Intel corporation (20240221277). LEARNING NEURAL REFLECTANCE SHADERS FROM IMAGES simplified abstract

LEARNING NEURAL REFLECTANCE SHADERS FROM IMAGES

Organization Name

intel corporation

Inventor(s)

Benjamin Ummenhofer of Unterhaching (DE)

Shenlong Wang of Santa Clara CA (US)

Sanskar Agrawal of Santa Clara CA (US)

Yixing Lao of Santa Clara CA (US)

Kai Zhang of Santa Clara CA (US)

Stephan Richter of Neubiberg (DE)

Vladlen Koltun of Santa Clara CA (US)

LEARNING NEURAL REFLECTANCE SHADERS FROM IMAGES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240221277 titled 'LEARNING NEURAL REFLECTANCE SHADERS FROM IMAGES

• • Simplified Explanation:**

This patent application describes techniques for learning neural reflectance shaders from images, where machine learning models are trained to optimize illumination and reflectance latent codes for objects in input images. A shader is then generated based on these models to render a 3D representation of the object.

• • Key Features and Innovation:**
• Training machine learning models to optimize illumination and reflectance latent codes for objects in images.
• Generating shaders based on these models to render 3D representations of objects.

• • Potential Applications:**
• Computer graphics
• Virtual reality
• Augmented reality

• • Problems Solved:**
• Enhancing the realism of rendered objects
• Improving the efficiency of shader generation

• • Benefits:**
• More realistic 3D renderings
• Faster shader generation process

• • Commercial Applications:**
• "Neural Reflectance Shader Learning for Enhanced 3D Rendering in Virtual Reality and Augmented Reality Applications"

• • Prior Art:**

Prior art related to this technology can be found in research papers on machine learning in computer graphics and rendering techniques.

• • Frequently Updated Research:**

Stay updated on advancements in machine learning models for shader generation and 3D rendering techniques.

• • Questions about Neural Reflectance Shader Learning:**

1. How does this technology improve the visual quality of 3D renderings? 2. What are the potential limitations of using machine learning models for shader generation in computer graphics?

Original Abstract Submitted

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.