32 citations · 32 across the 8 of their papers we have counts for
8 papers
Polycepta: Object-Centric Appearance Estimation for Multi-Object Tracking
Mohamed Nagy, Naoufel Werghi, Jorge Dias +1
The tracking-by-detection paradigm in multi-object tracking (MOT) typically relies on static appearance descriptors to complement motion estimation. However, these descriptors are…
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…
EagleVision: A Multi-Task Benchmark for Cross-Domain Perception in High-Speed Autonomous Racing
Zakhar Yagudin, Murad Mebrahtu, Ren Jin +5
High-speed autonomous racing presents extreme perception challenges, including large relative velocities and substantial domain shifts from conventional urban-driving datasets. Exi…
Visual Prompt Based Reasoning for Offroad Mapping using Multimodal LLMs
Abdelmoamen Nasser, Yousef Baba'a, Murad Mebrahtu +3
Traditional approaches to off-road autonomy rely on separate models for terrain classification, height estimation, and quantifying slip or slope conditions. Utilizing several model…
Collaborative Last-Mile Delivery: A Multi-Platform Vehicle Routing Problem With En-route Charging
Sumbal Malik, Majid Khonji, Khaled Elbassioni +1
The rapid growth of e-commerce and the increasing demand for timely, cost-effective last-mile delivery have increased interest in collaborative logistics. This research introduces…
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…