32 citations · 40 across the 5 of their papers we have counts for
5 papers
Collaborative Trajectory Prediction via Late Fusion
Nadya Abdel Madjid, Murad Mebrahtu, Zakhar Yagudin +5
Predicting future trajectories of surrounding traffic agents is critical for safe autonomous navigation and collision avoidance. Despite all advances in the trajectory forecasting…
Towards Accurate State Estimation: Motion Dynamics Kalman Filter for 3D Multi-Object Tracking
Mohamed Nagy, Naoufel Werghi, Bilal Hassan +2
Robust 3D state estimation in multi-object tracking is crucial for object localization in self-driving vehicles. Misalignment between the Kalman filter (KF) motion model and an obj…
Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directions
Nadya Abdel Madjid, Abdulrahman Ahmad, Murad Mebrahtu +7
As the potential for autonomous vehicles to be integrated on a large scale into modern traffic systems continues to grow, ensuring safe navigation in dynamic environments is crucia…
EMT: A Visual Multi-Task Benchmark Dataset for Autonomous Driving
Nadya Abdel Madjid, Murad Mebrahtu, Abdulrahman Ahmad +5
This paper introduces the Emirates Multi-Task (EMT) dataset, designed to support multi-task benchmarking within a unified framework. It comprises over 30,000 frames from a dash-cam…
RobMOT: Robust 3D Multi-Object Tracking by Observational Noise and State Estimation Drift Mitigation on LiDAR PointCloud
Mohamed Nagy, Naoufel Werghi, Bilal Hassan +2
This paper addresses limitations in 3D tracking-by-detection methods, particularly in identifying legitimate trajectories and reducing state estimation drift in Kalman filters. Exi…