Mask-based Change Detection Network for Accurate Identification of Changed Objects in Remote Sensing Imagery

The proposed MaskCD framework introduces a novel paradigm shift from per-pixel classification to mask classification for change detection in remote sensing imagery. It leverages a cross-level change representation perceiver and a masked attention-based detection transformer decoder to accurately locate and identify changed objects.