CPC G06T 3/00 (2013.01) [G06N 3/045 (2023.01); G06T 3/04 (2024.01); G06T 5/50 (2013.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06T 2207/30201 (2013.01)] | 18 Claims |
1. A method for generating a texturized image, the method comprising:
receiving a plurality of exemplar stylistic images;
training a first generative adversarial network (GAN) generator using transfer learning based on the received plurality of exemplar stylistic images;
receiving a plurality of training images;
training an encoder using the plurality of training images and another second GAN generator, the encoder trained for inversion by learning a posterior distribution of a fixed pre-trained GAN model, and the encoder using the fixed pre-trained GAN model as a decoder;
receiving an input image;
receiving an exemplar texture image;
generating, using the encoder, a first latent code vector representation based on the input image;
generating, using the first GAN generator, a second latent code vector representation based on the exemplar texture image;
blending the first latent code vector representation and the second latent code vector representation to obtain a blended latent code vector representation by concatenating a first predetermined amount of first sub-codes of the first latent code vector representation and a second predetermined amount of last sub-codes of the second latent code vector representation;
generating, by the first GAN generator, a texturized image based on the blended latent code vector representation; and
providing the texturized image as an output.
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