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Author

Amir Hamza

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Preprint Aug 2026

Foundational feature fusion for conditional flow matching in 6D pose estimation

This work presents FunFlow6D, a novel flow matching-based formulation that leverages features from geometric and appearance foundation models for pose estimation, eliminating the need for task-specific encoders supervised on object-scene overlap and reducing supervision requirements and memory overhead.

Amir Hamza, Davide Boscaini, Fabio Poiesi · 0 citations

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