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Siamese networks are widely used for remote sensing change detection tasks. Avanilla siamese network has two identical feature extraction branches whichshare weights, these two branches work independently and the feature maps arenot fused until about to be sent to a decoder head. However we find that it iscritical to exchange information between two feature extraction branches atearly stage for change detection task. In this work we present Mutual-AttentionSiamese Network (MASNet), a general siamese network with mutual-attentionplug-in, so to exchange information between the two feature extractionbranches. We show that our modification improve the performance of siamesenetworks on multi change detection datasets, and it works for bothconvolutional neural network and visual transformer.

MASNet:Improve Performance of Siamese Networks with Mutual-attention for Remote Sensing Change Detection Tasks