High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving. Most previous works try to solve it using anchor-based detection methods which come with two drawbacks: post-processing is relatively complex and computationally expensive; tuning anchor parameters is tricky. We are the first to address these drawbacks with an anchor free and Non-Maximum Suppression free one stage detector called AFDet. The entire AFDet can be processed efficiently on a CNN accelerator or a GPU with the simplified post-processing. Without bells and whistles, our proposed AFDet performs competitively with other one stage anchor-based methods on KITTI validation set and Waymo Open Dataset validation set.

翻译：在嵌入系统中操作的高效点云 3D 物体探测对包括自主驾驶在内的许多机器人应用非常重要。 以往的多数工作都试图使用基于锚的探测方法来解决它,这些方法有两个缺点:后处理相对复杂,而且计算成本很高; 调控锚参数很棘手。 我们是第一个用一个无锚和非氧化抑制的舞台探测器(AFDet)来解决这些缺陷的。 整个AFDet 可以通过有线电视新闻网的加速器或带有简化后处理的GPU 来有效处理。 没有钟声和哨子,我们提议的AFDet 在KITTI验证器和Waymo Open数据集验证器上与其他一种基于级的定位方法竞争。