Online Mutual Adaptation of Deep Depth Prediction and Visual SLAM. (arXiv:2111.04096v3 [cs.RO] UPDATED)

The ability of accurate depth prediction by a convolutional neural network
(CNN) is a major challenge for its wide use in practical visual simultaneous
localization and mapping (SLAM) applications, such as enhanced camera tracking
and dense mapping. This paper is set out to answer the following question: Can
we tune a depth prediction CNN with the help of a visual SLAM algorithm even if
the CNN is not trained for the current operating environment in order to
benefit the SLAM …

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