Towards Robust Monocular Depth Estimation : Mixing Datasets for Zero-Shot Cross-Dataset Transfer
The success of monocular depth estimation relies on large and diverse training sets. Due to the challenges associated with acquiring dense ground-truth depth across different environments at scale, a number of datasets with distinct characteristics and biases have emerged. We develop tools that enab...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 3 vom: 23. März, Seite 1623-1637
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| 1. Verfasser: |
Ranftl, Rene
(VerfasserIn) |
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| Weitere Verfasser: |
Lasinger, Katrin,
Hafner, David,
Schindler, Konrad,
Koltun, Vladlen |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2022
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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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