1st Workshop and Challenge on Category-Level Object Pose Estimation for Robotic Manipulation
Yang You, Jiyao Zhang, Jiankai Sun, Leonidas Guibas, Chen Wang, Luca Carlone, Linfang Zheng, Mac Schwager, Cewu Lu, Hao Dong, Bowen Wen, Ruida Zhang, Weiyao Huang, Mingdong Wu, Yijia Weng, Yitong Peng, Ruihai Wu, Lixin Yang, Junxiao Kong, Qiaojun Yu
Abstract
This workshop addresses the critical problem of category-level object pose estimation and its applications within complex robotic manipulation scenarios. Pose estimation, a fundamental challenge in both 3D computer vision and robotics perception, involves accurately determining an object's complete 6-degree-of-freedom (6DoF) pose, comprising its 3D rotation and translation. Our workshop specifically focuses on advancing category-level pose estimation methods under realistic and demanding robotic manipulation settings, particularly emphasizing articulated objects, dynamic environments with potential human-object interactions, and objects subject to severe occlusions and partial visibility.
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