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Alexandre Massoud Alahi

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Publications associées (121)

JRDB-Traj: A Dataset and Benchmark for Trajectory Forecasting in Crowds

Alexandre Massoud Alahi, Saeed Saadatnejad, Yang Gao

Predicting future trajectories is critical in autonomous driving, especially in preventing accidents involving humans, where a predictive agent’s ability to anticipate in advance is of utmost importance. Trajectory forecasting models, employed in fields su ...

2024

Towards more Practical Threat Models in Artificial Intelligence Security

Alexandre Massoud Alahi, Kathrin Grosse

Recent works have identified a gap between research and practice in artificial intelligence security: threats studied in academia do not always reflect the practical use and security risks of AI. For example, while models are often studied in isolation, th ...

Usenix Association2024

Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?

Alexandre Massoud Alahi

Motion forecasting is crucial in enabling autonomous vehicles to anticipate the future trajectories of surrounding agents. To do so, it requires solving mapping, detection, tracking, and then forecasting problems, in a multi-step pipeline. In this complex ...

2024

When Your AI Becomes a Target: AI Security Incidents and Best Practices

Alexandre Massoud Alahi, Kathrin Grosse

In contrast to vast academic efforts to study AI security, few real-world reports of AI security incidents exist. Released incidents prevent a thorough investigation of the attackers' motives, as crucial information about the company and AI application is ...

AAAI Press2024

Toward Reliable Human Pose Forecasting With Uncertainty

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan, Parham Saremi

Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

2024

Social-Transmotion: Promptable Human Trajectory Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yang Gao, Kaouther Messaoud Ben Amor

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

2024

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

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning

Alexandre Massoud Alahi, Ting Zhang

Prediction is a vital component of motion planning for autonomous vehicles (AVs). By reasoning about the possible behavior of other target agents, the ego vehicle (EV) can navigate safely, efficiently, and politely. However, most of the existing work overl ...

IEEE Institute of Electrical and Electronics Engineers2024

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Alexandre Massoud Alahi, Mariam Ahmed Mahmoud Hegazy Hassan, Mohamed Ossama Ahmed Abdelfattah

Current transformer-based skeletal action recognition models tend to focus on a limited set of joints and low-level motion patterns to predict action classes. This results in significant performance degradation under small skeleton perturbations or changin ...

2024

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

MPL: Lifting 3D Human Pose from Multi-view 2D Poses

Alexandre Massoud Alahi

Estimating 3D human poses from 2D images is challenging due to occlusions and projective acquisition. Learning-based approaches have been largely studied to address this challenge, both in single and multi-view setups. These solutions however fail to gener ...

Springer Science and Business Media Deutschland GmbH2024

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Mathieu Salzmann, Alexandre Massoud Alahi, Megh Hiren Shukla

Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

2024

Predicting the long-term collective behaviour of fish pairs with deep learning

Francesco Mondada, Alexandre Massoud Alahi, Vaios Papaspyros

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

2024

Real-Time Localization for Closed-Loop Control of Assistive Furniture

Auke Ijspeert, Alexandre Massoud Alahi, George Adaimi, Chuanfang Ning, Lixuan Tang, Anastasia Bolotnikova

For people with limited mobility, navigating in cluttered indoor environment is challenging. In this work, we propose a mobile assistive furniture suite that is designed to ease the life of people with special needs in indoor movement. To enable intelligen ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Urban Digital Twin Challenges: A Systematic Review and Perspectives for Sustainable Smart Cities

François Golay, Alexandre Massoud Alahi, Régis Longchamp, Charlotte Gisèle Weil, Simon Elias Bibri

Recent scientific and technological advancements have transformed the knowledge frontiers, giving rise to the next wave of disruptive technologies with deep impacts on urban society. An Urban Digital Twin (UDT) is a technology with great potential to trans ...

ELSEVIER2023

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

Alexandre Massoud Alahi, Amin Kaboli, Simon Elias Bibri

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

Composite Relationship Fields with Transformers for Scene Graph Generation

Alexandre Massoud Alahi, George Adaimi, David Mizrahi

Scene graph generation (SGG) methods extract relationships between objects. While most methods focus on improving top-down approaches, which build a scene graph based on detected objects from an off-the-shelf object detector, there is a limited amount of w ...

Los Alamitos2023

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

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

The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

2023

Training Traffic Light Behavior with End-to-End Learning

Alexandre Massoud Alahi

In this work, we study neural network architectures that will reduce the number of infractions made by autonomous-driving agents. These agents control vehicles by providing future waypoints directly from a forward-facing camera. Building on top of the teac ...

Springer2023

On Pitfalls of Test-time Adaptation

Alexandre Massoud Alahi, Yuejiang Liu, Tao Lin, Hao Zhao

2023

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