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arXiv Computer Vision By Zhouyuan Huai, Meiqi Wan, Yan Yang, Minshi Chen, Xin Yuan, Wei Wang, Xiao Wang

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

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KSG‑Net introduces a Key‑Sparse and Global‑Context learning framework for maritime 3D ship detection, addressing weak feature representation of small, sparse vessels and limited global modeling of large vessels. The network employs a Key Sparse Multi‑scale Aggregation module to select informative voxels and aggregate cross‑scale features, and a Global Context Aggregation module to capture long‑range geometric dependencies via scene‑level context modeling. Experiments on the Thames River vessel dataset and simulated data show that KSG‑Net outperforms existing methods in multi‑scale vessel detection and remains robust in complex maritime environments.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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