3 papers
cs.CV2021
Raw High-Definition Radar for Multi-Task Learning
Julien Rebut, Arthur Ouaknine, Waqas Malik +1
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 progre…
cs.CV2021
PolarNet: Accelerated Deep Open Space Segmentation Using Automotive Radar in Polar Domain
Farzan Erlik Nowruzi, Dhanvin Kolhatkar, Prince Kapoor +5
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 d…
eess.SP2020
Deep Open Space Segmentation using Automotive Radar
Farzan Erlik Nowruzi, Dhanvin Kolhatkar, Prince Kapoor +5
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 c…