Author

Q. Ge

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Jul 2026

Does Robust VIO Need More Learning? Geometry-Verified Visual Measurements under Distribution Shift

A minimal-learning stereo VIO framework in which SEA-RAFT is used only to propose dense stereo correspondences and predict their uncertainty, while temporal tracking, geometric verification, and state estimation remain explicit is proposed.

Yangyang Ning, Shuao Liang, Q. Ge et al. · arXiv.org · 0 citations