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Recursive Uncertainty-Gated Image Registration for Learning-based Algorithms

arXiv · AI, language, vision and robotics · article · Sep 23, 2026 · UTC

Conventional image registration algorithms are robust to domain shifts and achieve low errors, but they are slow and computationally expensive. Deep-learning methods are efficient at inference-time, but face challenges in out-of-domain samples. We propose Recursive Uncertainty-Gated Image Registration (RUGI), an algorithm for iteratively refining deformation fields predicted by learning-based registration models. At each iteration, the registration model predicts an incremental deformation, and a gating map modulates the update. Refinements are hence concentrated in regions that remain difficu

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First collected: 2026-09-24T08:22:30.429Z. This is not the publication date.