VINet: Visual-inertial odometry as a sequence-to-sequence learning problem
In this paper we present an on-manifold sequence-to-sequence learning approach to motion estimation using visual and inertial sensors. It is to the best of our knowledge the first end-to-end trainable method for visual-inertial odometry which performs fusion of the data at an intermediate feature-re...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Published: |
Association for the Advancement of Artificial Intelligence
2017
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