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English(EN) Stereo LWIR-RGB Automatic Labeling for Low-Light Camera-Based VRU Detection

新流程可自动标注低光照VRU检测图像

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种用于低光照条件下弱势道路使用者（VRU）图像自动标注的流程。该方法利用LWIR-RGB图像对，从LWIR（长波红外）光谱中获取标签，VRU在该光谱中可通过其体温区分。该系统采用立体设置，与以往侧重对齐的方法相比，简化了硬件要求并降低了成本。使用这些自动生成的标签训练的模型在检测指标上表现优于使用手动标注数据或现成基线训练的模型。 AI

影响 这项研究通过在具有挑战性的低光照条件下实现更有效的VRU检测，有望改善安全系统。

排序理由 这是一篇详细介绍新图像标注方法的学术论文。[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 →

新流程可自动标注低光照VRU检测图像

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这是一篇详细介绍新图像标注方法的学术论文。[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) · Dimitrios Bouzoulas, Pyry J\"appinen, Pejman Habibiroudkenar, Eerik Alamikkotervo, Risto Ojala ·

    用于低光照相机VRU检测的立体LWIR-RGB自动标注

    arXiv:2610.23621v1 Announce Type: new Abstract: VRU detection in low-light conditions is a key component in ensuring VRU safety during the most collision prone time of the day. Currently, advances in low-light detection are limited due to the lack of large scale datasets and auto…

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