A video jitter detection method, comprising: acquiring a video; inputting the video into a detection model to obtain an evaluation value of the video, wherein the evaluation value is used to indicate a degree of jitter of the video; wherein the detection model is a model obtained by training using video samples in a video sample set as inputs, and evaluation values of the video samples in the video sample set as outputs; wherein the video sample set comprises a first subset and a second subset, wherein video samples comprised in the first subset are labeled with evaluation values, video samples comprised in the second subset are not labeled with evaluation values, and training the detection model is obtained by the following manner: obtaining a first model by training using the video samples in the first subset as inputs, and the evaluation values of the video samples in the first subset as outputs; inputting the video samples in the second subset into the first model to obtain evaluation values of the video samples in the second subset; acquiring a modified second subset by manually correcting evaluation values for video samples, whose evaluation values are greater than a first numerical value, in the second subset, wherein the video samples in the modified second subset are labeled with evaluation values; and obtaining the detection model by training using the video samples in the first subset and the video samples in the modified second subset as inputs, and the evaluation values respectively corresponding to the video samples in the first subset and the video samples in the modified second subset as outputs. acquiring a video; inputting the video into a detection model to obtain an evaluation value of the video, wherein the evaluation value is used to indicate a degree of jitter of the video; wherein the detection model is a model obtained by training using video samples in a video sample set as inputs, and evaluation values of the video samples in the video sample set as outputs; wherein the video sample set comprises a first subset and a second subset, wherein video samples comprised in the first subset are labeled with evaluation values, video samples comprised in the second subset are not labeled with evaluation values, and training the detection model is obtained by the following manner: obtaining a first model by training using the video samples in the first subset as inputs, and the evaluation values of the video samples in the first subset as outputs; inputting the video samples in the second subset into the first model to obtain evaluation values of the video samples in the second subset; acquiring a modified second subset by manually correcting evaluation values for video samples, whose evaluation values are greater than a first numerical value, in the second subset, wherein the video samples in the modified second subset are labeled with evaluation values; and obtaining the detection model by training using the video samples in the first subset and the video samples in the modified second subset as inputs, and the evaluation values respectively corresponding to the video samples in the first subset and the video samples in the modified second subset as outputs. obtaining a first model by training using the video samples in the first subset as inputs, and the evaluation values of the video samples in the first subset as outputs; inputting the video samples in the second subset into the first model to obtain evaluation values of the video samples in the second subset; acquiring a modified second subset by manually correcting evaluation values for video samples, whose evaluation values are greater than a first numerical value, in the second subset, wherein the video samples in the modified second subset are labeled with evaluation values; and obtaining the detection model by training using the video samples in the first subset and the video samples in the modified second subset as inputs, and the evaluation values respectively corresponding to the video samples in the first subset and the video samples in the modified second subset as outputs.