English(EN) RS-JEPA: Remote Sensing Joint-Embedding Predictive Architecture with Scan-Path Views for Cross-Sensor Image Retrieval

RS-JEPA框架改进了跨传感器遥感图像检索

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-11 05:00

研究人员开发了RS-JEPA，一种用于跨传感器遥感图像检索的新型自监督学习框架。该方法利用Vision Mamba编码器，并引入“扫描路径视图”来从可见图像块预测隐藏的图像块，从而提高检索精度。与以前的方法相比，RS-JEPA在多个基准测试中取得了最先进的性能，并且参数数量大大减少。 AI

影响这项研究推进了图像检索的自监督学习技术，有望改进遥感和跨传感器数据分析中的应用。

排序理由该集群包含一篇详细介绍新模型架构和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Tanishq Rachamalla, Srishti Kaushik, Muhammad Attique Khan, Gustau Camps-Valls, Swalpa Kumar Roy · 2026-11-11 05:00

RS-JEPA：具有扫描路径视图的遥感联合嵌入预测架构，用于跨传感器图像检索

arXiv:2611.14496v1 Announce Type: new Abstract: Cross-sensor remote sensing image retrieval aims to find scenes with the same content across heterogeneous sensors, such as SAR and optical or panchromatic (PAN) and multispectral (MS) imagery, without manual labels. Existing self-s…