Method of training cycle generative networks model, and method of building character library

Abstract

A method of training a cycle generative networks model and a method of building a character library are provided, which relate to a field of artificial intelligence, in particular to a computer vision and deep learning technology, and which may be applied to a scene such as image processing and image recognition. A specific implementation scheme includes: inputting a source domain sample character into the cycle generative networks model to obtain a first target domain generated character; calculating a character error loss and a feature loss of the cycle generative networks model by inputting the first target domain generated character and a preset target domain sample character into a character classification model; and adjusting a parameter of the cycle generative networks model according to the character error loss and the feature loss. An electronic device and a storage medium are further provided.

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