Xiuyuan Li

High-precision self-supervised underwater visual odometry via unified image enhancement and coupled cycle consistency

Experimental results indicate that the proposed self-supervised monocular visual odometry framework achieves higher depth estimation and pose estimation accuracy than existing state-of-the-art monocular VO approaches, and results suggest that the proposed framework is well suited to challenging underwater environments.