ATTRIBUTIONALLY ROBUST TRAINING FOR WEAKLY SUPERVISED LOCALIZATION AND SEGMENTATION

    公开(公告)号:US20220012530A1

    公开(公告)日:2022-01-13

    申请号:US16926511

    申请日:2020-07-10

    Applicant: Adobe Inc.

    Abstract: Embodiments are disclosed for training a neural network classifier to learn to more closely align an input image with its attribution map. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving a training image comprising a representation of one or more objects, the training image associated with at least one label for the representation of the one or more objects, generating a perturbed training image based on the training image using a neural network, and training the neural network using the perturbed training image by minimizing a combination of classification loss and attribution loss to learn to align an image with its corresponding attribution map.

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