An action recognition method, comprising: obtaining a to-be-processed picture; extracting a spatial feature of the to-be-processed picture; determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature of the to-be-processed picture and X spatial features and X optical flow features in a preset feature library, wherein there is a one-to-one correspondence between the X spatial features and the X optical flow features, and X is an integer greater than 1; determining a first type of confidence of the to-be-processed picture in different action categories based on similarities between the virtual optical flow feature of the to-be-processed picture and Y optical flow features in the feature library, wherein each of the Y optical flow features corresponds to one action category, and Y is an integer greater than 1; and determining an action category of the to-be-processed picture based on the first type of confidence; wherein the determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature of the to-be-processed picture and X spatial features and X optical flow features in a preset feature library comprises: determining a weight coefficient of each of the X optical flow features based on a similarity between the spatial feature of the to-be-processed picture and each of the X spatial features; and performing weighted summation on the X optical flow features based on the weight coefficient of each of the X optical flow features, to obtain the virtual optical flow feature of the to-be-processed picture; wherein a value of the determined weight coefficient of each of the X optical flow features is positively correlated to a first similarity, and the first similarity is a similarity between the spatial feature of the to-be-processed picture and a spatial feature in the X spatial features that corresponds to each of the X optical flow features. obtaining a to-be-processed picture; extracting a spatial feature of the to-be-processed picture; determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature of the to-be-processed picture and X spatial features and X optical flow features in a preset feature library, wherein there is a one-to-one correspondence between the X spatial features and the X optical flow features, and X is an integer greater than 1; determining a first type of confidence of the to-be-processed picture in different action categories based on similarities between the virtual optical flow feature of the to-be-processed picture and Y optical flow features in the feature library, wherein each of the Y optical flow features corresponds to one action category, and Y is an integer greater than 1; and determining an action category of the to-be-processed picture based on the first type of confidence; wherein the determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature of the to-be-processed picture and X spatial features and X optical flow features in a preset feature library comprises: determining a weight coefficient of each of the X optical flow features based on a similarity between the spatial feature of the to-be-processed picture and each of the X spatial features; and performing weighted summation on the X optical flow features based on the weight coefficient of each of the X optical flow features, to obtain the virtual optical flow feature of the to-be-processed picture; wherein a value of the determined weight coefficient of each of the X optical flow features is positively correlated to a first similarity, and the first similarity is a similarity between the spatial feature of the to-be-processed picture and a spatial feature in the X spatial features that corresponds to each of the X optical flow features. determining a weight coefficient of each of the X optical flow features based on a similarity between the spatial feature of the to-be-processed picture and each of the X spatial features; and performing weighted summation on the X optical flow features based on the weight coefficient of each of the X optical flow features, to obtain the virtual optical flow feature of the to-be-processed picture; wherein a value of the determined weight coefficient of each of the X optical flow features is positively correlated to a first similarity, and the first similarity is a similarity between the spatial feature of the to-be-processed picture and a spatial feature in the X spatial features that corresponds to each of the X optical flow features.