  In this paper, we present a deep learning-based network, GCNv2, for
generation of keypoints and descriptors. GCNv2 is built on our previous method,
GCN, a network trained for 3D projective geometry. GCNv2 is designed with a
binary descriptor vector as the ORB feature so that it can easily replace ORB
in systems such as ORB-SLAM2. GCNv2 significantly improves the computational
efficiency over GCN that was only able to run on desktop hardware. We show how
a modified version of ORB-SLAM2 using GCNv2 features runs on a Jetson TX2, an
embedded low-power platform. Experimental results show that GCNv2 retains
comparable accuracy as GCN and that it is robust enough to use for control of a
flying drone.
