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Alexandre Massoud Alahi

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Publications associées (121)

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STATNet: Spatial-temporal attention in the traffic prediction

Alexandre Massoud Alahi

Recent traffic flow prediction methods are lacking abilities to determine predictive features. Thus, they will propagate the error in the next timestamps. In this paper, first, we assess the role of spatial and temporal features on the traffic speed predic ...

2022

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

Alexandre Massoud Alahi

Understanding human motion behavior is critical for autonomous moving platforms (like self-driving cars and social robots) if they are to navigate human-centric environments. This is challenging because human motion is inherently multimodal: given a histor ...

2018

Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

Alexandre Massoud Alahi, Simon Elias Bibri, Amin Kaboli

The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to enhance and optimize the environmental performance and efficiency of smart c ...

Elsevier2023

A qualitative AI security risk assessment of autonomous vehicles

Alexandre Massoud Alahi, Kathrin Grosse

This paper systematically analyzes the security risks associated with artificial intelligence (AI) components in autonomous vehicles (AVs). Given the increasing reliance on AI for various AV functions, from perception to control, the potential for security ...

Elsevier BV2024

Stream Carving: an Adaptive Seam Carving Algorithm

Pierre Vandergheynst, Alexandre Massoud Alahi

We propose a new content-aware image resizing scheme, "Stream Carving", which is based on the well-known seam carving method. Our algorithm may introduce larger seams in the retargeted image, i.e. seams with a width larger than one pixel, that we call "str ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Vehicle trajectory prediction works, but not everywhere

Alexandre Massoud Alahi, Seyed Mohsen Moosavi Dezfooli, Saeed Saadatnejad, Mohammadhossein Bahari, Ahmad Rahimi

Vehicle trajectory prediction is nowadays a fundamental pillar of self-driving cars. Both the industry and research communities have acknowledged the need for such a pillar by providing public benchmarks. While state-of-the-art methods are impressive, i.e. ...

IEEE2022

From Bits to Images: Inversion of Local Binary Descriptors

Pierre Vandergheynst, Alexandre Massoud Alahi, Laurent Jacques, Emmanuel D'Angelo

Local Binary Descriptors are becoming more and more popular for image matching tasks, especially when going mobile. While they are extensively studied in this context, their ability to carry enough information in order to infer the original image is seldom ...

Institute of Electrical and Electronics Engineers2014

MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization

Alexandre Massoud Alahi, Sven Kreiss, Taylor Ferdinand Mordan, Lorenzo Bertoni

Monocular and stereo visions are cost-effective solutions for 3D human localization in the context of self-driving cars or social robots. However, they are usually developed independently and have their respective strengths and limitations. We propose a no ...

IEEE2021

Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression

Mathieu Salzmann, Alexandre Massoud Alahi, Megh Hiren Shukla

Deep heteroscedastic regression models the mean and covariance of the target distribution through neural networks. The challenge arises from heteroscedasticity, which implies that the covariance is sample dependent and is often unknown. Consequently, recen ...

ICLR2025

Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion

Alexandre Massoud Alahi, Taylor Ferdinand Mordan

Forecasting pedestrians' future motions is essential for autonomous driving systems to safely navigate in urban areas. However, existing prediction algorithms often overly rely on past observed trajectories and tend to fail around abrupt dynamic changes, s ...

2022

Pedestrian Intention Prediction: A Multi-task Perspective

Alexandre Massoud Alahi, Saeed Saadatnejad

In order to be globally deployed, autonomous cars must guarantee the safety of pedestrians. This is the reason why forecasting pedestrians' intentions sufficiently in advance is one of the most critical and challenging tasks for autonomous vehicles. This w ...

2020

SoccerNet 2023 challenges results

Alexandre Massoud Alahi

The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vision-based tasks split into three main themes. The first theme, broadcast vi ...

2024

Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness

Alexandre Massoud Alahi, Kathrin Grosse

This study aims to comprehensively explore the complexities of integrating Artificial Intelligence (AI) into Autonomous Vehicles (AVs), examining the challenges introduced by AI components and their impact on testing procedures. The research focuses on ess ...

2025

1(st) Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results

Alexandre Massoud Alahi, Alexandre Bernardino, Siddharth Gupta, Vladimir Dominic K. Somers

The 1st Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection ...

IEEE COMPUTER SOC2023

Pedestrian 3D Bounding Box Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yi Zhou Ju

Safety is still the main issue of autonomous driving, and in order to be globally deployed, they need to predict pedestrians' motions sufficiently in advance. While there is a lot of research on coarse-grained (human center prediction) and fine-grained pre ...

2022

Joint Human Pose Estimation and Stereo 3D Localization

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni, Wenlong Deng

We present an end-to-end trainable Neural Network architecture for stereo imaging that jointly locates and estimates human body poses in 3D. Our method defines a 2D pose for each human in a stereo pair of images and uses a correlation layer with a composit ...

IEEE2020

Non-intrusive physiological parameters sensing for personalized human thermal comfort prediction

Alexandre Massoud Alahi, Dolaana Khovalyg, Mohamad Rida, Mohamed Ossama Ahmed Abdelfattah

Sensing and projecting an individual’s human thermal comfort in buildings is a complex but crucial task for transitioning toward human-centered indoor climate control. Non-intrusive collection of physiological and personal information from the human body, ...

2023

NAT: Learning to Attack Neurons for Enhanced Adversarial Transferability

Alexandre Massoud Alahi, Krishna Kanth Nakka

The generation of transferable adversarial perturbations typically involves training a generator to maximize embedding separation between clean and adversarial images at a single mid-layer of a source model. In this work, we build on this approach and intr ...

IEEE2025

A Shared Representation for Photorealistic Driving Simulators

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan

A powerful simulator highly decreases the need for real-world tests when training and evaluating autonomous vehicles. Data-driven simulators flourished with the recent advancement of conditional Generative Adversarial Networks (cGANs), providing high-fidel ...

IEEE Institute of Electrical and Electronics Engineers2021

PifPaf: Composite Fields for Human Pose Estimation

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

We propose a new bottom-up method for multi-person 2D human pose estimation that is particularly well suited for urban mobility such as self-driving cars and delivery robots. The new method, PifPaf, uses a Part Intensity Field (PIF) to localize body parts ...

IEEE2019