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Point Cloud based Hierarchical Deep Odometry Estimation
Processing point clouds using deep neural networks is still a challenging task.
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.
How much real data do we actually need: Analyzing object detection performance using synthetic and real data
In this paper, we take a comprehensive look into the effects of replacing real data with synthetic data.
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