DeepVIO is a self-supervised deep network for monocular VIO that projects stereo-derived 3D geometric constraints to train 2D optical flow and IMU fusion networks, outperforming prior learned methods on KITTI and EuRoC.
Visual-inertial monocular slam with map reuse
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
DeepVIO: Self-supervised Deep Learning of Monocular Visual Inertial Odometry using 3D Geometric Constraints
DeepVIO is a self-supervised deep network for monocular VIO that projects stereo-derived 3D geometric constraints to train 2D optical flow and IMU fusion networks, outperforming prior learned methods on KITTI and EuRoC.