公开(公告)号：US11663775B2

公开(公告)日：2023-05-30

申请号：US17233861

申请日：2021-04-19

Applicant: ADOBE INC.

Inventor： Akshat Dave ,  Kalyan Krishna Sunkavalli ,  Yannick Hold-Geoffroy ,  Milos Hasan

IPC: G06T15/50 ,  G06T15/00 ,  G06N3/08 ,  G06T15/04

CPC classification number: G06T15/506 ,  G06N3/08 ,  G06T15/005 ,  G06T15/04

Abstract: Methods, system, and computer storage media are provided for generating physical-based materials for rendering digital objects with an appearance of a real-world material. Images depicted the real-world material, including diffuse component images and specular component images, are captured using different lighting patterns, which may include area lights. From the captured images, approximations of one or more material maps are determined using a photometric stereo technique. Based on the approximations and the captured images, a neural network system generates a set of material maps, such as a diffuse albedo material map, a normal material map, a specular albedo material map, and a roughness material map. The material maps from the neural network may be optimized based on a comparison of the input images of the real-world material and images rendered from the material maps.

公开(公告)号：US20220335682A1

公开(公告)日：2022-10-20

申请号：US17233861

申请日：2021-04-19

Applicant: ADOBE INC.

Inventor： Akshat Dave ,  Kalyan Krishna Sunkavalli ,  Yannick Hold-Geoffroy ,  Milos Hasan

IPC: G06T15/50 ,  G06T15/04 ,  G06N3/08 ,  G06T15/00

Abstract: Methods, system, and computer storage media are provided for generating physical-based materials for rendering digital objects with an appearance of a real-world material. Images depicted the real-world material, including diffuse component images and specular component images, are captured using different lighting patterns, which may include area lights. From the captured images, approximations of one or more material maps are determined using a photometric stereo technique. Based on the approximations and the captured images, a neural network system generates a set of material maps, such as a diffuse albedo material map, a normal material map, a specular albedo material map, and a roughness material map. The material maps from the neural network may be optimized based on a comparison of the input images of the real-world material and images rendered from the material maps.