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English(EN) Image Guided Depth Upsampling using Anisotropic Total Generalized Variation

新方法使用各向异性扩散增强深度图像上采样

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新的深度图像上采样方法，该技术可提高Kinect和飞行时间传感器等现代相机捕获的深度数据的分辨率。该方法将一个凸优化问题形式化，该问题利用来自高分辨率强度图像的各向异性扩散张量来指导上采样过程。该方法通过并行化的原对偶算法实现，可实现实时性能，并在速度和准确性方面均优于现有的最先进方法，在中部数据集2007上得到了证明。 AI

影响 这项研究可能为机器人和增强现实等领域的更准确、更高效的深度传感应用带来突破。

排序理由 该条目描述了一种新颖的深度图像上采样方法，该方法在研究论文中提出。[lever_c_demoted from research: ic=1 ai=0.7]

在 Hugging Face Daily Papers 阅读 →

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新方法使用各向异性扩散增强深度图像上采样

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该条目描述了一种新颖的深度图像上采样方法，该方法在研究论文中提出。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Image Guided Depth Upsampling using Anisotropic Total Generalized Variation

    In this work we present a novel method for the challenging problem of depth image upsampling. Modern depth cameras such as Kinect or Time of Flight cameras deliver dense, high quality depth measurements but are limited in their lateral resolution. To overcome this limitation we f…

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