Tomtom Global Content B.v.

Erik Stammes

Klaus Michael Hofmann

Mohsen Ghafoorian

The invention relates to a method of training a model for use in semantic image segmentation. The model includes a first classifier neural network and a second classifier neural network. The method includes training the first network by inputting a first training image containing a target object to the first network, using the first network to identify and erase pixels of the first training image that are discriminative for the target object, inputting the first training image to the second network, using the second network to determine a likelihood of the first modified training image containing the target object and updating weights of the first network using a first loss function that is a monotonically-increasing function of the determined likelihood.

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Barcelona, Spain

Erik Stammes