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...

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Bibliographic Details
Main Authors: Klodt, M, Vedaldi, A
Format: Conference item
Published: Springer 2018