Video frame rate upconversion method and system based on cyclic convolution neural network

A convolutional neural network and neural network technology, applied in the field of video frame rate up-conversion, can solve the problems of excessive smoothing of generated frames, influence of intermediate frame quality, and lack of details, so as to improve accuracy, improve synthesis quality, and improve visual effects Effect

Active Publication Date: 2018-12-21
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

[0004] However, the quality of intermediate frames is largely affected by the accuracy of motion estimation
For the video frame rate up-conversion

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  • Video frame rate upconversion method and system based on cyclic convolution neural network
  • Video frame rate upconversion method and system based on cyclic convolution neural network
  • Video frame rate upconversion method and system based on cyclic convolution neural network

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Embodiment Construction

[0047] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0048] Such as figure 1 As shown, the video frame rate up-conversion method based on the circular convolutional neural network provided by the present invention may include the following steps:

[0049] S1: Read the original high frame rate video, cut it into multiple groups of image blocks of three consecutive frames, where the two frames before and after are used as input, and the middle frame is used as a label to form a supervised data set for training and steps in step S3 Verification in S4;

[0...

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Abstract

The invention provides a video frame rate upconversion method and a video frame rate upconversion system based on a cyclic convolution neural network. Dividing the initial video into groups of image blocks comprising two consecutive frames of images; taking two consecutive frames of images in the image block as inputs of a target cyclic convolution neural network, and synthesizing intermediate frame images corresponding to the two consecutive frames of images; wherein, the target cyclic convolution neural network is trained by a preset training data set. The intermediate frame image is inserted into the image block to obtain the target video after the video frame rate upconversion. Thus, the mapping from the front and back two frames to the middle frame can be completed, the frame rate ofthe original video is improved, and the up-conversion of the video frame rate is better completed.

Description

technical field [0001] The present invention relates to the technical field of video processing, in particular to a video frame rate up-conversion method and system based on a circular convolutional neural network. Background technique [0002] The frame rate of a video is one of the important criteria to measure the video quality. The frame rate of the video represents the number of frames displayed per second, and the higher the frame rate, the better the smoothness of the video image. In addition, because the transmission of network video is affected by the network environment, in low-bandwidth video transmission, the video generally undergoes a certain degree of frame rate down-sampling and compression processing, so as to transmit at a lower bit rate. Therefore, at the receiving end, it is necessary to restore the frame rate of the original video, that is, to insert one or more frames between two frames of the original video, thereby increasing the frame rate of the vi...

Claims

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Application Information

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IPC IPC(8): H04N21/4402G06N3/04
CPCH04N21/4402H04N21/440281G06N3/044G06N3/045
Inventor 宋利张智峰解蓉陈立
Owner SHANGHAI JIAO TONG UNIV
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