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        <title>跨尺度 - 标签 - Zhaoylee&#39;s Blogs</title>
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    <title>SpikeSMOKE: Spiking Neural Networks for Monocular 3D Object Detection with Cross-Scale Gated Coding</title>
    <link>https://zhaoylee.github.io/Blogs_lovelt/posts/spikesmoke--spiking-neural-networks-for-monocular-3d-object-detection-with-cross-scale-gated-coding/</link>
    <pubDate>Sun, 15 Mar 2026 19:59:10 &#43;0800</pubDate>
    <author>zhaoylee</author>
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<blockquote>
<p><strong>🏛️ 会议/期刊</strong>：CVPR / ICCV / ECCV<br>
<strong>📅 发表年份</strong>：2026<br>
<strong>💻 开源代码</strong>：<a href="%e5%a1%ab%e5%86%99%e4%bd%a0%e7%9a%84URL" rel="">无</a><br>
<strong>📄 论文题目</strong>：<a href="https://arxiv.org/pdf/2506.07737" target="_blank" rel="noopener noreffer ">SpikeSMOKE: Spiking Neural Networks for Monocular 3D Object Detection with Cross-Scale Gated Coding</a></p>
</blockquote>
<hr>
<h3 id="一-背景研究目的与核心问题">一、 背景、研究目的与核心问题</h3>
<ul>
<li>
<p><strong>研究背景：</strong> 在自动驾驶等领域，3D 目标检测是核心技术。其中，“单目 3D 目标检测”由于仅依赖单张图像，硬件成本极低，备受青睐。然而，传统基于人工神经网络（ANNs）的模型计算量大、能耗极高，给边缘计算设备的电池续航和散热带来了巨大压力。</p>]]></description>
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