Structure Masking Network: A two-scale convolutional neural network (CNN) trained to extract contour masks of objects of interest from input 2D images. Point Cloud Generation: The contour masks are ...

The process begins with capturing multiple 2D images of a scene. These images are then fed into a neural network, which processes the data to infer the 3D structure of the scene. The network outputs a ...

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 from the McKelvey School of ...

Disney Research has developed an algorithm which can generate 3D computer models from 2D images in great detail, sufficient, it says, to meet the needs of video game and film makers.

The challenge of how to infer 3D information from 2D images has been tackled both from the perspective of synthesising EM images to create a 3D structural model (Milne et al., 2013), and in the ...

Now that 2D images so easy to create converting them to 3D models seems to be the next logical step. DreamGaussian represents a significant advancement in the field of 3D content creation ...

The Depth Pro system doesn't bother with all that though, yet is able to generate a detailed 3D depth map at 2.25 megapixels from a single image in 0.3 seconds via a standard graphics processing unit.