LEARNING NEURAL REFLECTANCE SHADERS FROM IMAGES

LEARNING NEURAL REFLECTANCE SHADERS FROM IMAGES

Described herein are techniques for learning neural reflectance shaders from images. A set of one or more machine learning models can be trained to optimize an illumination latent code and a set of reflectance latent codes for an object within a set of input images. A shader can then be generated ba...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Wang, Shenlong, Zhang, Kai, Ummenhofer, Benjamin, Agrawal, Sanskar, Koltun, Vladlen, Lao, Yixing, Richter, Stephan
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Beschreibung
Zusammenfassung:Described herein are techniques for learning neural reflectance shaders from images. A set of one or more machine learning models can be trained to optimize an illumination latent code and a set of reflectance latent codes for an object within a set of input images. A shader can then be generated based on a machine learning model of the one or more machine learning models. The shader is configured to sample the illumination latent code and the set of reflectance latent codes for the object. A 3D representation of the object can be rendered using the generated shader.