Nvidia corporation (20240257437). REAL-TIME NEURAL APPEARANCE MODELS simplified abstract

REAL-TIME NEURAL APPEARANCE MODELS

Organization Name

nvidia corporation

Inventor(s)

Karthik Vaidyanathan of Oakland CA (US)

Alex John Bauld Evans of London (GB)

[[:Category:Jan Nov�k of Dobrichovice (CZ)|Jan Nov�k of Dobrichovice (CZ)]][[Category:Jan Nov�k of Dobrichovice (CZ)]]

Andrea Weidlich of Montreal (CA)

Fabrice Pierre Armand Rousselle of Ostermundigen (CH)

Aaron Eliot Lefohn of Kirkland WA (US)

Franz Petrik Clarberg of Lund (SE)

Benedikt Bitterli of Kirkland WA (US)

Tizian Lucien Zeltner of Zürich (CH)

REAL-TIME NEURAL APPEARANCE MODELS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240257437 titled 'REAL-TIME NEURAL APPEARANCE MODELS

Abstract: Embodiments of the present disclosure relate to real-time neural appearance models. Using a neural decoder, scenes are rendered in real-time with complex material appearance previously reserved for offline use. Learned hierarchical textures representing the material properties are encoded as latent codes. When a ray is cast and intersects with geometry in the scene, the intersection point is mapped to one of the latent codes. The latent code is interpreted using neural decoders, which produce reflectance values and importance-sampled directions that can be used to determine a pixel color.

• Simplified Explanation:

This technology involves using neural appearance models to render scenes in real-time with complex material appearance, typically used offline.

• Key Features and Innovation:

- Utilizes neural decoders to render scenes with intricate material appearance in real-time. - Encodes material properties as latent codes for efficient processing. - Maps intersection points to latent codes to determine pixel colors. - Produces reflectance values and importance-sampled directions for accurate rendering.

• Potential Applications:

- Real-time rendering in video games and virtual reality environments. - Architectural visualization for design and construction. - Product design and prototyping for realistic material representation.

• Problems Solved:

- Enables real-time rendering of complex material appearance. - Improves efficiency in processing material properties. - Enhances the realism of virtual scenes and objects.

• Benefits:

- Enhanced visual quality in real-time rendering. - Faster processing of material properties for efficient rendering. - Improved user experience in interactive applications.

• Commercial Applications:

"Real-Time Neural Appearance Models for Enhanced Visual Rendering in Video Games and Virtual Reality Environments"

• Questions about Neural Appearance Models:

1. How do neural appearance models differ from traditional rendering techniques? - Neural appearance models use learned hierarchical textures and latent codes to represent material properties, allowing for real-time rendering with complex appearance.

2. What are the advantages of using neural decoders in rendering scenes? - Neural decoders can produce reflectance values and importance-sampled directions, leading to more accurate and realistic pixel colors in real-time rendering.

Original Abstract Submitted

embodiments of the present disclosure relate to real-time neural appearance models. using a neural decoder, scenes are rendered in real-time with complex material appearance previously reserved for offline use. learned hierarchical textures representing the material properties are encoded as latent codes. when a ray is cast and intersects with geometry in the scene, the intersection point is mapped to one of the latent codes. the latent code is interpreted using neural decoders, which produce reflectance values and importance-sampled directions that can be used to determine a pixel color.