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Tutorial : Theory and Application of Generative Adversarial Network

Ming­Yu Liu; Jan Kautz; Julie Bernauer Generative adversarial network framework has recently emerged as a promising generative modeling approach. It consists of a generative network and a discriminative network. Through the competition between the two networks, it learns to model the data distribution. In addition to modeling the image/video distribution in computer vision problems, the framework finds use in defining visual concept using examples. To a large extent, it eliminates the need of hand-crafting objective functions for various computer vision problems. In this tutorial, we will present a comprehensive overview of generative adversarial network research. We will cover several recent theoretical studies as well as training techniques and will also cover multiple vision applications of generative adversarial networks.