The research team trained the system in an unsupervised fashion, meaning the training data consisted of product titles and images that didn't require any additional human annotation. The team increased the system's stability using an auxiliary classifier that categorized images generated by the model according to three properties: apparel type (pants, jeans, or shorts), color, and whether they depicted men's, women's, or unisex clothing
