Research on arbitrary style transfer algorithm based on attention mechanism
Jianxia Wang, Yukun Zhang, Wanzhen Zhou · 2023
With the continuous development of society and economy, people have more preferences and pursuits for various kinds of art works, but few people can reproduce the great works of artists like Van Gogh, which is undoubtedly a pity. Related applications show that the image style transfer technology can transfer the styles of various art paintings to common images, so that different art styles can be generated relatively quickly. Combining with the current mainstream migration ideas, this paper proposes the decoupling and extraction of style features using effective channel attention (ECA) module, the decoupling and extraction of content features using spatial attention (SA)module, and the feature fusion using the feature fusion (FF) module. The proposed method is compared with the mainstream method in terms of speed. The results show that the method used in this paper has better results in both speed and sensory. The proposed method can satisfy people's pursuit of artistic works, inspire contemporary artists to create, and promote the cross integration of art field and computer vision field.