论文标题
使用汽车雷达深度开放空间分割
Deep Open Space Segmentation using Automotive Radar
论文作者
论文摘要
在这项工作中，我们建议将雷达与先进的深层分割模型一起使用，以识别停车场景中的开放空间。收集了一个公开可用的雷达观测数据集，称为Scorp。深层模型通过各种雷达输入表示。我们提出的方法可实现低内存使用量和实时处理速度，因此非常适合嵌入式部署。
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.
