Using AI to create 3D spaces from 2D images

The potential to improve navigation for autonomous vehicles has emerged with research from NC State University (NCSU) that uses artificial intelligence (AI) programs to map 3D spaces using 2D images captured by multiple cameras.

Called Multi-View Attentive Contextualization (MvACon), the method is a plug-and-play supplement that can be used in conjunction with existing vision transformer AIs to improve how automated vehicles map 3D spaces.

“Most autonomous vehicles use powerful AI programs called vision transformers to take 2D images from multiple cameras and create a representation of the 3D space around the vehicle,” said Tianfu Wu, an associate professor of electrical and computer engineering at NCSU. “However, while each of these AI programs takes a different approach, there is still substantial room for improvement.

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