Invariant Structure Representation for Remote Sensing Object Detection Based on Graph Modeling
Published in IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022
This paper proposes GFA Net, with the core contribution of systematically studying the invariant structural features of remote sensing targets, proposing an implicit modeling of target structural features based on graph convolution in the graph focusing process, and designing a graph aggregation network to achieve end-to-end efficient training. The effectiveness of the SOTA method has been validated on mainstream open-source datasets.
Recommended citation:
Z. Zhu, X. Sun, W. Diao, K. Chen, G. Xu and K. Fu, "Invariant Structure Representation for Remote Sensing Object Detection Based on Graph Modeling," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-17, 2022, Art no. 5625217, doi: 10.1109/TGRS.2022.3181686.
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