Research on Violent Action Recognition Based on Deep Learning
Violent action recognition is a research direction in the field of video action recognition.With the development of deep learning,video action recognition has made significant progress in the past decade,but also faced new chal-lenges,such as how to effectively model the long-term temporal information in videos,how to reduce the computational cost,etc.To address this problem,a deep learning network model based on soft attention mechanism and depthwise sep-arable convolution LSTM,called Att-SepConvLSTM,is introduced.It first uses a lightweight NasNetMobile network to extract the spatial features of video frames,then inputs the spatial feature maps sequentially,obtaining the global temporal fea-tures,and finally outputs whether there is violent action or not through a classification layer.
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