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A SAM2-Driven RGB-T Annotation Pipeline with Thermal-Guided Refinement for Semantic Segmentation in Search-and-Rescue Scenes

2026-01-06

Abstract excerpt

High-quality RGB–thermal infrared (RGB-T) semantic segmentation datasets are crucial for search-and-rescue (SAR) applications, yet their development is hindered by the scarcity of annotated ground truth and by the challenges of thermal-camera calibration, which typically depends on heated targets with limited geometric definition. Recent approaches, such as MATT, focus on transferring SAM-based RGB masks to multi-...

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Literature Corpus work
41a71638-3980-5f3c-a60d-742571ee0c87
DOI
10.20944/preprints202601.0365.v1
Open publication

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A SAM2-Driven RGB-T Annotation Pipeline with Thermal-Guided Refinement for Semantic Segmentation in Search-and-Rescue ScenesDOI 10.20944/preprints202601.0365.v1
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