October 8, 2025Open Access

Transformer Based Building Boundary Reconstruction using Attraction Field Maps

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The new approach improves building footprint accuracy and consistency, addressing traditional manual mapping challenges.
Modeling based on Graph Convolutional Networks demonstrates a significant 6% gain in Average Precision for footprint extraction.
Incorporating Attraction Field Maps allows for scalable solutions, utilizing multi-resolution satellite imagery effectively.
Enhanced automated methods pave the way for applications in disaster management and urban development efforts.

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Implication

Novel methodology demonstrates improved building footprint extraction in satellite imagery, indicating potential for urban planning and spatial analysis.

Cite This Study

Kamran et al. (2025) studied this question.

synapsesocial.com/papers/68e6494525bc5bdb98713b2e https://doi.org/10.48550/arxiv.2507.17038

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Implication

Novel methodology demonstrates improved building footprint extraction in satellite imagery, indicating potential for urban planning and spatial analysis.

Transformer Based Building Boundary Reconstruction using Attraction Field Maps

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Implication

Cite This Study

Transformer Based Building Boundary Reconstruction using Attraction Field Maps

Key Points

Discussion

Implication

Cite This Study

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