A neural field network can create a continuous 3D model from a limited number of 2D images, and it does it without being trained on other samples.

Researchers at NVIDIA have come up with a clever machine learning technique for taking 2D images and fleshing them out into 3D models.

Microscopic images of 2D materials were processed via three deep-learning architectures for classification, segmentation, and detection.

Nvidia Research and others collaborated to create the DIB-R framework that can predict 3D properties from 2D images to create 3D models.

Adobe's Large Reconstruction Model can generate 3D models from 2D images in 5 seconds, representing a major advance in 3D reconstruction.

Nvidia Corp. today revealed that it has created a new deep learning application that can take a standard 2D image and transform it into an extremely realistic 3D model, one that can be visualized ...

A new AI tool harnessing machine learning is capable of converting 2D images into 3D models that can be taken into Blender and other similar ...

Apple's Machine Learning Research wing has developed a foundational AI model "for zero-shot metric monocular depth estimation." Depth Pro enables high-speed generation of detailed 3D depth maps ...