Fashion has always been at the forefront of innovation from the invention of the sewing machine to the rise of e-commerce. Like tech, fashion is forward-looking and cyclical.
Fashion technology is defined as any cutting-edge technology that develops cutting-edge tools for the fashion industry, whether to boost production or consumption.
Depending on the technology’s function, it could be used by designers, manufacturers, merchants, and customers. As new technologies become available, we should expect fashion tech to grow more mainstream.
Impact of AI In Fashion Industry
The issues and concerns that persist in the traditional garment ecosystem highlight the need to use AI in fashion to automate, innovate, and reinvent business activities like trend spotting, cloth design, manufacturing, transportation, retailing, and selling. Here are some prime ways that artificial intelligence is transforming the future of fashion.
Apparel designing
Technology is being used by fashion firms of all sizes and specialties to better understand their clients than ever before. Fashion firms are utilizing technology to better understand client wants and produce better garments thanks to more sophisticated data collection.
Fashion design that is AI-powered is based on the customer’s selected colors, textures, and other stylistic preferences. Before brands can rely on AI-only designers, further research and development are required. However, artificial intelligence is already assisting brands in the creation and iteration of their designs. The application of artificial intelligence is shaping the way we will get dressed, from 3D avatars to closet consultants.
Size Recommendations
In the fashion business, 3D scanning is already being utilized to correctly analyze body proportions, provide sizing recommendations, and sell goods in a more focused manner. This is due to the fact that clothing size specifications and accompanying measures vary greatly from one brand to the next. As a result, buyers frequently order and return multiple sizes of the same item of apparel, reducing earnings for online sellers. As a result, the fashion industry is increasingly resorting to solutions that advise buyers on the proper size from the start, resulting in fewer returns.
The body’s measurements are precisely replicated by the 3D avatar. As a result, it provides correct and individualized fit assistance automatically, which is crucial for improving the online shopping experience and lowering product return rates. Size recommendation uses AI-powered technology to match consumers’ body shapes to garment SKUs, allowing them to buy apparel in the size that best fits them.
Manufacturing & supply chain process
Fashion brands are now able to identify fast-changing fashion trends and get the latest fashion accessories to store shelves faster than the “traditional” fashion shop, thanks to AI and machine learning capabilities.
Intelligent forecasting systems are another area where businesses should consider employing AI to reduce inventory and shipping expenses. For example, computers can be taught to take different behaviors based on the best feasible decision in a given situation via reinforcement learning. Today, AI can assist in estimating approximate product amounts to order and analyzing inventories in stores based on historical sales data.
Virtual Mirrors
Virtual mirrors incorporate computer vision and augmented https://www.tagxdata.com/impact-of-ai-and-data-annotation-in-fashion-industryto allow users to try on different outfits in different sizes and colors without having to change and use the fitting room. A customer scans the code of a clothing item and the virtual mirror displays the image of the person in the outfit. Virtual mirrors use gesture recognition algorithms to recognize user commands and they also feature a virtual cart.
Coupled with augmented reality, image recognition (AI) technology can be used to analyze pieces of clothing and automatically generate an image of the garment on a person of any size, shape, or wearing any kind of shoes. Some companies are already experimenting with smart fitting rooms to allow customers in-store to immediately view themselves in the clothes they pick, and swap those clothes for different styles, without even changing.
Personalized shopping
One of the biggest ways it can help drive growth is through leveraging information about customers and thus creating a personalized shopping experience. AI can help computers identify images and recommend those products online which the customer is more likely to buy.
Through AI-powered personal stylist apps, interested customers are allowed to browse clothes online to click pictures of their clothes. By offering these images as inputs, the app will suggest the perfect style in accordance with the customer’s body type, complexion and style while also maintaining the current fashion trends. Computer vision-based AI models can make this a reality with the support of high-quality annotation.
Visual Product Discovery
Visual search, another AI in fashion retail trends, makes it easier than ever for shoppers to find and purchase the things they want. Most buyers simply snap and submit a photo of the goods they want, and AI recognizes the captured object, or at least similar products, across a variety of websites and merchants.
People occasionally come upon something unusual, but when they go online to look for it later, they are unable to locate it. Fashion sellers should make sure that their product images are high-quality and up-to-date in order to take advantage of visual search and make their products more discoverable.
Data Annotation for Fashion AI
While AI will not be able to completely replace people, it will present a huge potential to leverage insight into customer preferences in order to align supply and demand, deliver a personalized customer experience, and push all the way to the supply chain in order to generate superior products.
Furthermore, high-quality machine learning training data is necessary to improve AI performance so that more and more data may be fed into the model for more exact predictions in real-life settings. Another problem for AI startups is generating relevant training data.
However, data-labeling firms like TagX are working around the clock to accommodate the demand for such information and to assist AI firms in developing more advanced systems for the fashion and retail industries.
TagX is working with industry innovators to create training datasets and annotations for fashion AI. Using our knowledge, expertise, and proprietary annotation tools, we can fulfill the demands of any computer vision project.
For thousands of individual clothing items require the assistance of controlled teams of professional annotators for accurate tagging. TagX can ensure that your information captures the complex picture of today’s fashion choices by using labeling techniques like Bounding box annotation, polygon annotation, semantic segmentation, etc.
No comments yet