title: In-Domain Representation Learning For Remote Sensing
abstract: Given the importance of remote sensing, surprisingly little attention has been paid to it by the representation learning community. To address it and to speed up innovation in this domain, we provide simplified access to 5 diverse remote sensing datasets in a standardized form. We specifically explore in-domain representation learning and address the question of "what characteristics should a dataset have to be a good source for remote sensing representation learning". The established baselines achieve state-of-the-art performance on these datasets. 
  
authors: Maxim Neumann Andre Susano Pinto Xiaohua Zhai Neil Houlsby
hIndex: Neil Houlsby 28