<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>All Auto GT OD - Naifan Li's Blog</title><link>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/</link><description>All Auto GT OD | Naifan Li's Blog</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><lastBuildDate>Wed, 25 Feb 2026 10:38:44 +0800</lastBuildDate><atom:link href="https://blog.omagiclee.com/posts/ai-data/auto-gt-od/index.xml" rel="self" type="application/rss+xml"/><item><title>Auto GT OD</title><link>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/draft-overview/</link><pubDate>Wed, 25 Feb 2026 10:38:44 +0800</pubDate><guid>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/draft-overview/</guid><description><![CDATA[<p>Offboard 3D Object Detection from Point Cloud Sequences (CVPR 2021)
Auto4D: Learning to Label 4D Objects from Sequential Point Clouds (2021)</p>
<p>Once Detected, Never Lost (CTRL) (ICCV 2023)
MPPNet (OpenMMLab， 2022)
DetZero (2023)r
DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds (ICCV 2023)
LablFormer: Object Trajectory Refinement for Offboard Perception (Waabi, 2023)</p>
<p>Fusion4DAL: Offline Multi-modal 3D Object Detection for 4D Auto-labeling
SAM4D (2025)</p>]]></description></item><item><title>SAM4D: Segment Anything in Camera and LiDAR Streams</title><link>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/sam4d/</link><pubDate>Thu, 26 Jun 2025 13:07:34 +0800</pubDate><guid>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/sam4d/</guid><description><![CDATA[<p><i class="fas fa-award fa-fw" aria-hidden="true"></i><span style="color:gray">ICCV 2025</span>
<i class="fas fa-building fa-fw" aria-hidden="true"></i><span style="color:gray"></span>
<i class="fas fa-file-pdf fa-fw" aria-hidden="true"></i><a href="https://arxiv.org/abs/2506.21547" target="_blank" rel="noopener noreffer ">arXiv 2506.21547</a>
<i class="fab fa-github fa-fw" aria-hidden="true"></i><a href="https://github.com/CN-ADLab/SAM4D" target="_blank" rel="noopener noreffer ">CN-ADLab/SAM4D</a>
<i class="fas fa-globe fa-fw" aria-hidden="true"></i><a href="https://sam4d-project.github.io/" target="_blank" rel="noopener noreffer ">Project</a>
<i class="fas fa-blog fa-fw" aria-hidden="true"></i></p>
<h2 id="tldr">TL;DR</h2>
<p><span style="color:red;"></span></p>
<h2 id="motivations--innovations">Motivations &amp; Innovations</h2>
<h2 id="approach">Approach</h2>
<h3 id="model">Model</h3>
<h3 id="training-recipe">Training Recipe</h3>
<h3 id="data-recipe">Data Recipe</h3>
<h2 id="experiments">Experiments</h2>]]></description></item><item><title>DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds</title><link>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/detzero/</link><pubDate>Fri, 09 Jun 2023 13:06:17 +0800</pubDate><guid>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/detzero/</guid><description><![CDATA[<p><i class="fas fa-award fa-fw" aria-hidden="true"></i><span style="color:gray"></span>
<i class="fas fa-building fa-fw" aria-hidden="true"></i><span style="color:gray"></span>
<i class="fas fa-file-pdf fa-fw" aria-hidden="true"></i>arXiv 
<i class="fab fa-github fa-fw" aria-hidden="true"></i>

<i class="fas fa-globe fa-fw" aria-hidden="true"></i>
<i class="fas fa-blog fa-fw" aria-hidden="true"></i></p>
<h2 id="tldr">TL;DR</h2>
<p><span style="color:red;"></span></p>
<h2 id="motivations--innovations">Motivations &amp; Innovations</h2>
<h2 id="approach">Approach</h2>
<h3 id="model">Model</h3>
<h3 id="training-recipe">Training Recipe</h3>
<h3 id="data-recipe">Data Recipe</h3>
<h2 id="experiments">Experiments</h2>]]></description></item><item><title>3DAL: Offboard 3D Object Detection from Point Cloud Sequences</title><link>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/3dal/</link><pubDate>Mon, 08 Mar 2021 11:38:25 +0800</pubDate><guid>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/3dal/</guid><description><![CDATA[<p><i class="fas fa-award fa-fw" aria-hidden="true"></i><span style="color:gray"></span>
<i class="fas fa-building fa-fw" aria-hidden="true"></i><span style="color:gray">Waymo LLC</span>
<i class="fas fa-file-pdf fa-fw" aria-hidden="true"></i><a href="https://arxiv.org/abs/2103.13612" target="_blank" rel="noopener noreffer ">arXiv 2103.13612</a></p>
<h2 id="tldr">TL;DR</h2>
<p><span style="color:red;"></span></p>
<h2 id="motivations--innovations">Motivations &amp; Innovations</h2>
<h2 id="approach">Approach</h2>
<p></p>
<h3 id="multi-frame-3d-object-detection">Multi-frame 3D Object Detection</h3>
<h3 id="multi-object-tracking">Multi-object Tracking</h3>
<p>tracking-by-detection: using detector boxes for associations and Kalman filter for state updates.</p>
<h3 id="object-track-data-extraction">Object Track Data Extraction</h3>
<h3 id="object-centric-auto-labeling">Object-centric Auto Labeling</h3>
<h4 id="divide-and-conquer-motion-state-estimation">Divide and conquer: motion state estimation</h4>
<p>A linear classifier using a few heuristic features from the object track’s boxes can already achieve 99%+ motion state classification accuracy for vehicles.</p>]]></description></item><item><title>Auto4D: Learning to Label 4D Objects from Sequential Point Clouds</title><link>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/auto4d/</link><pubDate>Sun, 17 Jan 2021 11:56:49 +0800</pubDate><guid>https://blog.omagiclee.com/posts/ai-data/auto-gt-od/auto4d/</guid><description><![CDATA[<p><i class="fas fa-award fa-fw" aria-hidden="true"></i><span style="color:gray"></span>
<i class="fas fa-building fa-fw" aria-hidden="true"></i><span style="color:gray"></span>
<i class="fas fa-file-pdf fa-fw" aria-hidden="true"></i><a href="https://arxiv.org/abs/2101.06586" target="_blank" rel="noopener noreffer ">arXiv 2101.06586</a>
<i class="fab fa-github fa-fw" aria-hidden="true"></i></p>
<h2 id="tldr">TL;DR</h2>
<p><span style="color:red;"></span></p>
<h2 id="motivations--innovations">Motivations &amp; Innovations</h2>
<h2 id="approach">Approach</h2>
<p></p>]]></description></item></channel></rss>