Reusable Architecture Growth for Continual Stereo Matching
The remarkable performance of recent stereo depth estimation models benefits from the successful use of convolutional neural networks to regress dense disparity. Akin to most tasks, this needs gathering training data that covers a number of heterogeneous scenes at deployment time. However, training...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 9 vom: 19. Aug., Seite 6167-6184
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| 1. Verfasser: |
Zhang, Chenghao
(VerfasserIn) |
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| Weitere Verfasser: |
Meng, Gaofeng,
Fan, Bin,
Tian, Kun,
Zhang, Zhaoxiang,
Xiang, Shiming,
Pan, Chunhong |
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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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