Abstract: Loop closure is an essential module in long-term SLAM, as detecting and recognizing re-visited locations serves to bound localization drift and correct for geometric map distortions. It also provides a mechanism to recover from track loss. However, most methods employ offline learnt maps that cannot be customized to the feature space of new environments. This work explores a means to generate a loop closing map with online adaptive properties.