Real-Time Object Pose Estimation with Pose Interpreter Networks
In this work, we introduce pose interpreter networks for 6-DoF object pose estimation. In contrast to other CNN-based approaches to pose estimation that require expensively annotated object pose data, our pose interpreter network is trained entirely on synthetic pose data. We use object masks as an...
Main Authors: | Wu, Jimmy (Author), Zhou, Bolei (Author), Russell, Rebecca (Author), Kee, Vincent (Author), Wagner, Syler (Author), Hebert, Mitchell (Author), Torralba, Antonio (Author), Johnson, David M.S (Author) |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor) |
Format: | Article |
Language: | English |
Published: |
IEEE,
2020-01-20T18:35:05Z.
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Subjects: | |
Online Access: | Get fulltext |
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