DIAMONDNET: SHIP DETECTION IN REMOTE SENSING IMAGES BY EXTRACTING AND CLUSTERING KEYPOINTS IN A DIAMOND
Published in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2024
This paper proposes a ship detection framework based on keypoint extraction: the ship is characterized by five keypoints (center, head and tail, left and right midpoints) distributed in a diamond shape, and a clustering algorithm based on geometric features is designed to aggregate the keypoints. Flexible export of horizontal or rotated boxes to achieve SOTA on two datasets.
Recommended citation:
Z. Zhu, W. Diao, K. Chen, L. Zhao, Z. Yan, W. Zhang, G. Xu and X. Sun, "DiamondNet: Ship Detection in Remote Sensing Images by Extracting and Clustering Keypoints in a Diamond," ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. V-2-2020, pp. 625-632, 2020, doi: 10.5194/isprs-annals-V-2-2020-625-2020.
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