Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation
6D object pose estimation is a fundamental yet challenging problem in computer vision. Convolutional Neural Networks (CNNs) have recently proven to be capable of predicting reliable 6D pose estimates even under monocular settings. Nonetheless, CNNs are identified as being extremely data-driven, and...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 3 vom: 15. Feb., Seite 1788-1803
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| 1. Verfasser: |
Wang, Gu
(VerfasserIn) |
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| Weitere Verfasser: |
Manhardt, Fabian,
Liu, Xingyu,
Ji, Xiangyang,
Tombari, Federico |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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