US 2021/0241497 A1 · GENERATION OF CONTROLLED ATTRIBUTE-BASED IMAGES

Abstract

Embodiments of the present disclosure are directed towards generating images conditioned on a desired attribute. In particular, an attribute-based image generation system can use a directional-GAN architecture to generate images conditioned on a desired attribute. A latent vector and a desired attribute are received. A feature subspace is determined for the latent vector using a latent-attribute linear classifier trained to determine a relationship between the latent vector and the desired attribute. An image is generated using the latent vector such that the image contains the desired attribute. In embodiments, where the feature space differs from a desired feature subspace, a directional vector is applied to the latent vector that shifts the latent vector from the feature subspace to the desired feature subspace. This modified latent vector is then used during generation of the image.

Claims20

Dependent claims

A computer-implemented method, comprising:

receiving a latent vector and a first desired attribute;
determining a feature subspace for the latent vector using one or more latent-attribute linear classifiers trained to determine a first relationship between the latent vector and the first desired attribute;
receiving a second desired attribute;
determining a second relationship between the latent vector and the second desired attribute;
and
generating an image, using the latent vector, wherein the image contains the desired first and second desired attributes.

3 more elements

Dependencies are inferred from the claim text.

Generation of controlled attribute-based images

Life of this patent

Generation of controlled attribute-based images

Life of this patent

Abstract

Claims20