Incomplete image filling task, often known as the image inpainting task, is a popular topic in the applied deep learning field. This thesis paper considers several popular designs for deep neural networks including the supervised autoencoder and unsupervised generative adversarial networks. The goal of this thesis is to give researcher guidelines for solving the image inpainting task by deep learning methods with limited resources.