Changer: Feature Interaction is What You Need for Change Detection

Change detection is an important tool for long-term earth observation missions. It takes bi-temporal images as input and predicts “where” the change has occurred. Different from other dense prediction tasks, a meaningful consideration for change detection is the interaction between bi-temporal features. With this motivation, in this paper we propose a novel general change detection architecture, MetaChanger, which includes a series of alternative interaction layers in the feature extractor. To verify the effectiveness of MetaChanger, we propose two derived models, ChangerAD and ChangerEx with simple interaction strategies: Aggregation-Distribution (AD) and feature “exchange”. AD is abstracted from some complex…

• NN
  National Natural Science Foundation of China

  Award: 42276185
• NS
  Natural Science Foundation of Shandong Province

  Awards: ZR2020MF132, ZR2022MF325