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English(EN) PIE-PS: Photometric Stereo from Physical Irradiance Event Streams

新框架从事件相机数据中重建表面法线

研究人员开发了PIE-PS,一个用于从事件相机数据重建表面法线的新颖框架。该方法利用物理辐照度事件(PIEs),这些事件源自像素处的相邻事件及其相关的光方向。PIE-PS框架利用图神经网络(PIE-GNN)来编码这些PIEs,并结合了可靠性分级注意力机制来降低不可靠数据的权重,最终生成密集的法线重建。实验表明,PIE-PS在事件驱动的光度立体视觉技术和直接求解器基线方面均优于现有方法。 AI

影响 引入了一种使用事件相机数据进行密集表面法线重建的新方法,有望改进机器人和3D建模中的应用。

排序理由 该集群包含一篇详细介绍计算机视觉新方法的学术论文。[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 →

新框架从事件相机数据中重建表面法线

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该集群包含一篇详细介绍计算机视觉新方法的学术论文。[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) · Xiangze Meng, Guangyu Li, Jing Li, Di Mei, Songchen Ma, Mingkun Xu, Rui Ma ·

    PIE-PS:基于物理辐照度事件流的光度立体成像

    arXiv:2610.08188v1 Announce Type: new Abstract: Event cameras record asynchronous log-image-irradiance changes with microsecond latency and high dynamic range. These properties are useful for photometric stereo under moving illumination, but raw events are sparse and depend on an…