AI-DRIVEN BACKGROUND GENERATION FOR MANGA ILLUSTRATIONS: A DEEP GENERATIVE MODEL APPROACH

Abstract

This paper introduces the generation technique of manga illustration background, discusses the traditional background generation technique and stylized migration technique, and points out that the application of AI technology provides new possibilities for the creation of manga illustration backgrounds. Aiming at the limitations of traditional methods, the design concept and principle of conditional generative model based on deep learning are proposed, the implementation principles of convolutional neural network and generative adversarial network are introduced, and the conditional manga illustration background generation model based on deep learning is proposed by combining the two. The paper uses MindSpore software to train CNN models.CNN models are very good for processing data such as images and are able to reduce the number of parameters in the model and increase the speed of training the model.The model data has a wide range of applications and is capable of removing the influence of character factors from the image while providing high resolution.The model can effectively realize the conditional generation of manga illustration background. The practical effect of this technology is demonstrated through a case study and technical exploration of manga illustration background generation technology, which demonstrates the potential of the new technology and its application in creating richer and more vivid comic backgrounds. In the future, with the continuous improvement and promotion of this technology, more similar cases are expected to be seen, bringing more possibilities and innovations to the creation of comics and illustrations.