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.
Learning monocular visual odometry with dense 3d mapping from dense 3d flow
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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.