Deep Open Space Segmentation using Automotive Radar
In this work, we propose the use of radar with advanced deep segmentation models to identify open space in parking scenarios. A publically available dataset of radar observations called SCORP was collected. Deep models are evaluated with various radar input representations. Our proposed approach achieves low memory usage and real-time processing speeds, and is thus very well suited for embedded deployment.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
PolarNet: Accelerated Deep Open Space Segmentation Using Automotive Radar in Polar Domain
Camera and Lidar processing have been revolutionized with the rapid development of deep learning model architectures. Automotive radar is one of the crucial elements of automated driver assistance and autonomous driving …
Autonomous DrivingDecision MakingDAROD: A Deep Automotive Radar Object Detector on Range-Doppler maps
Due to the small number of raw data automotive radar datasets and the low resolution of such radar sensors, automotive radar object detection has been little explored with deep learning models in comparison to camera and…
2D Object DetectionObjectobject-detectionObject Detection+1ERASE-Net: Efficient Segmentation Networks for Automotive Radar Signals
Among various sensors for assisted and autonomous driving systems, automotive radar has been considered as a robust and low-cost solution even in adverse weather or lighting conditions. With the recent development of rad…
Autonomous DrivingSegmentationSemantic SegmentationMMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor Perception
Compared with an extensive list of automotive radar datasets that support autonomous driving, indoor radar datasets are scarce at a smaller scale in the format of low-resolution radar point clouds and usually under an op…
Autonomous Drivingenergy managementInstance Segmentationobject-detection+3Deep Instance Segmentation with Automotive Radar Detection Points
Automotive radar provides reliable environmental perception in all-weather conditions with affordable cost, but it hardly supplies semantic and geometry information due to the sparsity of radar detection points. With the…
Autonomous DrivingClusteringInstance SegmentationSegmentation+1