English(EN) GeoISF: Instance Semantic Forest Inspired Large-Scale Cross-View Geo-Localization via Ground LiDAR-to-Satellite Image

GeoISF 管道提高了 LiDAR 到卫星地理定位的准确性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-30 04:00

研究人员开发了 GeoISF，一种使用地面 LiDAR 点云和卫星图像进行大规模跨视图地理定位的新型管道。该方法通过构建实例语义森林来解决语义对齐和模态差距相关的挑战，该森林整合了来自多个帧的语义树，以增强时间表示和判别能力。GeoISF 通过使用环境语义作为共享媒介，有效地弥合了模态差距，从而提高了匹配精度，并在 KITTI 等数据集上显著优于现有方法。 AI

影响这项研究通过在大规模环境中实现更精确的定位，有可能改进自主导航和地理空间分析。

排序理由该集群包含一篇详细介绍新方法和基准测试结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Di Hu, Xia Yuan, Chunxia Zhao · 2026-06-30 04:00

GeoISF：受实例语义森林启发的、通过地面LiDAR到卫星图像实现的大规模跨视图地理定位

arXiv:2606.28371v1 Announce Type: new Abstract: The problem of localization on a large-scale satellite image given a frame of query ground view point clouds remains challenging. Existing LiDAR-to-image cross-view localization methods struggle in large-scale scenarios due to limit…

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报道来源 [1]

GeoISF：受实例语义森林启发的、通过地面LiDAR到卫星图像实现的大规模跨视图地理定位

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