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Found 3 papers, 1 papers with code
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.
PolarNet: Accelerated Deep Open Space Segmentation Using Automotive Radar in Polar Domain
In this paper, we propose PolarNet, a deep neural model to process radar information in polar domain for open space segmentation.
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.
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