Face image super-resolution reconstruction method based on discriminable attribute constraint generative adversarial network
A face image and image technology, which is applied in the field of super-resolution reconstruction of face images, can solve the problems of low accuracy of face verification and loss of detail information of LR face images, etc., to enhance detail information, improve learning ability and performance Enhanced effect
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[0046] Below in conjunction with accompanying drawing of description, the embodiment of the present invention is described in detail:
[0047] A face image super-resolution reconstruction method based on discriminable attribute constraints generative adversarial network, the overall flow chart is attached figure 1 shown; the algorithm is divided into offline part and online part; the relationship between offline part and online part is as attached image 3 As shown; the offline part is divided into two stages: sample preprocessing and network training. In the first stage, in order to avoid the interference of the background of the face object, the present invention first preprocesses the face data set in batches, and obtains the aligned HR face image after image preprocessing "face detection, face alignment", and the image size It is unified into M×N pixels; then it is down-sampled by S times, and the LR face image with the size of M / S×N / S is obtained; finally, the LR and HR ...
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