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New MariSat dataset targets maritime object segmentation in satellite imagery

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced MariSat, a new dataset designed for instance segmentation of maritime objects in satellite and aerial imagery. The dataset comprises 1260 images annotated at the pixel level for eight distinct maritime object classes. MariSat was developed using a semi-automatic pipeline that combined the Segment Anything Model 3 (SAM 3) with post-processing filters and manual quality control via the CVAT platform. This new resource has already been utilized to fine-tune and benchmark models like SAM 3 and YOLOv11 for real-time maritime surveillance. AI

IMPACT Enhances capabilities for maritime surveillance and object detection in satellite imagery.

RANK_REASON The cluster describes the release of a new academic dataset for computer vision research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New MariSat dataset targets maritime object segmentation in satellite imagery

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The cluster describes the release of a new academic dataset for computer vision research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Amir Abbes, Ines Harrabi, Lucas Justin Yirepoa Kinda, Rim Trabelsi, Adnane Cabani, Fatma Abdelkefi ·

    MariSat: A Maritime Dataset for Instance Segmentation of Objects in Satellite and Aerial Images

    arXiv:2608.29852v1 Announce Type: new Abstract: Automated maritime surveillance from satellite and aerial imagery requires large, precisely annotated datasets, which remain scarce for the instance-segmentation task, particularly for small vessels in cluttered port environments. W…

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