A synthetic-data-driven, hierarchy-aware adaptation of foundation models produces geometry-consistent representations that improve pose estimation and monocular depth in endoscopy.
Monocular absolute depth estimation from endoscopy via domain-invariant feature learning and latent consistency,
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Geometry-Consistent Endoscopic Representations for Image-Guided Navigation via Structured Foundation Model Adaptation
A synthetic-data-driven, hierarchy-aware adaptation of foundation models produces geometry-consistent representations that improve pose estimation and monocular depth in endoscopy.