Detecting and localizing Mars craters is important for several planetary science endeavors. Until now, the automatic detection of craters from images has been attempted by using generic deep learning object detectors, which require large amounts of annotated examples, generally unavailable. In this project, we will develop unsupervised approaches to crater detection that avoid the need for manual labeling, thus enabling the direct use of the most important and complete datasets of Mars images.