Towards deep radar perception for autonomous driving: Datasets, methods, and challenges
With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …
The next generation of 4D radar can achieve imaging capability in the form of high …
Automotive radar signal processing: Research directions and practical challenges
F Engels, P Heidenreich… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Automotive radar is used in many applications of advanced driver assistance systems and is
considered as one of the key technologies for highly automated driving. An overview of state …
considered as one of the key technologies for highly automated driving. An overview of state …
Multi-class road user detection with 3+ 1D radar in the View-of-Delft dataset
Next-generation automotive radars provide elevation data in addition to range-, azimuth-and
Doppler velocity. In this experimental study, we apply a state-of-the-art object detector …
Doppler velocity. In this experimental study, we apply a state-of-the-art object detector …
Raw high-definition radar for multi-task learning
With their robustness to adverse weather conditions and ability to measure speeds, radar
sensors have been part of the automotive landscape for more than two decades. Recent …
sensors have been part of the automotive landscape for more than two decades. Recent …
RODNet: A real-time radar object detection network cross-supervised by camera-radar fused object 3D localization
Various autonomous or assisted driving strategies have been facilitated through the
accurate and reliable perception of the environment around a vehicle. Among the commonly …
accurate and reliable perception of the environment around a vehicle. Among the commonly …
RadarScenes: A real-world radar point cloud data set for automotive applications
A new automotive radar data set with measurements and point-wise annotations from more
than four hours of driving is presented. Data provided by four series radar sensors mounted …
than four hours of driving is presented. Data provided by four series radar sensors mounted …
Multi-object detection and tracking, based on DNN, for autonomous vehicles: A review
R Ravindran, MJ Santora, MM Jamali - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Multi-object detection and multi-object-tracking in diverse driving situations is the main
challenge in autonomous vehicles. Vehicle manufacturers and research organizations are …
challenge in autonomous vehicles. Vehicle manufacturers and research organizations are …
SMURF: Spatial multi-representation fusion for 3D object detection with 4D imaging radar
The 4D millimeter-Wave (mmWave) radar is a promising technology for vehicle sensing due
to its cost-effectiveness and operability in adverse weather conditions. However, the …
to its cost-effectiveness and operability in adverse weather conditions. However, the …
Radar-camera fusion for object detection and semantic segmentation in autonomous driving: A comprehensive review
Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …
Flow: A dataset and benchmark for floating waste detection in inland waters
Marine debris is severely threatening the marine lives and causing sustained pollution to the
whole ecosystem. To prevent the wastes from getting into the ocean, it is helpful to clean up …
whole ecosystem. To prevent the wastes from getting into the ocean, it is helpful to clean up …