AI RESEARCH
FAF-CD: Frequency-Aware Fusion for Change Detection under Imperfect Multimodal Remote Sensing
arXiv CS.CV
•
ArXi:2606.03114v1 Announce Type: new Remote sensing change detection for real-world monitoring often relies on imperfect heterogeneous observations, where pre- and post-event images may be asynchronous, cross-sensor, or affected by illumination, seasonal, and modality shifts. This setting is especially challenging for EO-SAR disaster mapping, where nuisance variation can resemble structural damage. We propose FAF-CD, a frequency-aware hybrid framework with a DINOv3-pretrained ConvNeXt encoder and a linear-complexity VMamba-based decoder.