AOPDet: Automatic Organized Points Detector for Precisely Localizing Objects in Aerial Imagery
Published in IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022
This paper proposes AOPDet, with the core contribution of proposing a non sequential corner representation method as a novel rotation target representation, designing an automatic organization mechanism to guide the model to learn target corners, and designing a dedicated detection head structure. Improved 17.0 mAP compared to baseline on the publicly available aerial dataset, reaching SOTA level.
Recommended citation:
Z. Zhu, X. Sun, W. Diao, K. Chen, G. Xu and K. Fu, "AOPDet: Automatic Organized Points Detector for Precisely Localizing Objects in Aerial Imagery," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022, Art no. 5606816, doi: 10.1109/TGRS.2021.3093557.
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