@unpublished{corley2024a,
author = {Corley, Isaac and Robinson, Caleb and Ortiz, Anthony},
title = {A Change Detection Reality Check},
year = {2024},
month = {February},
abstract = {In recent years, there has been an explosion of proposed change detection deep learning architectures in the remote sensing literature. These approaches claim to offer state-of the-art performance on different standard benchmark datasets. However, has the field truly made significant progress? In this paper we perform experiments which conclude a simple U-Net segmentation baseline without training tricks or complicated architectural changes is still a top performer for the task of change detection.},
url = {http://approjects.co.za/?big=en-us/research/publication/a-change-detection-reality-check/},
}