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Pose Estimation for Objects with Rotational Symmetry
[article]
2018
arXiv
pre-print
Pose estimation is a widely explored problem, enabling many robotic tasks such as grasping and manipulation. In this paper, we tackle the problem of pose estimation for objects that exhibit rotational symmetry, which are common in man-made and industrial environments. In particular, our aim is to infer poses for objects not seen at training time, but for which their 3D CAD models are available at test time. Previous work has tackled this problem by learning to compare captured views of real
arXiv:1810.05780v1
fatcat:5h6dfh3v7zffnkx5pa4er2e7yi