English(EN) LiG-DETR: Local-in-Global Reassembly in Latent Space for Aerial Object Detection

LiG-DETR框架通过集成局部-全局特征增强航空目标检测

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-08 04:00

研究人员推出了一种新颖的LiG-DETR框架，旨在通过解决尺度和密度变化的挑战来改进航空目标检测。该方法将图像切片重新构建为高保真局部特征获取，从而能够在单一端到端检测框架内集成局部和全局特征。该方法旨在提高小目标的检测能力，同时保持对大目标的性能，提供改进的准确性-效率权衡和跨域泛化能力。 AI

影响这项研究可能带来更准确、更高效的航空监视和分析系统。

排序理由这是一篇详细介绍目标检测新技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.CV TIER_1 English(EN) · Yupeng Zhang, Fangzhuo Gao, Juntao Cheng, Ziyi Zhao, Liang Wan, Ruize Han · 2026-10-08 04:00

LiG-DETR：空中目标检测的潜在空间中的局部-全局重组

arXiv:2610.09511v1 Announce Type: new Abstract: Aerial object detection faces substantial scale and density variations. Small objects are easily degraded by downsampling and feature compression, while medium and large objects require sufficient global context. Existing methods ma…