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.
Self-constructing graph neural networks to model long-range pixel dependencies for semantic segmen- tation of remote sensing images
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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.