<ul><li>Feature-based image matching has extensive applications in computer vision. In this paper, an innovative adaptive graph construction method is introduced for image matching. The method dynamically adjusts the criteria for incorporating new vertices based on the characteristics of existing vertices, allowing for more precise and robust graph structures. The vertex processing capabilities of Graph Neural Networks (GNNs) are combined with Transformers to enhance the model's representation of spatial and feature information. The system achieves significant improvements in overall matching performance.</li></ul>

GIMS: Image Matching System Based on Adaptive Graph Construction and Graph Neural Network

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