Image processing method, device and equipment and computer readable storage medium

Abstract

The embodiment of the invention provides an image processing method, device and equipment and a computer readable storage medium. The method comprises the steps: obtaining a first image and a second image; performing identity feature extraction on a first target object in the first image to obtain an identity feature vector of the first image; performing attitude feature extraction on a second target object in the second image to obtain an attitude feature vector of the second image; obtaining an image synthesis vector corresponding to the first image and the second image based on the identityfeature vector and the attitude feature vector; generating a composite image of the first image and the second image according to the image composite vector; wherein the first target object in the composite image has the posture of the second target object. Through the embodiment of the invention, the image reproduction adaptability during image synthesis can be improved, and accurate image synthesis processing can be performed on the first image and the second image.

Description

technical field [0001] The embodiment of the present application relates to the field of Internet technologies, and relates to but not limited to an image processing method, device, equipment, and computer-readable storage medium. Background technique [0002] The face reconstruction technology in the related art mainly uses big data to drive model training to obtain an image processing network. During model training, the identity information of the original image and the target image are set to be consistent, and a large amount of image data is used to generate images in the image processing network. The machine network is trained, and then the face is reproduced through the trained image processing network. [0003] However, the applicant found in the process of implementing the embodiment of the present application that the methods in the related art are only limited to the reproduction of a specific target face, and the trained image processing network is only suitable f...

AI Technical Summary

Problems solved by technology

[0003] However, the applicant found in the process of implementing the embodiment of the present application that the methods in the related art are only limited to the reproduction of a specific target face, and the trained image processing network is only suitable for the reproduction of a single target face, and other The target face is not applicable, and the training of a single target face requires a large amount of data support, making it impractical to retrain a new image processing network. At the same time, since most network training sets the identity information of the original image and the target image to be consistent, The adaptability of the network to the reproduction of faces of different identities is poor, and the synthesis accuracy of the network for reproducing faces of different images is low

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