RBE-Flow recasts dense cross-modal flow estimation as closed-loop recurrent Bayesian estimation on learned feature manifolds with uncertainty-adaptive updates and achieves SOTA on three registration benchmarks.
Gdros: A geometry- guided dense registration framework for optical-sar images under large geometric transformations
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CRFT is a new transformer architecture using recurrent consistent feature flow learning to achieve accurate and robust cross-modal image registration under large variations.
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RBE-Flow: Recurrent Bayesian Estimation on Feature Manifolds for Cross-Modal Registration
RBE-Flow recasts dense cross-modal flow estimation as closed-loop recurrent Bayesian estimation on learned feature manifolds with uncertainty-adaptive updates and achieves SOTA on three registration benchmarks.
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CRFT: Consistent-Recurrent Feature Flow Transformer for Cross-Modal Image Registration
CRFT is a new transformer architecture using recurrent consistent feature flow learning to achieve accurate and robust cross-modal image registration under large variations.