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here we will discuss the main ideas of style gang 3 architecture i will begin by introducing an intuitive understanding of the style going architecture and benedict will cover the details of the code implementation this discussion is a part of our survey paper deep learning for phase generation and editing to learn more check the links in the description and visit our github repository stylegang3 is an improvement over previous versions of this architecture the architecture itself has different use cases for example it can generate in high resolution faces which do not exist [Music] or for example here the same architecture but trained on a different data set can generate shoe which doesnt exist another important use case is that these architecture allows to merge two objects such that the resulting object contain features of both sources of information if we merge source a and service b the resulting image will contain information from both source a and b [Music] this architecture c