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English(EN) Physically Grounded Monocular Depth via Nanophotonic Wavefront Encoding

超透镜通过编码物理线索增强单目深度估计

研究人员开发了一种新颖的方法,通过将纳米光子超透镜与深度基础模型(DFM)集成,来改进计算机视觉中的单目深度估计。该方法物理编码了通常在单图像深度估计中缺失的度量深度线索,从而解决了尺度模糊问题。该系统将依赖于深度的位置偏移嵌入到偏振光波前中,并创建了一个仿真管线来弥合训练的仿真到真实世界的差距。 AI

影响 这项研究可能导致从单张图像中获得更准确、更符合物理规律的3D感知,从而影响机器人和增强现实等领域。

排序理由 该集群包含一篇详细介绍新研究方法和实验结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

超透镜通过编码物理线索增强单目深度估计

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该集群包含一篇详细介绍新研究方法和实验结果的学术论文。[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) · Bingxuan Li, Jiahao Wu, Yuan Xu, Zezheng Zhu, Yunxiang Zhang, Kenneth Chen, Yanqi Liang, Nanfang Yu, Qi Sun ·

    通过纳米光子波前编码实现物理约束的单目深度估计

    arXiv:2503.15770v3 Announce Type: replace-cross Abstract: Depth foundation models (DFMs) offer strong learned priors for 3D perception from single RGB images but lack physical depth cues, leading to ambiguities in metric scale. We introduce metalenses, an emerging class of ultrat…