LiM-YOLO: Less is More with Pyramid Level Shift for Ship Detection in Optical Remote Sensing 文章

ArXiv CS.CV2026-05-27NEWSen作者: Seon-Hoon Kim, Yerin Kim, Hyeji Sim, Youeyun Jung, Okchul Jung, Daewon Chung

摘要

arXiv:2512.09700v3 Announce Type: replace Abstract: General-purpose object detectors face fundamental structural limitations when applied to ship detection in satellite imagery, where the ship scale distribution is concentrated at small sizes and high aspect ratios. In conventional You Only Look Once architectures, the deepest feature pyramid level (stride 32) compresses narrow vessels into sub-pixel representations, causing severe spatial feature dilution and compromising accurate ship boundary regression. We propose Less is More YOLO, a streamlined detector built upon the extra-large variant of YOLOv9, to address these domain-specific structural conflicts. From a statistical analysis of ship scale distributions across four major benchmarks (SODA-A, DOTA-v1.5, FAIR1M-v2.0, and ShipRSImageNet), we introduce a Pyramid Level Shift Strategy that shifts the detection head from strides 8, 16, and 32 to strides 4, 8, and 16.