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6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints
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<span title="2019-10-23">2019</span>
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arXiv
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We present 6-PACK, a deep learning approach to category-level 6D object pose tracking on RGB-D data. ...
Our method tracks in real-time novel object instances of known object categories such as bowls, laptops, and mugs. 6-PACK learns to compactly represent an object by a handful of 3D keypoints, based on ...
To this end, we propose 6-PACK, a vision-based 6D-Pose Anchor-based Category-level Keypoint tracker. 6-PACK tracks a small set of keypoints in RGB-D videos and estimates object pose by accumulating relative ...
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An Embarrassingly Pragmatic Introduction to Vision-based Autonomous Robots
[article]
<span title="2021-12-14">2021</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
Part of the problem is to get a robot to emulate the perception of human beings, our sense of sight, replacing the eyes with cameras and the brain with mathematical models such as Neural Networks. ...
[90] Chen Wang, Roberto Martín-Martín, Danfei Xu, Jun Lv, Cewu Lu, Li Fei-Fei, Silvio
Savarese, and Yuke Zhu. 6-pack: Category-level 6d pose tracker with anchor-based
keypoints, 2019. ...
[95] Di Wu, Zhaoyong Zhuang, Canqun Xiang, Wenbin Zou, and Xia Li. 6d-vnet: End-
to-end 6dof vehicle pose estimation from monocular rgb images. ...
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