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2019 | OriginalPaper | Buchkapitel

Let AI Clothe You: Diversified Fashion Generation

verfasst von : Rajdeep H. Banerjee, Anoop Rajagopal, Nilpa Jha, Arun Patro, Aruna Rajan

Erschienen in: Computer Vision – ACCV 2018 Workshops

Verlag: Springer International Publishing

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Abstract

In this paper, we demonstrate automation of fashion assortment generation that appeals widely to consumer tastes given context in terms of attributes. We show how we trained generative adversarial networks to automatically generate an assortment given a fashion category (such as dresses and tops etc.) and its context (neck type, shape, color etc.), and describe the practical challenges we faced in terms of increasing assortment diversity. We explore different GAN architectures in context based fashion generation. We show that by providing context better quality images can be generated. Examples of taxonomy of design given a fashion article and finally automate generation of new designs that span the created taxonomy is shown. We also show a designer-in-loop process of taking a generated image to production level design templates (tech-packs). Here the designers bring their own creativity by adding elements, suggestive from the generated image, to accentuate the overall aesthetics of the final design.

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Metadaten
Titel
Let AI Clothe You: Diversified Fashion Generation
verfasst von
Rajdeep H. Banerjee
Anoop Rajagopal
Nilpa Jha
Arun Patro
Aruna Rajan
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-21074-8_7

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