公开(公告)号：US20240198720A1

公开(公告)日：2024-06-20

申请号：US18084361

申请日：2022-12-19

Applicant: Adobe Inc.

Inventor： Daichi ITO ,  Gavin Stuart Peter MILLER

IPC: B44F7/00 ,  B44C1/16 ,  G06K15/02

CPC classification number: B44F7/00 ,  B44C1/16 ,  G06K15/021

Abstract: Methods and systems are provided for a three-dimensional effect on the edge of a multi-page document (e.g., a book). In one embodiment, a first set of image slices associated with a left-eye image is printed on a first side of long pages of a multi-page document. The first set of image slices printed adjacent to edges of the long pages. A second set of image slices associated with a right-eye image is printed on a second side of the long pages of the multi-page document. The second set of image slices printed adjacent to the edges of the long pages. Thereafter, the multi-page document is created by interleaving the long pages with short pages to enable visibility of the first set of image slices and the second set of image slices printed adjacent to the edges of the long pages.

公开(公告)号：US20210158139A1

公开(公告)日：2021-05-27

申请号：US16691110

申请日：2019-11-21

Applicant: ADOBE INC.

Inventor： Long MAI ,  Yannick HOLD-GEOFFROY ,  Naoto INOUE ,  Daichi ITO ,  Brian Lynn PRICE

IPC: G06N3/08 ,  G06T15/80 ,  G06T15/50 ,  G06T5/50

Abstract: Embodiments of the present invention provide systems, methods, and non-transitory computer storage media for generating an ambient occlusion (AO) map for a 2D image that can be combined with the 2D image to adjust the contrast of the 2D image based on the geometric information in the 2D image. In embodiments, using a trained neural network, an AO map for a 2D image is automatically generated without any predefined 3D scene information. Optimizing the neural network to generate an estimated AO map for a 2D image requires training, testing, and validating the neural network using a synthetic dataset comprised of pairs of images and ground truth AO maps rendered from 3D scenes. By using an estimated AO map to adjust the contrast of a 2D image, the contrast of the image can be adjusted to make the image appear lifelike by modifying the shadows and shading in the image based on the ambient lighting present in the image.

公开(公告)号：US20240290022A1

公开(公告)日：2024-08-29

申请号：US18176267

申请日：2023-02-28

Applicant: ADOBE INC.

Inventor： Yijun LI ,  Yannick HOLD-GEOFFROY ,  Manuel Rodriguez Ladron DE GUEVARA ,  Jose Ignacio Echevarria VALLESPI ,  Daichi ITO ,  Cameron Younger SMITH

IPC: G06T13/40 ,  G06N3/0455 ,  G06N3/0895

CPC classification number: G06T13/40 ,  G06N3/0455 ,  G06N3/0895

Abstract: Avatar generation from an image is performed using semi-supervised machine learning. An image space model undergoes unsupervised training from images to generate latent image vectors responsive to image inputs. An avatar parameter space model undergoes unsupervised training from avatar parameter values for avatar parameters to generate latent avatar parameter vectors responsive to avatar parameter value inputs. A cross-modal mapping model undergoes supervised training on image-avatar parameter pair inputs corresponding to the latent image vectors and the latent avatar parameter vectors. The trained image space model generates a latent image vector from an image input. The trained cross-modal mapping model translates the latent image vector to a latent avatar parameter vector. The trained avatar parameter space model generates avatar parameter values from the latent avatar parameter vector. The latent avatar parameter vector can be used to render an avatar having features corresponding to the input image.