Patent ID: 11934958
Assignee: ADOBE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 13:
14. A computer-implemented method comprising:
modifying a foreground region of an image generated from a noise-to-image generative adversarial neural network (GAN) to generate a foreground-modified image;
generating a pruned GAN by pruning channels of the noise-to-image GAN based on gradients for outgoing channel weights corresponding to the channels upon a backpropagation of a differentiable loss between the image and the foreground-modified image within the noise-to-image GAN;
utilizing the pruned GAN to generate an additional image; and
generating a distilled GAN from the pruned GAN by learning parameters for the distilled GAN that cause outputs of the distilled GAN to mimic outputs of the noise-to-image GAN by utilizing at least one knowledge distillation loss between a foreground mask from the image and an additional foreground mask from the additional image.