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".

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}
}
Owner
VITA lab at EPFL
Visual Intelligence for Transportation
VITA lab at EPFL
Final report with code for KAIST Course KSE 801.

Orthogonal collocation is a method for the numerical solution of partial differential equations

Chuanbo HUA 4 Apr 06, 2022
This is a simple backtesting framework to help you test your crypto currency trading. It includes a way to download and store historical crypto data and to execute a trading strategy.

You can use this simple crypto backtesting script to ensure your trading strategy is successful Minimal setup required and works well with static TP a

Andrei 154 Sep 12, 2022
A CV toolkit for my papers.

PyTorch-Encoding created by Hang Zhang Documentation Please visit the Docs for detail instructions of installation and usage. Please visit the link to

Hang Zhang 2k Jan 04, 2023
Implementation of "A MLP-like Architecture for Dense Prediction"

A MLP-like Architecture for Dense Prediction (arXiv) Updates (22/07/2021) Initial release. Model Zoo We provide CycleMLP models pretrained on ImageNet

Shoufa Chen 244 Dec 27, 2022
[CVPR22] Official codebase of Semantic Segmentation by Early Region Proxy.

RegionProxy Figure 2. Performance vs. GFLOPs on ADE20K val split. Semantic Segmentation by Early Region Proxy Yifan Zhang, Bo Pang, Cewu Lu CVPR 2022

Yifan 54 Nov 29, 2022
Source code for deep symbolic optimization.

Update July 10, 2021: This repository now supports an additional symbolic optimization task: learning symbolic policies for reinforcement learning. Th

Brenden Petersen 290 Dec 25, 2022
Object recognition using Azure Custom Vision AI and Azure Functions

Step by Step on how to create an object recognition model using Custom Vision, export the model and run the model in an Azure Function

El Bruno 11 Jul 08, 2022
Artstation-Artistic-face-HQ Dataset (AAHQ)

Artstation-Artistic-face-HQ Dataset (AAHQ) Artstation-Artistic-face-HQ (AAHQ) is a high-quality image dataset of artistic-face images. It is proposed

onion 105 Dec 16, 2022
Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration

This repo is for the paper: Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration The DAC environment is based on the Dynam

Carola Doerr 1 Aug 19, 2022
Implementation of GGB color space

GGB Color Space This package is implementation of GGB color space from Development of a Robust Algorithm for Detection of Nuclei and Classification of

Resha Dwika Hefni Al-Fahsi 2 Oct 06, 2021
Official repo for BMVC2021 paper ASFormer: Transformer for Action Segmentation

ASFormer: Transformer for Action Segmentation This repo provides training & inference code for BMVC 2021 paper: ASFormer: Transformer for Action Segme

42 Dec 23, 2022
Self-training for Few-shot Transfer Across Extreme Task Differences

Self-training for Few-shot Transfer Across Extreme Task Differences (STARTUP) Introduction This repo contains the official implementation of the follo

Cheng Perng Phoo 33 Oct 31, 2022
Face Recognition plus identification simply and fast | Python

PyFaceDetection Face Recognition plus identification simply and fast Ubuntu Setup sudo pip3 install numpy sudo pip3 install cmake sudo pip3 install dl

Peyman Majidi Moein 16 Sep 22, 2022
This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework

neon_course This repository contains several jupyter notebooks to help users learn to use neon, our deep learning framework. For more information, see

Nervana 92 Jan 03, 2023
Collision risk estimation using stochastic motion models

collision_risk_estimation Collision risk estimation using stochastic motion models. This is a new approach, based on stochastic models, to predict the

Unmesh 7 Jun 26, 2022
shufflev2-yolov5:lighter, faster and easier to deploy

shufflev2-yolov5: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size

pogg 1.5k Jan 05, 2023
Malmo Collaborative AI Challenge - Team Pig Catcher

The Malmo Collaborative AI Challenge - Team Pig Catcher Approach The challenge involves 2 agents who can either cooperate or defect. The optimal polic

Kai Arulkumaran 66 Jun 29, 2022
Simple tutorials using Google's TensorFlow Framework

TensorFlow-Tutorials Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of Newmu's Theano Tutorial

Nathan Lintz 6k Jan 06, 2023
CVPR '21: In the light of feature distributions: Moment matching for Neural Style Transfer

In the light of feature distributions: Moment matching for Neural Style Transfer (CVPR 2021) This repository provides code to recreate results present

Nikolai Kalischek 49 Oct 13, 2022
Stacked Generative Adversarial Networks

Stacked Generative Adversarial Networks This repository contains code for the paper "Stacked Generative Adversarial Networks", CVPR 2017. Part of the

Xun Huang 241 May 07, 2022