You can try without visiting: a comprehensive survey on virtually try-on outfits

Abstract

Since the last years and until now, technology has made fast progress for many industries, in particularly, garment industry which aims to follow consumer desires and demands. One of these demands is to fit clothes before purchasing them on-line. Therefore, many research works have been focused on how to develop an intelligent apparel industry to ensure the online shopping experience. Image-based virtual try-on is among the most potential approach of virtual fitting that tries on target clothes into customer's image, therefore, it has received considerable research efforts in the recent years. However, there are several challenges involved in development of virtual try-on that make it difficult to achieve naturally looking virtual outfit such as shape, pose, occlusion, illumination cloth texture, logo and text etc. The aim of this study is to provide a comprehensive and structured overview of extensive research on the advancement of virtual try-on. This review first introduces virtual try-on and its challenges followed by its demand in fashion industry. We summarize state-of-the-art image based virtual try-on for both fashion detection and fashion synthesis as well as their respective advantages, drawbacks, and guidelines for selection of specific try-on model followed by its recent development and successful application. Finally, we conclude the paper with promising directions for future research.

Deep Learning in Virtual Try-On: A Comprehensive Survey

“…In this paper, our emphasis will be on the deep learning-based models that have gained more popularity within the research community and shown greater promise in applications. Interested readers can refer to [27], [59], and [61] for further details regarding the 3D virtual try-on models.…”

“…These outcomes include increased visitor numbers, longer time spent on the site, higher spending, and greater sales, as well as an increase in the conversion rate of customers [101]. By employing virtual try-on models, it is observed that the return rate was significantly decreased [81], and the customers were willing to spend more [59]. Research has indicated that the adoption of virtual try-on technology for online apparel shopping can significantly reduce the risk regarding apparel fit perceived by consumers when shopping online while also increasing the enjoyment of the shopping experience [99].…”

“…There are a few existing survey papers that discuss the potential use of artificial intelligence (AI) in supporting the fashion industry and facilitating fashion-related tasks [27], [59], [61], [132], as shown in TABLE 1. These literatures cover a wide range of topics, such as how AI can benefit the fashion industry, how fashion tools are developed and employed, which countries are leading in research on AI for fashion, how fashion data is utilised to enhance the effectiveness of AI models, and the classification of fashion-based AI tools.…”

Monocular Image-Based 3-D Model Retrieval: A Benchmark

“…In spite of the rapidly emerging works, there lacks a systematic survey to summarize image-based virtual tryon methods in datasets, method design and experimental evaluation. Two previous reviews [51], [52] only introduced several representative methods, but did not perform comprehensive comparison and unified evaluation. To the best of our knowledge, this is the first systematic image-based virtual try-on review with unified evaluation, which also has the following unique characteristics:…”