2024
DOI: 10.1088/1742-6596/2759/1/012003
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A Digital Animation Generation Model Based on Cycle Adversarial Neural Network

Juan Xu,
Lijun Xu,
Kai Zhang
et al.

Abstract: This paper proposes a digital animation generation model based on Cycle Adversarial Neural Network (CycleGAN). Compared with the classical CycleGAN, this research presents a multi-attention approach to enhance the network’s generalization. Specifically, a style enhancement module and a style cross-attention mechanism are introduced into the generator network structure, which enables the model to better parse the structural information of the content image and realize the accurate matching of content features a… Show more

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