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English(EN) HistReNeRF: Historic Image Relocalisation within Contemporary Neural Radiance Field Reconstructions

HistReNeRF框架在3D场景中重新定位历史照片

研究人员开发了HistReNeRF,一个新颖的框架,旨在将历史照片准确地重新定位到当代3D场景重建中。该方法解决了历史和现代图像在外观、物体和空间布局上的差异带来的挑战。通过适配DINOv2补丁特征并查询神经辐射场(NeRF)重建,HistReNeRF可以估计历史照片的6-DoF位姿。在新欧洲地标数据集上的评估表明,这种嵌入空间适配将平移和旋转误差平均分别降低了11%和16%,优于像素空间方法。 AI

影响 增强了历史照片分析和3D场景重建能力。

排序理由 该项目是一篇在arXiv上发表的研究论文,详细介绍了一种新的图像重新定位方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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HistReNeRF框架在3D场景中重新定位历史照片

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该项目是一篇在arXiv上发表的研究论文,详细介绍了一种新的图像重新定位方法。[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) · Benjamin T. Hughes, Stuart James ·

    HistReNeRF:在当代神经辐射场重建中进行历史图像重定位

    arXiv:2608.15420v1 Announce Type: new Abstract: Relocalising archival photographs within a contemporary scene model is challenging because historic and modern views can differ in photographic appearance, visible objects, and spatial layout. Therefore, we present HistReNeRF, a fra…