{"id":108009,"date":"2022-02-25T13:12:52","date_gmt":"2022-02-25T07:42:52","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=108009"},"modified":"2022-02-25T13:15:28","modified_gmt":"2022-02-25T07:45:28","slug":"generative-adversarial-network-in-fashion-industry","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/generative-adversarial-network-in-fashion-industry\/","title":{"rendered":"Applying Generative Adversarial Network (GANs) in The Fashion Industry"},"content":{"rendered":"

There are still many theoretical challenges in the design of GANs, so authors of research papers do not
\nfocus their attention on the tasks that have an immediate practical impact. For instance, there were papers
\ninvestigating the reproducibility of reported results from different GANs, generation of clustered data with
\nGANs, accelerating GAN computational operations on specific hardware (Field Programmable Gate
\nArrays), and many other works.<\/p>\n

However, there have also been some interesting ideas that may be of more practical value but have not yet
\nmade it into the business that we would like to review.<\/p>\n

One interesting topic to cover is applying GANs in the fashion industry. The publication is dedicated to AI
\ntechnologies for virtual fitting room<\/a> development. After deep research, it was decided that any virtual fitting
\nroom application must be combined with AR libraries for additional functionality. Therefore, data scientists
\nshould work on a model for pose estimation that could detect crucial points of the frame.<\/p>\n

It seems that fashion companies have slowly become aware of the benefits machine learning can bring and
\nare looking for new ways of enhancing the customer experience with its help.<\/p>\n

For instance, Zalando is researching how GANs can be used to generate images of fashion models
\nwearing customer-selected clothing items, thus helping customers visualize how the individual outfit
\nitems would combine together. This is an excellent example of how GANs can change the industry since in
\nthe past the only option to solve this problem would be to take photographs of a model wearing each
\ncombination of clothing which is simply not feasible.<\/p>\n

One additional curious piece of research from the same company shows that GANs can also be applied to
\nhelp designers experiment with new clothing ideas by allowing them to modify the shape, color, and texture
\nof an existing clothing item.<\/p>\n

Continuing on, we would like to discuss a popular topic of face swapping. While almost everybody has
\nheard of the DeepFake technology as it has been used to make fun of politicians and celebrities, not
\neverybody knows about the technology\u2019s limitations.<\/p>\n

For each target and source subject, the DeepFake network has to be trained on video sequences for both
\nsubjects that are not always available. In a recent paper on the topic, the authors introduced a new face
\nswap model called FaceShifter that allows users to swap faces in situations when only two photos are
\navailable.<\/p>\n

Moreover, the network is able to handle situations when the target or source face is occluded by clothing items, obstacles, or when the lighting conditions significantly differ between the two images.<\/p>\n

One can think of negative consequences a technology like this may lead to when made accessible to a
\nwider public, but there are positive applications as well. For instance, it can be used to anonymize peoples\u2019
\nfaces in photos\/videos by swapping the real faces with synthetic ones as in the research published here.
\nThe resulting media could be used for any purpose (e.g. content creation) without being afraid of legal
\nclaims and objections from the persons originally captured in the media.

There are still many theoretical challenges in the design of GANs, so authors of research papers do not focus their attention on the tasks that have an immediate practical impact. For instance, there were...<\/p>\n","protected":false},"author":5,"featured_media":108011,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19501],"tags":[26637,26638],"class_list":["post-108009","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","tag-gan-in-fashion-industry","tag-generative-adversarial-network"],"yoast_head":"\nApplying Generative Adversarial Network (GANs) in The Fashion Industry - DataFlair<\/title>\n<meta name=\"description\" content=\"Learn about Generative Adversarial Network in the fashion industry. 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