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English(EN) DiCoR: Decoupled Referent Disambiguation and Contour Recalibration for Efficient Referring Remote Sensing Image Segmentation

DiCoR框架提升遥感图像分割的准确性和效率

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了DiCoR，一个用于指代遥感图像分割的新框架，旨在提高准确性和效率。DiCoR解决了区分正确指代对象和模糊候选对象以及精炼分割掩码的挑战。该框架包含一个具有消歧意识的定位引导策略和一个轻量级的轮廓重校准模块。在多个基准数据集上的实验表明，DiCoR在保持性能和计算成本之间良好平衡的同时，实现了卓越的分割准确性。 AI

影响 引入了一种新颖的方法来提高遥感图像分割任务的准确性和效率。

排序理由 这是一篇详细介绍新图像分割框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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DiCoR框架提升遥感图像分割的准确性和效率

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这是一篇详细介绍新图像分割框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Ziyang Gao, Zhizhuo Jiang, Jingjing Chang, Yixin Yang, Yuwen Pan, Yong-Qiang Mao, Yu Liu, Hai-Bao Chen ·

    DiCoR：解耦的指代消歧和轮廓重新校准，用于高效的指代遥感图像分割

    arXiv:2608.12980v1 Announce Type: new Abstract: Referring remote sensing image segmentation (RRSIS) aims to delineate targets specified by natural language expressions in remote sensing imagery. Existing methods mainly follow joint fusion segmentation (JFS) or decoupled prompt se…

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