公开(公告)号：US11107257B1

公开(公告)日：2021-08-31

申请号：US16052480

申请日：2018-08-01

Applicant: ADOBE INC.

Inventor： Stephen Diverdi ,  Jose Ignacio Echevarria Vallespi ,  Jingwan Lu

IPC: G06T11/00 ,  G06T7/50 ,  G06T7/90 ,  G06K9/62 ,  G06F3/048 ,  G06F3/0484

Abstract: Disclosed herein are embodiments of systems and computer-implemented methods for extracting a set of discrete colors from an input image. A playful palette may be automatically generated from the set of discrete colors, where the playful palette contains a gamut limited to a blend of the set of discrete colors. A representation of the playful palette may be displayed on a graphical user interface of an electronic device. In a first method, an optimization may be performed using a bidirectional objective function comparing the color gamut of the input image and rendering of a candidate playful palette. Initial blobs may be generated by clustering. In a second method, color subsampling may be performed from the image, and a self-organizing map (SOM) may be generated. Clustering the SOM colors may be performed, and each pixel of the SOM may be replaced with an average color value to generate a cluster map.

公开(公告)号：US11288771B2

公开(公告)日：2022-03-29

申请号：US16861688

申请日：2020-04-29

Applicant: ADOBE INC.

Inventor： Yulun Zhang ,  Zhifei Zhang ,  Jose Ignacio Echevarria Vallespi ,  Zhaowen Wang ,  Stephen Diverdi

IPC: G06T3/40

Abstract: Systems and methods for texture hallucination with a large upscaling factor are described. Embodiments of the systems and methods may receive an input image and a reference image, extract an upscaled feature map from the input image, match the input image to a portion of the reference image, wherein a resolution of the reference image is higher than a resolution of the input image, concatenate the upscaled feature map with a reference feature map corresponding to the portion of the reference image to produce a concatenated feature map, and generate a reconstructed image based on the concatenated feature map using a machine learning model trained with a texture loss and a degradation loss, wherein the texture loss is based on a high frequency band filter, and the degradation loss is based on a downscaled version of the reconstructed image.

公开(公告)号：US20210342974A1

公开(公告)日：2021-11-04

申请号：US16861688

申请日：2020-04-29

Applicant: ADOBE INC.

Inventor： Yulun Zhang ,  Zhifei Zhang ,  Jose Ignacio Echevarria Vallespi ,  Zhaowen Wang ,  Stephen Diverdi

IPC: G06T3/40 ,  G06N20/00

Abstract: Systems and methods for texture hallucination with a large upscaling factor are described. Embodiments of the systems and methods may receive an input image and a reference image, extract an upscaled feature map from the input image, match the input image to a portion of the reference image, wherein a resolution of the reference image is higher than a resolution of the input image, concatenate the upscaled feature map with a reference feature map corresponding to the portion of the reference image to produce a concatenated feature map, and generate a reconstructed image based on the concatenated feature map using a machine learning model trained with a texture loss and a degradation loss, wherein the texture loss is based on a high frequency band filter, and the degradation loss is based on a downscaled version of the reconstructed image.