Nvidia corporation (20240104689). APPLICATION PROGRAMMING INTERFACE TO ENABLE FRAME INTERPOLATION simplified abstract
Contents
- 1 APPLICATION PROGRAMMING INTERFACE TO ENABLE FRAME INTERPOLATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 APPLICATION PROGRAMMING INTERFACE TO ENABLE FRAME INTERPOLATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
APPLICATION PROGRAMMING INTERFACE TO ENABLE FRAME INTERPOLATION
Organization Name
Inventor(s)
Robert Thomas Pottorff of Layton UT (US)
Karan Sapra of San Jose CA (US)
Andrew Leighton Edelsten of Morgan Hill CA (US)
APPLICATION PROGRAMMING INTERFACE TO ENABLE FRAME INTERPOLATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104689 titled 'APPLICATION PROGRAMMING INTERFACE TO ENABLE FRAME INTERPOLATION
Simplified Explanation
The patent application describes apparatuses, systems, and techniques for processing image frames using a neural network-based frame interpolation method.
- An application programming interface (API) is utilized to enable frame interpolation using one or more neural networks.
- The technology aims to improve the quality of interpolated frames in video processing applications.
- By leveraging neural networks, the system can generate more realistic and visually appealing intermediate frames.
- The API allows developers to easily integrate the frame interpolation functionality into their applications.
- The innovation could potentially be used in video editing software, gaming graphics, and virtual reality applications.
Potential Applications
The technology could be applied in various fields such as video editing, gaming, virtual reality, and animation to enhance the visual quality of interpolated frames.
Problems Solved
The technology addresses the challenge of generating high-quality interpolated frames in video processing applications, improving the overall visual experience for users.
Benefits
The use of neural networks for frame interpolation results in more realistic and visually appealing intermediate frames, enhancing the quality of videos and graphics.
Potential Commercial Applications
The technology could find commercial applications in video editing software, gaming graphics engines, virtual reality platforms, and animation studios.
Possible Prior Art
One possible prior art in this field is the use of traditional frame interpolation techniques, which may not produce as high-quality results as neural network-based methods.
Unanswered Questions
How does the API handle different types of input frames for interpolation?
The article does not provide details on how the API manages various types of input frames, such as different resolutions or frame rates, for the interpolation process.
What computational resources are required to implement the neural network-based frame interpolation?
The article does not mention the computational resources needed to run the neural networks for frame interpolation, which could be crucial for practical implementation.
Original Abstract Submitted
apparatuses, systems, and techniques to process image frames. in at least one embodiment, an application programming interface (api) is performed to enable frame interpolation to use one or more neural networks.
