Supervising the new with the old: Learning SFM from SFM
Recent work has demonstrated that it is possible to learn deep neural networks for monocular depth and ego-motion estimation from unlabelled video sequences, an interesting theoretical development with numerous advantages in applications. In this paper, we propose a number of improvements to these a...
Main Authors: | Klodt, M, Vedaldi, A |
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Format: | Conference item |
Published: |
Springer
2018
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