Guangwu Chen

MAIG-Net: Unsupervised Remote Sensing Road Extraction Combining Multi-Layer Adversarial Learning and Intermediate Domain Guidance

MAIG-Net combines a target-label-free ground-sampling-distance rule, an intermediate domain constructed by Fourier domain adaptation (FDA) that transfers only low-frequency target appearance onto labeled source images while preserving the complete source phase and road labels, and Domain-Invariant Feature Alignment modules that perform reliability-weighted, topology-conditioned adversarial alignment at three encoder depths.