US 2021/0279841 A1 · TECHNIQUES TO USE A NEURAL NETWORK TO EXPAND AN IMAGE

Abstract

Apparatuses, systems, and techniques for texture synthesis from small input textures in images using convolutional neural networks. In at least one embodiment, one or more convolutional layers are used in conjunction with one or more transposed convolution operations to generate a large textured output image from a small input textured image while preserving global features and texture, according to various novel techniques described herein.

Claims31

Dependent claims

A processor comprising:

one or more circuits to use one or more neural networks to generate a second image based, at least in part, on one or more feature maps corresponding to a first image, wherein the first image is smaller than the second image.

Dependencies are inferred from the claim text.

Facts

Application

16/813,589Filed 9 Mar 2020

Published

9 Sep 2021

Term ends

Not estimatedThe source records don’t support an estimate.

Classification22 codes

G06T 3/4038
Scaling of whole images or parts thereof, e.g. expanding or contracting: image mosaicing, e.g. composing plane images from plane sub-images
G06N 3/045
Architecture, e.g. interconnection topology: combinations of networks
G06N 3/0455
Combinations of networks: auto-encoder networks; Encoder-decoder networks
G06N 3/0464
Architecture, e.g. interconnection topology: convolutional networks [CNN, ConvNet]

Techniques to use a neural network to expand an image

Life of this patent

Techniques to use a neural network to expand an image

Life of this patent

Abstract

Claims31