AI RESEARCH
On the Effectiveness of Textual Prompting with Lightweight Fine-Tuning for SAM3 Remote Sensing Segmentation
arXiv CS.CV
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ArXi:2512.15564v2 Announce Type: replace Remote sensing (RS) image segmentation is constrained by the limited availability of annotated data and a gap between overhead imagery and natural images used to train foundational models. This motivates effective adaptation under limited supervision. SAM3 concept-driven framework generates masks from textual prompts without requiring task-specific modifications, which may enable this adaptation.