MATERIAL MAP IDENTIFICATION AND AUGMENTATION

Patent №

US 11,488,342

Granted

2022-11-01

Filed 2021

Owner

ADOBE INC.

Lab

AI components

5

ml · vision · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17332708

Embodiments of the technology described herein, make unknown material-maps in a Physically Based Rendering (PBR) asset usable through an identification process that relies, at least in part, on image analysis. In addition, when a desired material-map type is completely missing from a PBR asset the technology described herein may generate a suitable synthetic material map for use in rendering. In one aspect, the correct map type is assigned using a machine classifier, such as a convolutional neural network, which analyzes image content of the unknown material map and produce a classification. The technology described herein also correlates material maps into material definitions using a combination of the material-map type and similarity analysis. The technology described herein may generate synthetic maps to be used in place of the missing material maps. The synthetic maps may be generated using a Generative Adversarial Network (GAN).

Machine learningVisionKnowledge representationPlanningAI hardwareG06T 15/04G06T 17/00G06F 18/22G06F 18/2321G06N 3/0464G06N 3/0475G06N 3/09G06N 3/094+5 more

AI classification

Machine learning1.00
Vision1.00
AI hardware0.99
Planning0.99
Knowledge representation0.92
Natural language0.00
Speech0.00
Evolutionary computation0.00

Ownership

ADOBE INC.

assignment · 567920177

Assignors

SUNKAVALLI, KALYAN KRISHNA, HOLD-GEOFFROY, YANNICK, HASAN, MILOS, XU, ZEXIANG, YEH, YU-YING, CORAZZA, STEFANO

On an employer assignment, the assignors are typically the inventors.

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