Video description method based on cyclic convolution decoding of a complementary attention mechanism

A technology of video description and circular convolution, applied in the field of computer vision, can solve the problem of weakening the ability of the circular neural network to transmit information, and achieve the effects of improving long-distance dependence, improving accuracy, and good application value

Inactive Publication Date: 2019-06-21
ZHEJIANG UNIV
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  • Application Information

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The decoder generally uses a separate cyclic neural network, but the ability of the c...

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  • Video description method based on cyclic convolution decoding of a complementary attention mechanism
  • Video description method based on cyclic convolution decoding of a complementary attention mechanism
  • Video description method based on cyclic convolution decoding of a complementary attention mechanism

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[0040] 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.

[0041] On the contrary, the invention covers any alternatives, modifications, equivalent methods and schemes within the spirit and scope of the invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0042] refer to figure 1, in a preferred embodiment of the present invention, the video description g...

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Abstract

The invention discloses a video description method based on complementary attention mechanism cyclic convolution decoding. The video description method is used for generating short and accurate description for a given video clip. The method specifically comprises the following steps: obtaining a video data set for training a video description generation model, and defining an algorithm target; modeling a global time sequence feature and a local semantic feature in the video data set; establishing a complementary attention mechanism on a circular convolutional decoder based on global-local features; using the model to generate a description of an input video. The method is suitable for video description generation of a real video scene, and has a good effect and robustness for various complex conditions.

Description

technical field [0001] The invention belongs to the field of computer vision, in particular to a video description method based on a global-local complementary attention mechanism circular convolution decoding. Background technique [0002] In today's society, video has become an indispensable part of human life, it can be said that it is everywhere. Such an environment has made people's research on the semantic content of video has also been greatly developed, but most of the current research on video is mainly focused on lower levels, such as classification, detection and so on. Thanks to the development of recurrent neural networks, the new task of video description generation has also come into view. Given a video clip, use the trained network model to automatically generate a sentence description for the video clip. Its application in the real world is also very extensive. For example, about 100 hours of videos are generated every minute on YouTube. If the generated v...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 金涛李英明张仲非
Owner ZHEJIANG UNIV
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