RECON Labs to showcase advanced 3D implicit neural representation at CES 2023

SEOUL, South Korea, Dec. 28, 2022 /PRNewswire/ -- RECON Labs, an AI-based generative 3D content startup will attend CES 2023, presenting its advanced 3D content generation technology and applications (incl. AR commerce solution) at the global tech-industry trade show, held from January 5 to 8 in Las Vegas.

RECON Labs to showcase advanced 3D implicit neural representation at CES 2023

RECON Labs booth will feature:

  • 3D reconstruction technology, MetaRECON
  • AR Commerce solution, PlicAR
  • View Synthesis technology

MetaRECON is a technology that can automatically generate 3D models from photos or videos. This AI based 3D reconstruction algorithm has evolved with a preference to field adaptation, and now creates more realistic, high-quality 3D models.

The company's recently launched 3D commerce solution, PlicAR is based on MetaRECON, allows an easier use for online sellers to provide 360° product views and augmented reality experience. After taking photos or a video shot with a smartphone, only thing users need to do is to upload files on PlicAR. A lot of clients of PlicAR such as global e-commerce platform, furniture manufacturers, and home appliance companies already have been fascinated by high-quality 3D models and ease of use.

Not only objects but various spaces can be reconstructed with NeRF(Neural Radiance Field) technology. RECON Lab's View Synthesis technology enables to view wherever users want by space rendering from collected video sources. This cloud-based SaaS platform offers many benefits, including flexibility, scalability, and cost savings.

Seonghoon Ban, the CEO of RECON Labs, said that "Our goal is to make it easy for anyone to create desired objects and spaces in 3D or reconstruct them from a new perspective so that they can be used in the AR/VR environment.", "We are thrilled to showcase our new technology and look forward having an opportunity to cooperate with incredible companies or institutions in various fields."

SOURCE RECON Labs

For further information: Sohee Yoon, hazel@reconlabs.ai