ActiveZero++ : Mixed Domain Learning Stereo and Confidence-Based Depth Completion With Zero Annotation
Learning-based stereo methods usually require a large scale dataset with depth, however obtaining accurate depth in the real domain is difficult, but groundtruth depth is readily available in the simulation domain. In this article we propose a new framework, ActiveZero++, which is a mixed domain lea...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 45(2023), 12 vom: 15. Dez., Seite 14098-14113
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| 1. Verfasser: |
Chen, Rui
(VerfasserIn) |
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| Weitere Verfasser: |
Liu, Isabella,
Yang, Edward,
Tao, Jianyu,
Zhang, Xiaoshuai,
Ran, Qing,
Liu, Zhu,
Xu, Jing,
Su, Hao |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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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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