ProMi, a prototype-mixture classifier built from bounding-box labels, improves few-shot binary segmentation accuracy across standard benchmarks and foundation-model features.
Learning few-shot segmentation from bounding box annotations
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ProMi: An Efficient Prototype-Mixture Baseline for Few-Shot Segmentation with Bounding-Box Annotations
ProMi, a prototype-mixture classifier built from bounding-box labels, improves few-shot binary segmentation accuracy across standard benchmarks and foundation-model features.