5 citations · 5 across the 13 of their papers we have counts for
5 papers · 1 filter
Dense Coverage, Sparse Refinement: Byte-Constrained Cooperative Perception
Melih Yazgan, Timon Müller, J. Marius Zöllner
Collaborative perception improves autonomous perception by sharing intermediate Bird's-Eye-View (BEV) features across connected agents, but dense feature exchange is difficult to d…
Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bank
Abhishek Vivekanandan, Ahmed Abouelazm, J. Marius Zöllner
Motion forecasting often requires trading interpretability for predictive accuracy. Standard anchor-based architectures rely on opaque latent queries that are highly prone to laten…
2.5D Object Detection for Intelligent Roadside Infrastructure
Nikolai Polley, Yacin Boualili, Ferdinand Mütsch +3
On-board sensors of autonomous vehicles can be obstructed, occluded, or limited by restricted fields of view, complicating downstream driving decisions. Intelligent roadside infras…
Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light Detectors
Svetlana Pavlitska, Jamie Robb, Nikolai Polley +2
Realistic adversarial attacks on various camera-based perception tasks of autonomous vehicles have been successfully demonstrated so far. However, only a few works considered attac…
Collaborative Perception Datasets in Autonomous Driving: A Survey
Melih Yazgan, Mythra Varun Akkanapragada, J. Marius Zoellner
This survey offers a comprehensive examination of collaborative perception datasets in the context of Vehicle-to-Infrastructure (V2I), Vehicle-to-Vehicle (V2V), and Vehicle-to-Ever…