SELF-SUPERVISED LEARNING FOR MONOCULAR DEPTH ESTIMATION FROM AERIAL IMAGERY

Supervised learning based methods for monocular depth estimation usually require large amounts of extensively annotated training data. In the case of aerial imagery, this ground truth is particularly difficult to acquire. Therefore, in this paper, we present a method for self-supervised learning for...

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Bibliographic Details
Main Authors: M. Hermann, B. Ruf, M. Weinmann, S. Hinz
Format: Article
Language:English
Published: Copernicus Publications 2020-08-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2020/357/2020/isprs-annals-V-2-2020-357-2020.pdf