Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection
A novel 3D object detection framework that processes LiDAR data directly on its native representation: range images. To overcome scale sensitivity in this perspective view, a range-conditioned dilation (RCD) layer is proposed to dynamically adjust a continuous dilation rate as a function of the measured range. Unparalleled performance is achieved at long range detection when combined with a second stage refinement.