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KSG-Net: Key-Sparse and Global-Context Learning for Maritime 3D Ship Detection

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Accurate 3D ship detection in maritime environments is critical for autonomous navigation, yet remains challenging due to large-scale vessel variations, sparse point clouds of small vessels, and severe sea-clutter interference. Existing methods, primarily based on 2D features or dense representations, struggle to balance detection accuracy and computational efficiency, while sparse 3D detectors designed for road scenes generalize poorly to maritime scenarios. This paper focuses on two key challenges in maritime LiDAR perception: weak feature representation for small and sparse vessels, and ins

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Evidence & attribution

First collected: 2026-09-21T05:51:54.566Z. This is not the publication date.