1. A method for detecting a salient region of an image, comprising: performing classification processing on a test image according to an image feature vector of the test image using a classifier obtained by pre-training, so as to obtain a classification label, wherein the classification label is used to indicate a salience detection algorithm for detecting a salient region of the test image, wherein the classifier is a back propagation (BP) neural network, wherein the BP neural network comprises an input layer, an intermediate layer, and an output layer, wherein a transfer function between the input layer and the intermediate layer is a hyperbolic tangent sigmoid function, wherein performing the classification processing on the test image comprises: performing, by using the BP neural network obtained by pre-training, classification processing on the test image according to the image feature vector, which is input by the input layer of the BP neural network, of the test image, and according to the hyperbolic tangent sigmoid function between the input layer of the BP neural network and the intermediate layer of the BP neural network and the logarithmic sigmoid function between the intermediate layer of the BP neural network and the output layer of the BP neural network, so as to obtain the classification label from the output layer of the BP neural network; and detecting the salient region of the test image by using the salience detection algorithm indicated by the classification label, so as to obtain the salient region of the test image.