CUAHN-VIO: Content-and-Uncertainty-Aware Homography Network for Visual-Inertial Odometry. (arXiv:2208.13935v1 [cs.RO])

Learning-based visual ego-motion estimation is promising yet not ready for
navigating agile mobile robots in the real world. In this article, we propose
CUAHN-VIO, a robust and efficient monocular visual-inertial odometry (VIO)
designed for micro aerial vehicles (MAVs) equipped with a downward-facing
camera. The vision frontend is a content-and-uncertainty-aware homography
network (CUAHN) that is robust to non-homography image content and failure
cases of network prediction. It not only predicts the homography transformation
but also estimates its uncertainty. The training is …

arxiv homography network uncertainty