View source for 18456027. VIDEO PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM simplified abstract (Tencent Technology (Shenzhen) Company Limited)

=VIDEO PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM=


==Organization Name==

[[:Category:Tencent Technology (Shenzhen) Company Limited|Tencent Technology (Shenzhen) Company Limited]]


[[Category:Tencent Technology (Shenzhen) Company Limited]]

==Inventor(s)==

[[:Category:Boyuan Jiang of Shenzhen (CN)|Boyuan Jiang of Shenzhen (CN)]][[Category:Boyuan Jiang of Shenzhen (CN)]]

[[:Category:Lingtong Kong of Shenzhen (CN)|Lingtong Kong of Shenzhen (CN)]][[Category:Lingtong Kong of Shenzhen (CN)]]

[[:Category:Donghao Luo of Shenzhen (CN)|Donghao Luo of Shenzhen (CN)]][[Category:Donghao Luo of Shenzhen (CN)]]

[[:Category:Ying Tai of Shenzhen (CN)|Ying Tai of Shenzhen (CN)]][[Category:Ying Tai of Shenzhen (CN)]]

[[:Category:Chengjie Wang of Shenzhen (CN)|Chengjie Wang of Shenzhen (CN)]][[Category:Chengjie Wang of Shenzhen (CN)]]

[[:Category:Xiaoming Huang of Shenzhen (CN)|Xiaoming Huang of Shenzhen (CN)]][[Category:Xiaoming Huang of Shenzhen (CN)]]

[[:Category:Jilin Li of Shenzhen (CN)|Jilin Li of Shenzhen (CN)]][[Category:Jilin Li of Shenzhen (CN)]]

[[:Category:Feiyue Huang of Shenzhen (CN)|Feiyue Huang of Shenzhen (CN)]][[Category:Feiyue Huang of Shenzhen (CN)]]

[[:Category:Yongjian Wu of Shenzhen (CN)|Yongjian Wu of Shenzhen (CN)]][[Category:Yongjian Wu of Shenzhen (CN)]]

==VIDEO PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18456027 titled 'VIDEO PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM

==Simplified Explanation==

The patent application describes a method for processing videos using neural networks. Here is a simplified explanation of the abstract:

* The method starts by obtaining two consecutive frames from a target video.
* These frames are then inputted into a neural network.
* The neural network is trained using an optical flow distillation constraint and a feature consistency constraint.
* The neural network outputs an intermediate video frame.
* Finally, the method interpolates this intermediate frame between the two original frames.

Potential applications of this technology:

* Video editing and post-production: The method can be used to enhance the quality of videos by generating high-quality intermediate frames.
* Video compression: By generating intermediate frames, the method can help reduce the size of video files without significant loss of quality.
* Virtual reality and gaming: The technology can improve the visual experience in virtual reality environments and video games by generating smoother and more realistic video sequences.

Problems solved by this technology:

* Low-quality video interpolation: Traditional methods of video interpolation often result in blurry or distorted frames. This technology aims to generate high-quality intermediate frames.
* Time-consuming video processing: Manual video processing can be time-consuming and labor-intensive. This method automates the process using neural networks, saving time and effort.

Benefits of this technology:

* Improved video quality: The method aims to generate high-quality intermediate frames, resulting in smoother and more visually appealing videos.
* Time and cost savings: By automating the video processing using neural networks, the method can save time and reduce the need for manual intervention.
* Versatile applications: The technology can be applied to various video-related fields, including video editing, compression, virtual reality, and gaming.


==Original Abstract Submitted==

A video processing method includes: obtaining a first video frame and a second video frame in a target video, the first video frame being a previous frame of the second video frame; inputting the first video frame and the second video frame to a target neural network, and obtaining a target intermediate video frame output by the target neural network, the target neural network being trained based on an optical flow distillation constraint and a feature consistency constraint; and interpolating the target intermediate video frame between the first video frame and the second video frame.



[[Category:G06T3/40]]
[[Category:G06T7/246]]