Nvidia corporation (20240095097). APPLICATION PROGRAMMING INTERFACE TO CAUSE PERFORMANCE OF FRAME INTERPOLATION simplified abstract
Contents
- 1 APPLICATION PROGRAMMING INTERFACE TO CAUSE PERFORMANCE OF FRAME INTERPOLATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 APPLICATION PROGRAMMING INTERFACE TO CAUSE PERFORMANCE OF 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 CAUSE PERFORMANCE OF 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 CAUSE PERFORMANCE OF FRAME INTERPOLATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095097 titled 'APPLICATION PROGRAMMING INTERFACE TO CAUSE PERFORMANCE OF FRAME INTERPOLATION
Simplified Explanation
The abstract of the patent application describes apparatuses, systems, and techniques for processing image frames using a neural network-based frame interpolation method.
- Frame interpolation is performed using one or more neural networks.
- An application programming interface (API) is utilized to execute the frame interpolation process.
Potential Applications
This technology could be applied in various fields such as video editing, animation, virtual reality, and gaming to enhance the quality of video playback by generating intermediate frames.
Problems Solved
1. Addressing the issue of low frame rate videos by generating additional frames to improve the overall viewing experience. 2. Enhancing the smoothness and visual quality of videos by filling in missing frames through interpolation.
Benefits
1. Improved video quality with smoother transitions between frames. 2. Enhanced user experience with more visually appealing content. 3. Increased efficiency in video processing and editing tasks.
Potential Commercial Applications
"Enhancing Video Quality with Neural Network Frame Interpolation Technology"
Possible Prior Art
One possible prior art in this field is the use of traditional frame interpolation techniques such as optical flow algorithms to generate intermediate frames in videos. However, the use of neural networks for frame interpolation represents a more advanced and efficient approach to this process.
Unanswered Questions
How does this technology compare to traditional frame interpolation methods?
The article does not provide a direct comparison between neural network-based frame interpolation and traditional methods such as optical flow algorithms. It would be helpful to understand the specific advantages and disadvantages of each approach.
What are the computational requirements for implementing this technology?
The article does not mention the computational resources needed to perform frame interpolation using neural networks. Understanding the computational demands of this technology would be crucial for assessing its practicality and scalability.
Original Abstract Submitted
apparatuses, systems, and techniques to process image frames. in at least one embodiment, an application programming interface (api) is performed to cause frame interpolation to be performed using one or more neural networks.
