公开(公告)号：US20240412429A1

公开(公告)日：2024-12-12

申请号：US18332163

申请日：2023-06-09

Applicant: ADOBE INC.

Inventor： Wei-An Lin ,  Hui Qu ,  Siavash Khodadadeh ,  Kevin Duarte ,  Surabhi Sinha ,  Ratheesh Kalarot ,  Shabnam Ghadar

IPC: G06T11/60 ,  G06V10/82 ,  G06V40/16

Abstract: Systems and methods for editing multiple attributes of an image are described. Embodiments are configured to receive input comprising an image of a face and a target value of an attribute of the face to be modified; encode the image using an encoder of an image generation neural network to obtain an image embedding; and generate a modified image of the face having the target value of the attribute based on the image embedding using a decoder of the image generation neural network. The image generation neural network is trained using a plurality of training images generated by a separate training image generation neural network, and the plurality of training images include a first synthetic image having a first value of the attribute and a second synthetic image depicting a same face as the first synthetic image with a second value of the attribute.

公开(公告)号：US20240152757A1

公开(公告)日：2024-05-09

申请号：US18053641

申请日：2022-11-08

Applicant: ADOBE INC.

Inventor： Zohreh Azizi ,  Surabhi Sinha ,  Siavash Khodadadeh

IPC: G06N3/08 ,  G06N3/04 ,  G06T5/00 ,  G06V40/16

CPC classification number: G06N3/082 ,  G06N3/0454 ,  G06T5/005 ,  G06V40/172

Abstract: Methods for image processing are described. Embodiments of the present disclosure identifies an image generation network that includes an encoder and a decoder; prunes channels of a block of the encoder; prunes channels of a block of the decoder that is connected to the block of the encoder by a skip connection, wherein the channels of the block of the decoder are pruned based on the pruned channels of the block of the encoder; and generates an image using the image generation network based on the pruned channels of the block of the encoder and the pruned channels of the block of the decoder.