AI RESEARCH
ReMeDI: Refined Memory for Disambiguation of Identities with SAM3 in Surgical Segmentation
arXiv CS.CV
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ArXi:2512.16880v2 Announce Type: replace Accurate surgical instrument segmentation in endoscopy is crucial for computer-assisted interventions, yet remains challenging due to frequent occlusions, rapid motion, and long-term instrument re-entry. While SAM3 provides a powerful spatio-temporal framework for video object segmentation, its performance in surgical scenes is limited by indiscriminate memory updates, fixed memory capacity, and weak identity recovery after occlusions. We propose ReMeDI-SAM3, a.