CDXFormer: Boosting Remote Sensing Change Detection with Extended Long Short-Term Memory

• URL: http://arxiv.org/abs/2411.07863v2
• Date: Sat, 21 Dec 2024 03:10:42 GMT
• Title: CDXFormer: Boosting Remote Sensing Change Detection with Extended Long Short-Term Memory
• Authors: Zhenkai Wu, Xiaowen Ma, Rongrong Lian, Kai Zheng, Wei Zhang,
• Abstract summary: In this paper, we propose CDXFormer, with a core component that is a powerful XLSTM-based feature enhancement layer. We introduce a scale-specific Feature Enhancer layer, incorporating a Cross-Temporal Global Perceptron customized for semantic-accurate deep features. We also propose a Cross-Scale Interactive Fusion module to progressively interact global change representations with spatial responses.
• Score: 7.926250735066206
• License:
• Abstract: In complex scenes and varied conditions, effectively integrating spatial-temporal context is crucial for accurately identifying changes. However, current RS-CD methods lack a balanced consideration of performance and efficiency. CNNs lack global context, Transformers are computationally expensive, and Mambas face CUDA dependence and local correlation loss. In this paper, we propose CDXFormer, with a core component that is a powerful XLSTM-based feature enhancement layer, integrating the advantages of linear computational complexity, global context perception, and strong interpret-ability. Specifically, we introduce a scale-specific Feature Enhancer layer, incorporating a Cross-Temporal Global Perceptron customized for semantic-accurate deep features, and a Cross-Temporal Spatial Refiner customized for detail-rich shallow features. Additionally, we propose a Cross-Scale Interactive Fusion module to progressively interact global change representations with spatial responses. Extensive experimental results demonstrate that CDXFormer achieves state-of-the-art performance across three benchmark datasets, offering a compelling balance between efficiency and accuracy. Code is available at https://github.com/xwmaxwma/rschange.

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