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.