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Object pose estimation is an important component of most vision pipelines for embodied agents, as well as in 3D vision more generally.
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Manuelli, L., Gao, W., Florence, P., Tedrake, R.: kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation. In: ISRR (2019)
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Wang, H., Sridhar, S., Huang, J., Valentin, J., Song, S., Guibas, L.: Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation. In: CVPR (2019)
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Lin, Y., Tremblay, J., Tyree, S., Vela, P.A., Birchfield, S.: Single-stage Keypoint-based Category-level Object Pose Estimation from an RGB Image. In: ICRA (2022)
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Sajnani, R., Poulenard, A., Jain, J., Dua, R., Guibas, L.J., Sridhar, S.: ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes. In: CVPR (2022)
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Simeonov, A., Du, Y., Tagliasacchi, A., Tenenbaum, J.B., Rodriguez, A., Agrawal, P., Sitzmann, V.: Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. In: ICRA (2022)
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Vaze, S., Han, K., Vedaldi, A., Zisserman, A.: Generalized Category Discovery. In: CVPR (2022)
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