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<oembed><version>1.0</version><provider_name>Panoptic Lidar Segmentation for Autonomous Driving</provider_name><provider_url>https://mscvprojects.ri.cmu.edu/2021teame</provider_url><title>Motivation - Panoptic Lidar Segmentation for Autonomous Driving</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="Zo1PHZisOZ"&gt;&lt;a href="https://mscvprojects.ri.cmu.edu/2021teame/motivation/"&gt;Motivation&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://mscvprojects.ri.cmu.edu/2021teame/motivation/embed/#?secret=Zo1PHZisOZ" width="600" height="338" title="&#x201C;Motivation&#x201D; &#x2014; Panoptic Lidar Segmentation for Autonomous Driving" data-secret="Zo1PHZisOZ" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>4D panoptic segmentation is the task of labeling all 3D points in a spatio-temporal lidar sequence with distinct semantic classes and instance IDs. Such spatio-temporal scene understanding is directly relevant for autonomous navigation, as robots need to be aware of both scene semantics and surrounding dynamic objects in order to navigate safely. Because this task &hellip; Continue reading ""</description><thumbnail_url>https://mscvprojects.ri.cmu.edu/2021teame/wp-content/uploads/sites/50/2022/04/image.png</thumbnail_url></oembed>

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