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Video characterization method and device

A video and representation technology, applied in the computer field, can solve the problem of low accuracy of video representation and achieve the effect of improving accuracy

Pending Publication Date: 2022-08-05
TENCENT TECH (SHENZHEN) CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, video representation learning in related technologies relies on labeled category data, and video representation is only related to labeled category data, and the accuracy of video representation is low

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  • Video characterization method and device
  • Video characterization method and device

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Embodiment Construction

[0032] The video representation method provided in the embodiments of the present application involves artificial intelligence technology, which is briefly described below to facilitate understanding by those skilled in the art.

[0033] Artificial intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that the machines have the functions of perception, reasoning and decision-making.

[0...

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Abstract

The invention discloses a video representation method and device, and belongs to the technical field of computers. The method comprises the following steps: acquiring a to-be-processed video clip; and inputting the to-be-processed video clip into the target video representation model to obtain first video representation data corresponding to the to-be-processed video clip. In the technical scheme provided by the embodiment of the invention, the similarity information between the video clips can be determined through the video representation data corresponding to the video clips in the training sample, and the time sequence distance information between the video clips is introduced on the basis of the similarity information to determine the distance attenuation loss information. In this way, the negative correlation degree between the time sequence distance information and the similarity information is adjusted in the model training process, so that the video representation model learns the correlation between the distance and the similarity of different video clips in the time dimension, and more accurate video representation data is output to perform feature representation on a to-be-processed video. And the accuracy of video representation is effectively improved.

Description

technical field [0001] The present application relates to the field of computer technology, and in particular, to a video representation method and apparatus. Background technique [0002] With the development of digital technology and Internet technology, information content services in the form of video are favored by the public, and the amount of video on the Internet has surged. Therefore, video representation learning becomes more important. [0003] In the related art, a video representation model is trained by a large amount of labeled category data for video representation learning, so that videos with the same or similar labeled category data have similar feature distances between the corresponding video representation data. After the above-mentioned video representation model is trained, it can output video representation data to represent the input video and apply it to the downstream video classification task. [0004] However, the video representation learning...

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Application Information

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IPC IPC(8): G06V10/774G06V10/70G06V20/00G06K9/62G06N20/00
CPCG06N20/00G06F18/22G06F18/214
Inventor 苏冰张恒李昱祁仲昂单瀛
Owner TENCENT TECH (SHENZHEN) CO LTD