Dual-COPE: A novel prior-based category-level object pose estimation network with dual Sim2Real unsupervised domain adaptation module

Xi Ren; Nan Guo; Zichen Zhu; Xinbei Jiang

doi:10.1016/j.cag.2024.104045

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Dual-COPE: A novel prior-based category-level object pose estimation network with dual Sim2Real unsupervised domain adaptation module

Xi Ren Nan Guo Zichen Zhu Xinbei Jiang

Year: 2024 Journal: Computers & Graphics Vol: 124 Pages: 104045-104045 Publisher: Elsevier BV

DOI: 10.1016/j.cag.2024.104045

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Keywords:

Dual (grammatical number) Computer science Domain adaptation Adaptation (eye) Estimation Artificial intelligence Domain (mathematical analysis) Object (grammar) Pattern recognition (psychology) Computer vision Mathematics Psychology Neuroscience

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Robot Manipulation and Learning

Physical Sciences → Engineering → Control and Systems Engineering

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Human Pose and Action Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Dual-COPE: A novel prior-based category-level object pose estimation network with dual Sim2Real unsupervised domain adaptation module

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UDA-COPE: Unsupervised Domain Adaptation for Category-level Object Pose Estimation

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Diff-COPE: Diffusion-Based Category-Level 6D Object Pose Estimation

SGPA: Structure-Guided Prior Adaptation for Category-Level 6D Object Pose Estimation

DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency