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    DeepMask

    DeepMask

    Torch implementation of DeepMask and SharpMask

    DeepMask is an early, influential approach to class-agnostic object segmentation that learns to propose pixel-accurate masks directly from images. Instead of first generating boxes and then refining them, the network predicts a foreground mask and an “objectness” score for a given image patch, yielding high-quality segment proposals suitable for downstream detection or instance segmentation. The model is trained end-to-end to align mask shape with object extent, which markedly improves recall at a manageable number of proposals. ...
    Downloads: 1 This Week
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