One-Shot Learning for Semantic Segmentation

    BMVC, 2017.

    Cited by: 83|Bibtex|Views39|Links
    EI

    Abstract:

    Low-shot learning methods for image classification support learning from sparse data. We extend these techniques to support dense semantic image segmentation. Specifically, we train a network that, given a small set of annotated images, produces parameters for a Fully Convolutional Network (FCN). We use this FCN to perform dense pixel-lev...More

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