NEURAL NETWORK MODEL FOR IMAGE SEGMENTATION

摘要

A computer processing system is configured to train a model for use in semantic image segmentation.The model comprises a refinement neural network, a discriminator neural network. The refinement neural network is configured to receive a predicted label distribution for an image, obtain one or more random values from a random or pseudo-random noise source, use the one or more random values to generate a plurality of predicted segmentation maps from the received predicted label distribution and output the plurality of predicted segmentation maps to the discriminator neural network. The computer processing system is configured to train the refinement neural network using an objective function that is a function of an output of the discriminator neural network and that further includes a term representative of a difference between the predicted label distribution and an average of the plurality of predicted segmentation maps output by the refinement neural network for the predicted label distribution.