Alexandre Massoud Alahi

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Introduction REM sleep behavior disorder (RBD) poses a high risk of injury to patients and bed partners, yet symptomatic treatments are limited and clinical trials lack objective, quantifiable endpoints. We evaluated whether AI-driven computer-vision models could automatically detect injury-risk behaviors in a large, well-characterized cohort of patients with isolated RBD undergoing video-polysomnography (vPSG). Methods Motor events during REM sleep were automatically detected by optical flow on vPSG from 6

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 ...

Rock cuttings from destructive boreholes are a common and cheaper source of drilling materials that can be used to determine underground geology compared to rock core samples. Classifying manually the series of cuttings can be a long and tedious process an ...

A major challenge in the common approach of hot water generation in residential houses lies in the highly stochastic nature of domestic hot water (DHW) demand. Learning hot water use behavior enables water heating systems to continuously adapt to the stoch ...

Modeling spatial-temporal interactions among neighboring agents is at the heart of multi-agent problems such as motion forecasting and crowd navigation. Despite notable progress, it remains unclear to which extent modern representations can capture the cau ...

Existing vehicle trajectory prediction models struggle with generalizability, prediction uncertainties, and handling complex interactions. It is often due to limitations like complex architectures customized for a specific dataset and inefficient multimoda ...

Conditioning image generation facilitates seamless editing and the creation of photorealistic images. However, conditioning on noisy or Out-of-Distribution (OoD) images poses significant challenges, particularly in balancing fidelity to the input and realism of the output. We introduce Confident Ordinary Differential Editing (CODE), a novel approach for image synthesis that effectively handles OoD guidance images. Utilizing a diffusion model as a generative prior, CODE enhances images through score-based up

Drones are nowadays considered as a valuable solution to monitor urban traffic. Object detectors face numerous challenges when dealing with high-resolution aerial images captured by drones, due to variations in altitude, viewing angle, and weather conditio ...

Early and frequent patient mobilization substantially mitigates risk for post-intensive care syndrome and long-term functional impairment. We developed and tested computer vision algorithms to detect patient mobilization activities occurring in an adult IC ...

We propose Stable Video Infinity (SVI) that can generate non-looping, ultra-long videos with stable visual quality, while supporting per-clip prompt control and multi-modal conditioning. While existing long-video methods attempt to mitigate accumulated errors via handcrafted anti-drifting (e.g., modified noise scheduler, frame anchoring), they remain limited to single-prompt extrapolation, producing homogeneous scenes with repetitive motions. We identify that the fundamental challenge extends beyond error a

Most of the multi-camera systems assume a well structured environment to detect and match objects across cameras. Cameras need to be fixed and calibrated. In this work, a novel system is presented to detect and match any objects in a network of uncalibrate ...

Human beings are interested in understanding their environments and the dynamic content that fills their surroundings. For applications ranging from security to marketing, people have installed networks of cameras to capture the dynamic elements of scenes. ...

Accurate human trajectory prediction is one of the most crucial tasks for autonomous driving, ensuring its safety. Yet, existing models often fail to fully leverage the visual cues that humans subconsciously communicate when navigating the space. In this w ...

Scalable Vector Graphics (SVG) are ubiquitous in modern 2D interfaces due to their ability to scale to different resolutions. However, despite the success of deep learning-based models applied to rasterized images, the problem of vector graphics representa ...

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 ...

Local Binary Descriptors (LBDs) are good at matching image parts, but how much information is actually carried? Surprisingly, this question is usually ignored and replaced by a comparison of matching performances. In this paper, we directly address it by t ...

The ability to predict pedestrian behaviour is crucial for road safety, traffic management systems, Advanced Driver Assistance Systems (ADAS), and more broadly autonomous vehicles. We present a vision-based system that simultaneously locates where pedestri ...

This work tackles the challenge of detecting and matching objects in scenes observed simultaneously by fixed and mobile cameras. No calibration between the cameras is needed, and no training data is used. A fully automated system is presented to detect if an object, observed by a fixed camera, is seen by a mobile camera and where it is localized in its image plane. Only the observations from the fixed camera are used. An object descriptor based on grids of region descriptors is used in a cascade manner. Fix

Objective: Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is, in most cases, an early stage of Parkinson's disease or related disorders. Diagnosis requires an overnight video-polysomnogram (vPSG), however, even for sleep experts, interpre ...

The standard practice in Generative Adversarial Networks (GANs) discards the discriminator during sampling. However, this sampling method loses valuable information learned by the discriminator regarding the data distribution. In this work, we propose a co ...

Alexandre Massoud Alahi

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1172 Training Artificial Intelligence Models to Assess Injury Risk in REM Sleep Behavior Disorder

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

X-ray Micro-CT based characterization of rock cuttings with deep learning

Adaptive hot water production based on Supervised Learning

Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations

Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting

CODE: Confident Ordinary Differential Editing

Traffic perception from aerial images using butterfly fields

A computer vision system for deep learning-based detection of patient mobilization activities in the ICU

Stable Video Infinity: Infinite-Length Video Generation with Error Recycling

Cascade of Descriptors to Detect and Track Objects Across Any Network of Cameras

Vision-Based Scene Understanding with Sparsity Promoting Priors

Social-Pose: Enhancing Trajectory Prediction with Human Body Pose

DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation

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

Beyond Bits: Reconstructing Images from Local Binary Descriptors

Pedestrian intention prediction: A convolutional bottom-up multi-task approach

Object Detection and Matching in a Mixed Network of Fixed and Mobile Cameras

Automated Detection of Isolated REM Sleep Behavior Disorder Using Computer Vision

Collaborative Sampling in Generative Adversarial Networks