FAF-CD is a frequency-aware hybrid neural framework using ConvNeXt encoder, VMamba decoder, and tri-branch fusion with Fourier/Haar comparisons for robust change detection in imperfect multimodal remote sensing data.
NeXt2Former-CD: Efficient Remote Sensing Change Detection with Modern Vision Architectures, 2026
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FAF-CD: Frequency-Aware Fusion for Change Detection under Imperfect Multimodal Remote Sensing
FAF-CD is a frequency-aware hybrid neural framework using ConvNeXt encoder, VMamba decoder, and tri-branch fusion with Fourier/Haar comparisons for robust change detection in imperfect multimodal remote sensing data.