Align and Complete Samples in Remote Sensing Fine-Grained Rigid Object Detection
Published in IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2025
This paper proposes the ACDet rigid object fine-grained detector, which has the following core contributions: 1) adaptive anchor point alignment, decoupling classification centripetal deviation to achieve adaptive alignment; 2) Online tail sample supplementation algorithm to dynamically maintain category balance; 3) Adaptive grouping enhances discriminative features. Achieve SOTA with fewer resources.
Recommended citation:
Z. Zhu, J. Kang, W. Diao, B. Wang and J. Ni, "Align and Complete Samples in Remote Sensing Fine-Grained Rigid Object Detection," in IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1-17, 2025, Art no. 5655617, doi: 10.1109/TGRS.2025.3635340.
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