Changing clothing on people images using generative adversarial networks

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dc.date.accessioned	2020-01-28T13:32:17Z
dc.date.available	2020-01-28T13:32:17Z
dc.date.issued	2020
dc.identifier.citation	Pozdniakov, Yevhen. Changing clothing on people images using generative adversarial networks : Master Thesis : manuscript rights / Yevhen Pozdniakov ; Supervisor Dr. Orest Kupyn ; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2020. – 62 p. : ill.	uk
dc.identifier.uri	http://er.ucu.edu.ua/handle/1/1904
dc.language.iso	en	uk
dc.subject	generative adversarial networks	uk
dc.subject	Geometric Matching Module	uk
dc.subject	Flow Composition Module	uk
dc.title	Changing clothing on people images using generative adversarial networks	uk
dc.type	Preprint	uk
dc.contributor.translator	Pozdniakov, Yevhen
dc.status	Публікується вперше	uk
dc.description.abstracten	Generative Adversarial Networks (GANs) in recent years has certainly become one of the biggest trends in the computer vision domain. GANs are used for generating face images and computer game scenes, transferring artwork style, visualizing designs, creating super-resolution images, translating text to images, etc. We want to present a model to solve an image problem: generate new outﬁts onto people images. This task seems to be extremely important for ofﬂine/online trade and fashion industry. Changing clothing on people images isn’t a trivial task. The generated part of the image should have high quality without blurring. Another problem is generating long sleeves on the images with T-shirts, for example. As a result, well-known models are not suitable for this task. In the master project, we are going to reproduce the model for clothing changing on people images based on the existing approaches and improve it in order to get better quality of the image	uk