lands $8 million led by Hillhouse to create AI-generated fashion models – TechCrunch

With advances in machine learning, it is no longer uncommon to see algorithmically generated bodies that can move and speak authentically like real humans. The question now boils down to whether startups offering such products can achieve a sustainable business model. Some of them have shown that potential and attracted investors., founded by a team of Chinese entrepreneurs who have spent years studying and working abroad, has just closed an $8 million Series A funding round led by Hillhouse Capital. GGV Capital and GSR Ventures also participated in the round.

The startup has found healthy demand from fashion e-commerce companies struggling to hire and pay models due to their growing number of stock units (SKUs) or styles, as consumer tastes become more popular. changing. Using the Generative Adversarial Network (GAN), ZMO has created a piece of software to help them create full virtual bodies of models by defining simple parameters such as face, height, skin color, body shape, and pose.

“Traditionally, the entire cycle of garment manufacturing can take two to three months, from design, fabric selection, pattern making, modeling to hitting the shelves,” says Ella Zhang, CEO and co-founder of ZMO, former Google engineer. and apple.

“We are flipping and shortening that process. [Customers] now you can try on a garment by putting it on a virtual model, which can go on the website. Once the orders come in, the eCommerce customer can start manufacturing,” he tells TechCrunch. “They can also test what kind of people would suit a certain product by trying it out on different virtual models.”

It’s no surprise that fashion e-commerce operators find ZMO and the like a cost-saving tool. Zhang says his company is in early talks with fast-fashion giant Shein, which releases 2,000 to 3,000 new products a day, about possible collaborations.

Screenshot from ZMO’s AI-generated video

We previously covered Surreal, a Sequoia-backed Shenzhen-based startup also working on synthetic media to replace humans in lifestyle photos and other business scenarios. The business attracted a surge in interest as the COVID-19 pandemic hit China’s e-commerce exporters, who were having difficulty finding foreign models as the country entered strict border controls.

In the future, ZMO also plans to apply GPT-3, which uses big data and deep learning to mimic the natural language patterns of humans, to create speech for models. As creepy as it sounds, the feature would make it easier for e-commerce businesses to quickly and cheaply produce TikTok videos for product promotion.

On average, e-commerce companies spend 3-5% of the annual gross value of their merchandise (a ballpark that measures sales, typically excluding returns and refunds) on photo shoots, according to Roger Yin, who he worked at Evernote and ran his own cross-company. cross-border e-commerce business before co-founding ZMO with Zhang.

“Images play a big role in driving eCommerce sales. The problem is that the [sales] the cycle is short but the cost of images is high,” Yin observes, adding that costs can be even higher for fashion companies with rapid style turnover. ZMO’s goal is to reduce the costs of photo shoots to 1% of the GMV.

Right now, 80% of ZMO’s customers are in China, but this year it is working to attract more users abroad using its new financial infusion. Operating with a team of 30 employees, the startup has 30 “medium and large” clients, including Tencent-backed Chicv, one of Shein’s numerous challengers, and more than 100 “small and medium” clients, such as dropshippers.

ZMO’s other co-founders include Ma Liqian, Ph.D. in computer vision who graduated from Belgium’s KU Leuven, and Yang Han, who previously worked in AI-driven style at Tencent and SenseTime.

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