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        <title>时序聚合 - 标签 - Zhaoylee&#39;s Blogs</title>
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        <description>时序聚合 - 标签 - Zhaoylee&#39;s Blogs</description>
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    <title>PLOT: Pseudo-Labeling via Object Tracking for Monocular 3D Object Detection</title>
    <link>https://zhaoylee.github.io/Blogs_lovelt/posts/plot---pseudo-labeling-via-object-tracking-for-monocular-3d-object-detection/</link>
    <pubDate>Sun, 15 Mar 2026 20:52:51 &#43;0800</pubDate>
    <author>zhaoylee</author>
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<blockquote>
<p><strong>🏛️ 会议/期刊</strong>：ICLR<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://openreview.net/pdf?id=3knS4J9isg" target="_blank" rel="noopener noreffer ">PLOT: Pseudo-Labeling via Object Tracking for Monocular 3D Object Detection</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> 单目 3D 目标检测模型极度“吃数据”。然而，人工标注 3D 边界框极其昂贵且耗时，导致目前带 3D 标签的数据集规模很小，严重限制了模型的泛化能力。</p>]]></description>
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