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Advanced Interaction-aware Motion Models for Motorcycle Trajectory Prediction: Experiments on pNEUMA Datasets
Related publications (35)
Social-Transmotion: Promptable Human Trajectory Prediction
Alexandre Massoud Alahi, Yang Gao, Kaouther Messaoud Ben Amor, Saeed Saadatnejad
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 ...
2024From Prediction to Prevention: Leveraging Deep Learning in Traffic Accident Prediction Systems
We propose a novel system leveraging deep learning-based methods to predict urban traffic accidents and estimate their severity. The major challenge is the data imbalance problem in traffic accident prediction. The problem is caused by numerous zero values ...
Basel2023A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods
Michaël Unser, Pakshal Narendra Bohra
We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023Spatially adaptive machine learning models for predicting water quality in Hong Kong
Rongrong Li, Qiaoli Wang, Yu Xu
Water quality prediction in the spatially heterogeneous environment is challenging as the importance of water quality parameters (WQPs) and the performance of prediction models may vary across space. Thus, this study proposed spatially adaptive machine lea ...
ELSEVIER2023Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices
The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...
EPFL2023Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI
Purpose: To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-enco ...
Hoboken2023Manipulating Trajectory Prediction with Backdoors
Alexandre Massoud Alahi, Kaouther Messaoud Ben Amor, Kathrin Grosse
Autonomous vehicles ought to predict the surrounding agents' trajectories to allow safe maneuvers in uncertain and complex traffic situations. As companies increasingly apply trajectory prediction in the real world, security becomes a relevant concern. In ...
arXiv2023Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion
Alexandre Massoud Alahi, Taylor Ferdinand Mordan, Dongxu Guo
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 ...
2022Multivariate time series forecasting for freeway networks
This dissertation introduces traffic forecasting methods for different network configurations and data availability.Chapter 2 focuses on single freeway cases.Although its topology is simple, the non-linearity of traffic features makes this prediction still ...
EPFL2022Encoder-Decoder Models for Human Segmentation and Motion Analysis
Detecting people from 2D images and analyzing their motion in 3D have been long standing computer vision problems central to numerous applications such as autonomous driving and athletic training. Recently, with the availability of large amounts of trainin ...
EPFL2022