  In this paper we propose a real-time, calibration-agnostic and effective
localization system for self-driving cars. Our method learns to embed the
online LiDAR sweeps and intensity map into a joint deep embedding space.
Localization is then conducted through an efficient convolutional matching
between the embeddings. Our full system can operate in real-time at 15Hz while
achieving centimeter level accuracy across different LiDAR sensors and
environments. Our experiments illustrate the performance of the proposed
approach over a large-scale dataset consisting of over 4000km of driving.
