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English(EN) InfraNet: Quality-Aware RGB Guidance for Efficient Infrared Object Detection

InfraNet框架通过质量感知RGB引导增强红外目标检测

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出InfraNet，一个专为红外图像中更鲁棒的目标检测而设计的新型框架，特别是在RGB数据可能不可靠的恶劣条件下。该系统采用以红外为中心的架构，在训练期间调节RGB引导，允许灵活部署RGB-IR或仅IR输入。关键组件QualGate智能抑制不可靠的RGB信号并增强IR特征，从而在基准数据集上提高准确性和效率。 AI

影响 提高在具有挑战性的视觉环境中运行的目标检测系统的鲁棒性和效率。

排序理由 该条目是发表在arXiv上的研究论文，详细介绍了目标检测的新技术框架。[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 →

InfraNet框架通过质量感知RGB引导增强红外目标检测

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该条目是发表在arXiv上的研究论文，详细介绍了目标检测的新技术框架。[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) · Zichao Feng, Haodong Zhu, Jingying Yang, Sheng Xu, Yangyang Ren, Yuguang Yang, Xuhui Liu, Juan Zhang, Tian Wang, Linlin Yang, Baochang Zhang ·

    InfraNet：面向高效红外目标检测的质量感知RGB引导

    arXiv:2607.03795v1 Announce Type: new Abstract: Robust object detection under adverse visual conditions remains a long-standing challenge for multi-modal perception systems. Existing fusion-based methods typically require both RGB and infrared (IR) inputs, and treat them equally …

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