AI RESEARCH
UniSurgSAM: A Unified Promptable Model for Reliable Surgical Video Segmentation
arXiv CS.CV
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ArXi:2604.03645v1 Announce Type: cross Surgical video segmentation is fundamental to computer-assisted surgery. In practice, surgeons need to dynamically specify targets throughout extended procedures, using heterogeneous cues such as visual selections, textual expressions, or audio instructions. However, existing Promptable Video Object Segmentation (PVOS) methods are typically restricted to a single prompt modality and rely on coupled frameworks that cause optimization interference between target initialization and tracking.