三维卷积神经网络及其在视频理解领域中的应用研究

Research on 3D Convolutional Neural Network and Its Application on Video Understanding

3维卷积神经网络(3D CNN)是近几年来深度学习研究中的热点,在计算机视觉领域取得了诸多成就。虽然研究多年且成果丰富,但目前仍缺少关于此内容全面、细致的综述。基于此,该文从以下几个方面对其进行综述:首先阐述3维卷积神经网络的基本原理和模型结构,接着从网络结构、网络内部和优化方法总结3维卷积神经网络的相关改进工作,然后对3维卷积神经网络在视频理解领域中的应用进行总结,最后总结全文内容并对未来发展方向进行展望。该文针对3维卷积神经网络的最新研究进展以及在视频理解领域中的应用进行了系统的综述,对3维卷积神经网络的研究发展具有一定的积极意义。

3D Convolutional Neural Network(3D CNN)has been a hot topic in deep learning research over the last few years and has made great achievements in computer vision.Despite years of research and abundant results,a comprehensive and detailed review of this content is still lacking.In this paper,the 3D convolutional neural network is introduced in the following aspects.Firstly,the rationale and model structure of 3D convolutional neural network are put forward.Then the improvement of 3D convolutional neural network is summarized from the network structure,network interior and optimization methods.After that the application of 3D convolutional neural network in the field of video understanding is explained.Finally,the contents summary of the paper and future development.This paper provides a systematic review of the latest research progress of 3D convolutional neural networks and their applications in the field of video understanding,which is of positive significance to the research and development of 3D convolutional neural network.