Visual-Inertial Odometry with Deep Learning-Based Adaptive Noise Covariance Estimation

A novel deep learning-based approach, VIO-DualProNet, that dynamically estimates the inertial sensor noise covariance to improve the accuracy and robustness of visual-inertial odometry algorithms.