Every Pixel Counts ++ : Joint Learning of Geometry and Motion with 3D Holistic Understanding
Learning to estimate 3D geometry in a single frame and optical flow from consecutive frames by watching unlabeled videos via deep convolutional network has made significant progress recently. Current state-of-the-art (SoTA) methods treat the two tasks independently. One important assumption of the e...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - (2019) vom: 23. Juli
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| 1. Verfasser: |
Luo, Chenxu
(VerfasserIn) |
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| Weitere Verfasser: |
Yang, Zhenheng,
Wang, Peng,
Wang, Yang,
Xu, Wei,
Nevatia, Ramkant,
Yuille, Alan |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2019
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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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