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Text-driven adaptation of foundation models for few-shot surgical workflow analysis
5
Zitationen
5
Autoren
2025
Jahr
Abstract
We propose a text-driven adaptation approach that mitigates the modality gap and handles multiple downstream tasks in surgical workflow analysis, with minimal reliance on large annotated datasets. The code and dataset will be released in https://github.com/CAMMApublic/Surg-FTDA .
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