i-WiViG is an interpretable window vision GNN that constrains nodes to disjoint local windows and applies learnable sparse attention to identify relevant subgraphs, delivering competitive performance on scene classification and regression with natural and remote-sensing images.
Graph infor- mation bottleneck for remote sensing segmentation
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IB-HFN introduces a dual-stream backbone with spatial information bottleneck fusion, local-global gating, and joint optimization to achieve superior structural and spectral fidelity in SAR-assisted optical cloud removal on the SEN12MS-CR dataset.
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i-WiViG: Interpretable Window Vision GNN
i-WiViG is an interpretable window vision GNN that constrains nodes to disjoint local windows and applies learnable sparse attention to identify relevant subgraphs, delivering competitive performance on scene classification and regression with natural and remote-sensing images.
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IB-HFN: Information Bottleneck-Driven SAR-Optical Fusion Network for High-Fidelity Cloud Removal
IB-HFN introduces a dual-stream backbone with spatial information bottleneck fusion, local-global gating, and joint optimization to achieve superior structural and spectral fidelity in SAR-assisted optical cloud removal on the SEN12MS-CR dataset.