  We introduce a simple yet effective fusion method of LiDAR and RGB data to
segment LiDAR point clouds. Utilizing the dense native range representation of
a LiDAR sensor and the setup calibration, we establish point correspondences
between the two input modalities. Subsequently, we are able to warp and fuse
the features from one domain into the other. Therefore, we can jointly exploit
information from both data sources within one single network. To show the merit
of our method, we extend SqueezeSeg, a point cloud segmentation network, with
an RGB feature branch and fuse it into the original structure. Our extension
called FuseSeg leads to an improvement of up to 18% IoU on the KITTI benchmark.
In addition to the improved accuracy, we also achieve real-time performance at
50 fps, five times as fast as the KITTI LiDAR data recording speed.
