Training semantic image segmentation model comprising deformable convolutional neural network

Abstract

A method for training an image classification model includes obtaining first prediction class annotation information of a first image by using an image classification network based on a first model parameter of an offset network being fixed; determining a second model parameter corresponding to the image classification network by using a classification loss function based on the image content class information and the first prediction class annotation information; obtaining second prediction class annotation information of the first image by using the offset network based on the second model parameter of the image classification network being fixed; determining a third model parameter corresponding to the offset network by using the classification loss function based on the image content class information and the second prediction class annotation information; and training a semantic image segmentation network model based on the second model parameter and the third model parameter.

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