3DLook releases 3D generation to improve e-shopping

V2.0 will improve shopping experience for customers; solve fit and sizing problems, increase conversion rates, and lower return rates. The revolutionary upgrade to their product SAIA 3D instantly generates 3D body models from the two front and side facing photos of consumers that can be taken by any smartphone. Version 2.0 produces more accurate and realistic 3D models which can also be textured and the new releases’ approach significantly reduces the computation time of the 3D model generation. Additionally, 3DLook has made its avatars ready for animation, a process known as rigging which is targeted to retailers and brands focused on athletics, athleisure and virtual dressing.

The company has already partnered with CLO, a leading software solution for virtual garment rendering, and together has built a virtual try-on solution so that consumers can visualise how a product looks on them in 3D or augmented reality (AR) before purchase. The goal is to reduce the likelihood of a return and encourage shoppers to spend more time on a website, increasing customer engagement 3DLook said in a press release.

"The company is focused on revolutionising how the industry as a whole looks at sizing and fit from a product creation level. With SAIA 3D V2.0, we are giving brands and retailers the tools and data necessary to stay competitive against Amazon who late last year bought competitor Body Labs for a reported $50-100 million," said Vadim Rogovskiy, founder and CEO, 3DLook, said.

Separately, Rogovskiy also hopes that this technology will make a dent in the level of waste that plagues the industry by contributing the insight desperately needed to enable a much deeper level of customisation.

3DLook has put an enormous amount of time and focus on the user experience. The technology works on any background, processing time in seconds, and users can choose to have someone take a photo of them or take a selfie in a full-length mirror. Unlike other scan technologies, consumers do not have to disrobe. The algorithms are trained on a vast proprietary dataset of fully dressed people. 

Rogovskiy believes there is a huge opportunity to respond to the consumer's demand for customized apparel and more personalised shopping experience. "Understanding a consumer's unique body data is the first step to understanding what the consumer might actually want to buy. The online shopping experience is going to look very different in the next few years. Companies like Amazon are already working on their own solutions while other online retailers will have to look for opportunities to compete against the corporation. I'm glad that we are part of this exciting revolution that can help e-commerce apparel businesses of any size to grow," explained Rogovskiy. (RR)

Fibre2Fashion News Desk – India