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English(EN) GeoSearch: Augmenting Worldwide Geolocalization with Web-Scale Reverse Image Search and Image Matching

GeoSearch框架利用网络规模反向图像搜索进行全球地理定位

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了GeoSearch，一个旨在通过将网络规模反向图像搜索集成到检索增强生成（RAG）管道中来改进全球图像地理定位的新框架。该方法通过向大型多模态模型（LMMs）提供网页中的坐标和文本数据来增强它们，解决了固定数据库的局限性。GeoSearch采用两层过滤系统来管理不相关内容，并在Im2GPS3k和YFCC4k等基准测试中表现出色。 AI

影响 通过将网络规模搜索与LMMs集成，增强了地理定位能力，可能改进了位置感知AI应用。

排序理由 详细介绍图像地理定位新框架的学术论文。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

GeoSearch框架利用网络规模反向图像搜索进行全球地理定位

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Research
详细介绍图像地理定位新框架的学术论文。
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Topics
paper, other
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170 days old
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Tung-Duong Le-Duc, Hoang-Quoc Nguyen-Son, Minh-Son Dao ·

    GeoSearch：通过网络规模反向图像搜索和图像匹配增强全球地理定位

    arXiv:2604.25390v1 Announce Type: cross Abstract: Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity. Recent generative approaches based on Retrieval-Augmented Generation (RAG) and L…

  2. arXiv cs.CV TIER_1 English(EN) · Minh-Son Dao ·

    GeoSearch：通过网络规模反向图像搜索和图像匹配增强全球地理定位

    Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity. Recent generative approaches based on Retrieval-Augmented Generation (RAG) and Large Multimodal Models (LMMs) leverage candidates …

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