Envisioning the Future of Fashion: The Creation And Application Of Diverse Body Pose Datasets for Real-World Virtual Try-On
Date
2024-08
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
University of the Witwatersrand, Johannesburg
Abstract
Fashion presents an opportunity for research methods to unite machine learning concepts with e-commerce to meet the growing demands of consumers. A recent development in intelligent fashion research envisions how individuals might appear in different clothes based on their selection, a process known as “virtual try-on”. Our research introduces a novel dataset that ensures multi-view consistency, facilitating the effective warping and synthesis of clothing onto individuals from any given perspective or pose. This addresses a significant shortfall in existing datasets, which struggle to recognise various views, thus limiting the versatility of virtual try-on. By fine-tuning state-of-the-art architectures on our dataset, we expand the utility of virtual try-on, making them more adaptable and robust across a diverse range of scenarios. A noteworthy additional advantage of our dataset is its capacity to facilitate 3D scene reconstruction. This capability arises from utilising a sparse collection of images captured from multiple angles, which, while primarily aimed at enriching 2D virtual try-on, inadvertently supports the simulation of 3D environments. This enhancement not only broadens the practical applications of virtual try-on in the real-world but also advances the field by demonstrating a novel application of deep learning within the fashion industry, enabling more realistic and comprehensive virtual try-on experiences. Therefore, our work heralds a novel dataset and approach for virtually synthesising clothing in an accessible way for real-world scenarios.
Description
A dissertation submitted in fulfilment of the requirements for the degree of Master of Science Computer Science, to the Faculty of Science, School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, 2024.
Keywords
Computer vision, Virtual try-on, Generative adversarial networks, Spatial transformer networks, UCTD
Citation
Molefe, Molefe Reabetsoe-Phenyo. (2024). Envisioning the Future of Fashion: The Creation And Application Of Diverse Body Pose Datasets for Real-World Virtual Try-On. [Master's dissertation, University of the Witwatersrand, Johannesburg]. WIReDSpace. https://hdl.handle.net/10539/45307