UniSurgSAM: A Unified Promptable Model for Reliable Surgical Video Segmentation
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. Moreover, these methods produce hallucinated predictions when the target is absent and suffer from accumulated mask drift without failure recovery. To address these challenges, we present UniSurgSAM, a u...
| Authors | Haofeng Liu, Ziyue Wang, Alex Y. W. Kong et al. |
|---|---|
| Primary category | eess.IV |
| Published | 4 April 2026 |
| Last updated at source | 4 April 2026 |
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