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eess.IV2020
Deep Snow: Synthesizing Remote Sensing Imagery with Generative Adversarial Nets
Christopher X. Ren, Amanda Ziemann, James Theiler +1
In this work we demonstrate that generative adversarial networks (GANs) can be used to generate realistic pervasive changes in remote sensing imagery, even in an unpaired training…
eess.IV2019
Cycle-Consistent Adversarial Networks for Realistic Pervasive Change Generation in Remote Sensing Imagery
Christopher X. Ren, Amanda Ziemann, Alice M. S. Durieux +1
This paper introduces a new method of generating realistic pervasive changes in the context of evaluating the effectiveness of change detection algorithms in controlled settings. T…