High-frame-rate video generation method and system based on depth learning

A deep learning, high frame rate technology, applied in the field of computer vision, can solve the problems of dropped frame video quality and degradation, and achieve the effect of overcoming time-consuming, labor-intensive, and insignificant effects.

Active Publication Date: 2017-05-17
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0003] Aiming at the above defects or improvement needs of the prior art, the present invention provides a method for generating high frame rate video based on deep learning, the purpose of which is to convert low frame rate video in

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[0033] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0034] Below at first explain and illustrate with regard to the technical terms of the present invention:

[0035] Convolutional Neural Network (CNN): A neural network that can be used for image classification, regression and other tasks. Its particularity is reflected in two aspects. On the one hand, the connection between its neurons is not fully connected. , on the other hand the weights of ...

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Abstract

The invention discloses a high-frame-rate video generation method based on depth learning. The method includes the steps that one or more original high-frame-rate video segments are used for generating a training sample set; multiple video frame subsets in the training sample set are used for training a dual-channel convolutional neural network model so as to obtain an optimized dual-channel convolutional neural network, wherein the dual-channel convolutional neural network model is a convolutional neural network formed by fusing two convolutional channels; the optimized dual-channel convolutional neural network is adopted, according to any two adjacent video frames in a low-frame-rate video, an insert frame of the two video frames is generated, and therefore a video whose frame rate is higher than that of the low-frame-rate video is generated. The whole process of the method is in an end-to-end mode, no subsequent processing is needed for video frames, the video frame rate conversion effect is good, the fluency of the synthetic video is high, and the method has excellent robustness on shaking, video scene changing and other problems in the video shooting process.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and more specifically, relates to a method and system for generating high frame rate video based on deep learning. Background technique [0002] With the development of technology, it is more and more convenient for people to obtain videos. However, due to hardware reasons, most videos are collected by non-professional equipment, and the frame rate is generally only 24fps-30fps. High frame rate video has extremely high fluency, which can bring people a better visual experience. If people directly upload high frame rate videos to the Internet, due to the increase in traffic consumption, people's costs will also increase. If the video with a low frame rate is directly uploaded, due to the reasons of the network line, there will inevitably be a problem of frame loss during the video transmission process. The larger the video, the more likely this phenomenon will occur, so that the remote vi...

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Application Information

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IPC IPC(8): H04N21/845H04N19/587H04N7/01G06N3/04G06N3/08
CPCH04N7/0127H04N19/587H04N21/845G06N3/084G06N3/045
Inventor 王兴刚罗浩姜玉静刘文予
Owner HUAZHONG UNIV OF SCI & TECH
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