Face attribute classification method based on multilayer depth feature information
A technology of attribute classification and deep features, applied in the field of computer vision, can solve the problems that the effect cannot be applied in practice
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[0016] A face attribute classification method based on multi-layer depth feature information, the specific steps are as follows:
[0017] S1: Suppose x is a face image from any angle, y is a frontal image, find f such that f(x)=y, suppose In this way we construct the multilayer f i = θ(w, x), so that f holds true. Here, the w parameter is learned by means of deep learning, so as to find the f function. First, by preprocessing the frontal image, images of different angles are rotated as training pictures, and the corresponding frontal image As the desired result, in order to make the input and output of the network be images of the same size, the feature layer is followed by an upsampling layer, and the loss function uses L2 norm to compare the last feature layer and the front image, and through step-by-step iterative tuning, the last one The feature layer is close to the frontal image, and the finally trained network is the f we are looking for. Through this function, the in...
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