The fashion industry is currently one of the largest industries in the globe. Projections suggest the fashion apparel industry will reach a whopping valuation of $3.3 trillion by 2030. Hence, the way the fashion industry operates today shows a day and night difference from what the industry was two decades ago. As technology has impacted every aspect of human life, the fashion industry began adopting the latest and advanced technologies for better opportunities. For instance, AR try-on technology has managed to change customers' entire shopping experience. That being said, let's check out some technological trends revolutionizing the fashion apparel industry in 2022.

We present a novel method to solve image analogy problems : it allows to learn the relation between paired images present in training data, and then generalize and generate images that correspond to the relation, but were never seen in the training set. Therefore, we call the method Conditional Analogy Generative Adversarial Network (CAGAN), as it is based on adversarial training and employs deep convolutional neural networks. An especially interesting application of that technique is automatic swapping of clothing on fashion model photos. Our work has the following contributions. First, the definition of the end-to-end trainable CAGAN architecture, which implicitly learns segmentation masks without expensive supervised labeling data. Second, experimental results show plausible segmentation masks and often convincing swapped images, given the target article. Finally, we discuss the next steps for that technique: neural network architecture improvements and more advanced applications.