Samsung electronics co., ltd. (20240135632). METHOD AND APPRATUS WITH NEURAL RENDERING BASED ON VIEW AUGMENTATION simplified abstract

METHOD AND APPRATUS WITH NEURAL RENDERING BASED ON VIEW AUGMENTATION

Organization Name

samsung electronics co., ltd.

Inventor(s)

Young Chun Ahn of Suwon-si (KR)

Nahyup Kang of Suwon-si (KR)

Seokhwan Jang of Suwon-si (KR)

Jiyeon Kim of Suwon-si (KR)

METHOD AND APPRATUS WITH NEURAL RENDERING BASED ON VIEW AUGMENTATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240135632 titled 'METHOD AND APPRATUS WITH NEURAL RENDERING BASED ON VIEW AUGMENTATION

Simplified Explanation

The patent application describes a method and apparatus for neural rendering based on view augmentation. The method involves training a neural scene representation (NSR) model using original training images of a target scene, generating augmented images by warping the original training images, performing background-foreground segmentation on the images to generate segmentation masks, and training the NSR model for volume rendering of the target scene.

• Neural rendering based on view augmentation:

 - Involves training a neural scene representation model using original and augmented images of a target scene.
 - Utilizes background-foreground segmentation to improve the rendering process.
 - Enables volume rendering of the target scene by the trained NSR model.

Potential Applications

This technology can be applied in various fields such as virtual reality, augmented reality, medical imaging, and computer graphics for realistic scene rendering and visualization.

Problems Solved

- Improved rendering quality and accuracy. - Efficient volume rendering of complex scenes. - Seamless integration of foreground and background elements in rendered images.

Benefits

- Enhanced visual experience for users. - Faster rendering process. - More realistic and immersive virtual environments.

Potential Commercial Applications

"Neural Rendering for Enhanced Virtual Reality Experiences"

Possible Prior Art

There may be prior art related to neural rendering techniques, image augmentation methods, and scene representation models in the field of computer graphics and artificial intelligence.

What are the potential limitations of this technology in real-world applications?

Potential limitations of this technology in real-world applications may include: - Computational complexity and resource requirements for training and rendering. - Accuracy and generalization of the trained NSR model for different types of scenes. - Integration with existing rendering pipelines and software platforms.

How does this technology compare to traditional rendering methods in terms of efficiency and quality?

This technology offers advantages in terms of efficiency and quality compared to traditional rendering methods by leveraging neural networks for scene representation and view augmentation. It can provide more realistic and detailed renderings while potentially reducing the manual effort required for scene setup and rendering.

Original Abstract Submitted

a method and apparatus for neural rendering based on view augmentation are provided. a method of training a neural scene representation (nsr) model includes: receiving original training images of a target scene, the original training images respectively corresponding to base views of the target scene; generating augmented images of the target scene by warping the original training images, the augmented images respectively corresponding to new views of the target scene; performing background-foreground segmentation on the original training images and the augmented images to generate segmentation masks; and training a neural scene representation (nsr) model to be configured for volume rendering of the target scene by using the original training images, the augmented images, and the segmentation masks.