Customers all over the world want to see how the clothes fit them or not before purchasing. Therefore, customers by nature prefer brick-and-mortar clothes shopping so they can try on products before purchasing them. But after the Pandemic of COVID19 many sellers either shifted to online shopping or closed their fitting rooms which made the shopping process hesitant and doubtful. The fact that the clothes may not be suitable for their buyers after purchase led us to think about using new AI technologies to create an online platform or a virtual fitting room (VFR) in the form of a mobile application and a deployed model using a webpage that can be embedded later to any online store where they can try on any number of cloth items without physically trying them. Besides, it will save much searching time for their needs. Furthermore, it will reduce the crowding and headache in the physical shops by applying the same technology using a special type of mirror that will enable customers to try on faster. On the other hand, from business owners' perspective, this project will highly increase their online sales, besides, it will save the quality of the products by avoiding physical trials issues. The main approach used in this work is applying Generative Adversarial Networks (GANs) combined with image processing techniques to generate one output image from two input images which are the person image and the cloth image. This work achieved results that outperformed the state-of-the-art approaches found in literature.

A user wearing the measurement garment sees themself instead wearing a pre-selected item of digitized clothing from the store's catalog. A team of researchers have created a way for people to visualize themselves wearing items of clothing they don't have direct physical access to. The virtual try-on system uses a unique capture device and an artificial intelligence (AI)-driven way to digitize items of clothing. Using a corresponding imaging and display system, a user can then view themself on a screen wearing anything from the digital wardrobe. An AI engine synthesizes photorealistic images, allowing movement and details such as folds and ripples to be seen as if the user is really wearing the virtual clothing.

In October 2020, the Belarusian company VIPIT launched on Product Hunt with the Good Style app. Now users can virtually try on clothes before ordering in the online store. VIPIT launched the app in the US market in partnership with Shein. Now the startup has entered the CIS market. Moreover, VIPIT works in collaboration with Belarusian brands in the Belarusian market.

Buying books, electronics or food online is quick and convenient. However even the more e-commerce savvy consumers may hesitate to buy clothes on the Internet. The reason is simple -- there's no virtual fitting room. But don't worry, AI is working on that. Achieving accurate 3D human digitalization requires accurate unclothed human body modelling along with plenty of labelled 3D garment data.

Just as Skype revolutionized the way we communicate, and TransferWise found a way to break worn patterns in the financial world, Estonia is about to make a transforming difference in the dynamic field of robotics too. Besides the country being a Mecca for data and tech-driven startups, more and more Estonians, in addition to excelling in code writing and software development, are thrusting their hands deep into the wiring and metal of robots. Imagine a vacuum-cleaner-sized, yellow'turtle' diving elegantly down hundreds of metres to probe ship wrecks, thus gathering valuable data for archaeologists and maybe even finding lost treasures buried somewhere deep under the sea. But this intelligent'turtle' is actually a robot. Equipped with a camera and a searchlight, the relatively cheap and highly manoeuvrable U-CAT (Underwater Curious Archaeology Turtle) locomotion principle is similar to that of the sea turtles of the natural world.