Generating Realistic African Fashion Designs for Men using Deep Convolutional Generative Adversarial Networks

Abstract

The African fashion industry has continued to thrive over the years and has gained recognition globally. However, the design and manufacturing process still follows the conventional methodology. Some studies have been done on image synthesis using deep learning techniques for the progress of the fashion industry with little or none of the studies on African fashion. African fashion, especially Nigerian fashion lacks an online presence in terms of artificially generated realistic fashion styles. Since fashion is a way a people express themselves through clothing, footwear, makeup or hairdo in a specific time, place, and environment, this work aims to develop a system that would promote the diversity of the Nigerian people, reduce inequality and promote economic growth in line with the sustainable development goals. In this work, we developed a system that can generate new African fashion designs for men by applying the Deep Convolutional Generative Adversarial Networks (DCGAN) using a locally curated image data from publicly accessible and open-source images and the AFRIFASHION40000 dataset. The method involves designing a Male Fashion Generative Framework (MFGF), building an image generation model that can synthesize new fashion images and a neural style transfer model that can style the generated image. The model trained on the AFRIFASHION40000 dataset was found to perform better than the locally curated dataset as indicated by a lower generator loss and a higher discriminator loss. This study provides a solution to the problem of generating new designs for men in the Nigerian fashion industry and highlights the importance of integrating deep learning into the African fashion industry. The result shows a generation of low resolution images that represents different fashion styles for African men. It also provides a framework for future research. The findings can be beneficial to fashion designers, manufacturers, and consumers looking for new and innovative designs.