中圖分類(lèi)號(hào)： TP391 文獻(xiàn)標(biāo)識(shí)碼： A DOI：10.16157/j.issn.0258-7998.212388 中文引用格式： 楊戈,，鄒武星. 基于深度學(xué)習(xí)的視頻行為分類(lèi)方法綜述[J].電子技術(shù)應(yīng)用,，2022，48(7)：1-7,，12. 英文引用格式： Yang Ge,，Zou Wuxing. A survey on video action classification methods based on deep learning[J]. Application of Electronic Technique，2022,，48(7)：1-7,，12.
A survey on video action classification methods based on deep learning
Yang Ge1，2,，Zou Wuxing1,，2
1.Key Laboratory of Intelligent Multimedia Technology，Beijing Normal University,，Zhuhai 519087,，China； 2.Advanced Institute of Natural Sciences,，Beijing Normal University,，Zhuhai 519087，China
Abstract： In the past few years, video action classification has gradually changed from manual feature selection to deep learning end-to-end model. This article discusses the traditional action classification method of manually selecting features and the action classification method based on deep learning, focusing on different deep learning methods including convolutional neural networks, recurrent neural network, dual-stream network, long and short-term memory network, etc., and it summarizes the commonly used video action classification data sets, summarizes and prospects the development of video action classification methods.
Key words : video action classification,；data set,；deep learning
