3 papers
cs.CV2026
TriBand-BEV: Real-Time LiDAR-Only 3D Pedestrian Detection via Height-Aware BEV and High-Resolution Feature Fusion
Mohammad Khoshkdahan, Alexey Vinel
Safe autonomous agents and mobile robots need fast real time 3D perception, especially for vulnerable road users (VRUs) such as pedestrians. We introduce a new bird's eye view (BEV…
cs.RO2026
Cooperative Robotics Reinforced by Collective Perception for Traffic Moderation
Mohammad Khoshkdahan, John Pravin Arockiasamy, Andy Flores Comeca +1
Collisions at non-line-of-sight (NLOS) intersections remain a major safety concern because drivers have limited visibility of approaching traffic. V2X based warnings can reduce the…
cs.CV2025
Beyond Overall Accuracy: Pose- and Occlusion-driven Fairness Analysis in Pedestrian Detection for Autonomous Driving
Mohammad Khoshkdahan, Arman Akbari, Arash Akbari +1
Pedestrian detection plays a critical role in autonomous driving (AD), where ensuring safety and reliability is important. While many detection models aim to reduce miss-rates and…