Google Inc.

Adobe, Inc.

Yotam Nitzan

Inbar Mosseri

Orly Liba

Kfir Aberman

Yael Pritch Knaan

Qiurui He

Yossi Gandelsman

Michal Yarom

Elya Shechtman

Richard Zhang

Taesung Park

Junyan Zhu

Michaël Gharbi

Systems and methods for image generation include obtaining an input image and an attribute value representing an attribute of the input image to be modified; computing a modified latent vector for the input image by applying the attribute value to a basis vector corresponding to the attribute in a latent space of an image generation network; and generating a modified image based on the modified latent vector using the image generation network, wherein the modified image includes the attribute based on the attribute value.

Product of variations in image generative models

Systems and methods for identifying a personalized prior within a generative model's latent vector space based on a set of images of a given subject. In some examples, the present technology may further include using the personalized prior to confine the inputs of a generative model to a latent vector space associated with the given subject, such that when the model is tasked with editing an image of the subject (e.g., to perform inpainting to fill in masked areas, improve resolution, or deblur the image), the subject's identifying features will be reflected in the images the model produces.

Facial image editing and enhancement using a personalized prior

Growing community of inventors

Tel Aviv, Israel

Yotam Nitzan