectory prediction models really socially-aware?" and "Vehicle trajectory prediction works, but not everywhere".

Related tags

Deep Learning deep-learning human-behavior-understanding robustness adversarial-attacks human-trajectory-prediction vehicle-trajectory-prediction
Overview

S-attack library:
A library for evaluating trajectory prediction models

This library contains two research projects to assess the trajectory prediction models, Social-attack which evaluates social understanding of models, and Scene-attack which evaluates the scene-understanding of them.

Are socially-aware trajectory prediction models really socially-aware?
S. Saadatnejad, M. Bahari, P. Khorsandi, M. Saneian, S. Dezfooli, A. Alahi, arxiv 2021
Website                 Paper                 Citation

Vehicle trajectory prediction works, but not everywhere
M. Bahari, S. Saadatnejad, A. Rahimi, M. Shaverdikondori, S. Dezfooli, A. Alahi, arxiv 2021
Website                 Paper                 Citation

Social-attack

Are socially-aware trajectory prediction models really socially-aware?

The official code for the paper: "Are socially-aware trajectory prediction models really socially-aware?", Webpage, arXiv

 

Installation:

Start by cloning this repository:

git clone https://github.com/vita-epfl/s-attack
cd s-attack

And install the dependencies:

pip install .

For more info on the installation, please refer to Trajnet++

Dataset:

  • We used the trajnet++ dataset. For easy usage, we put data in DATA_BLOCK folder.

Training/Testing:

In order to attack the LSTM-based models (S-lstm, S-att, D-pool):

bash lrun.sh

In order to attack the GAN-based models:

bash grun.sh

Scene-attack

Vehicle trajectory prediction works, but not everywhere

The official code for the paper: "Vehicle trajectory prediction works, but not everywhere", Webpage, arXiv

 

Code will be released soon!

For citation:

@article{saadatnejad2021sattack,
  title={Are socially-aware trajectory prediction models really socially-aware?},
  author={Saadatnejad, Saeed and Bahari, Mohammadhossein and Khorsandi, Pedram and Saneian, Mohammad and Moosavi-Dezfooli, Seyed-Mohsen and Alahi, Alexandre},
  year={2021}, eprint={2108.10879}, archivePrefix={arXiv}, primaryClass={cs.CV}
}
@article{bahari2021sattack,
  title={Vehicle trajectory prediction works, but not everywhere},
  author={Bahari, Mohammadhossein and Saadatnejad, Saeed and Rahimi, Ahmad and Shaverdikondori, Mohammad and Moosavi-Dezfooli, Seyed-Mohsen and Alahi, Alexandre},
  year={2021}, eprint={2112.03909}, archivePrefix={arXiv}, primaryClass={cs.CV}
}
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Comments
  • PECNet and STG-CNN

    PECNet and STG-CNN

    Dear authors,

    I've noticed there is no option in your code to test S-Attack on PECNet and STG-CNN, two methods for which you provide adversarial attack results in your paper. I was wondering if you were planning on making your code for these two available, or if there's some way to install the dependencies separately ourselves.

    Thank you, Erica

    opened by ericaweng 2
  • Permutations on STGCNN and PECNet

    Permutations on STGCNN and PECNet

    Hi, great work! Can you provide the permutation trajectories obtained from PECNet and STGCNN publicly or privately if their code option cannot be released easily? I hope I can use them to do quick collision tests on other models. Thanks.

    opened by HRHLALALA 1
  • How to realise visualization in evaluator files

    How to realise visualization in evaluator files

    Hello, your article on pedestrian prediction has inspired me a lot. After debugging the code, I want to find out how to visualize the final result, because only a few data can be seen in the debugging process, and I don't know the implementation process. If you like, can you explain to me in detail how to do the visualization part？

    opened by Cxx0822 1
Owner
VITA lab at EPFL
Visual Intelligence for Transportation
VITA lab at EPFL
GitHub
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