Arbitrary artistic style transfer is a research area that combines rational academic study with emotive artistic creation. It aims to create a new image from a content image according to a target artistic style, maintaining the content's textural structural information while incorporating the artistic characteristics of the style image. However, existing style transfer methods often significantly damage the texture lines of the content image during the style transformation. To address these issues, we propose affinity-enhanced attentional network, which include the content affinity-enhanced attention (CAEA) module, the style affinity-enhanced attention (SAEA) module, and the hybrid attention (HA) module. The CAEA and SAEA modules first use attention to enhance content and style representations, followed by a detail enhanced (DE) module to reinforce detail features. The hybrid attention module adjusts the style feature distribution based on the content feature distribution. We also introduce the local dissimilarity loss based on affinity attention, which better preserves the affinity with content and style images. Experiments demonstrate that our work achieves better results in arbitrary style transfer than other state-of-the-art methods.

本研究解决了现有任意艺术风格迁移方法在风格转换过程中显著损害内容图像纹理线条的问题。提出了一种增强亲和力的注意网络，包括内容亲和力增强注意模块和风格亲和力增强注意模块，通过细节增强模块强化细节特征，并引入基于亲和注意力的局部差异损失，以更好地保留内容与风格图像之间的亲和性。实验表明，本方法在任意风格迁移方面优于其他先进方法。

AEANet: 增强亲和力的注意网络用于任意风格迁移