8 papers · 1 filter
Temporal Residual Bottleneck for Robust Asynchronous Collaborative Perception
Melih Yazgan, Ahmed Abouelazm, J. Marius Zöllner
Collaborative perception extends the sensing range of autonomous vehicles, but its performance degrades when shared features arrive stale or incomplete. Most latency-robust methods…
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…
4D Radar Meets LiDAR and Camera: Cooperative Perception under Adverse Weather
Melih Yazgan, Iramm Hamdard, Qiyuan Wu +1
Cooperative perception is important for autonomous driving but remains fragile when cameras and LiDAR degrade in adverse weather. We address this challenge by integrating 4D imagin…
SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perception
Melih Yazgan, Qiyuan Wu, Iramm Hamdard +2
Collaborative perception allows connected autonomous vehicles (CAVs) to overcome occlusion and limited sensor range by sharing intermediate features. Yet transmitting dense Bird's-…
EffiComm: Bandwidth Efficient Multi Agent Communication
Melih Yazgan, Allen Xavier Arasan, J. Marius Zöllner
Collaborative perception allows connected vehicles to exchange sensor information and overcome each vehicle's blind spots. Yet transmitting raw point clouds or full feature maps ov…
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…
A Survey on Intermediate Fusion Methods for Collaborative Perception Categorized by Real World Challenges
Melih Yazgan, Thomas Graf, Min Liu +2
This survey analyzes intermediate fusion methods in collaborative perception for autonomous driving, categorized by real-world challenges. We examine various methods, detailing the…
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…