Image style transferring method based on VGG-16 network

Huiyan Ni; Zhiqing Su

doi:10.1117/12.2636926

29 April 2022 Image style transferring method based on VGG-16 network

Huiyan Ni, Zhiqing Su

Proceedings Volume 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022); 1224702 (2022) https://doi.org/10.1117/12.2636926
Event: 2022 International Conference on Image, Signal Processing, and Pattern Recognition, 2022, Guilin, China

Abstract

With the development of techniques and society, people gradually have more and more serious requirements for artistic pleasure. People want to make artistic works by themselves, and thus, many photo applications presented image style transfer features to cater to consumers’ tendencies. In order to improve the present algorithm about the feature and get a more effective solution. We presented the VGG-16 structure and improved it when solving the image style transfer problem. After comparing different networks, weight ratio, and activation functions, we find the VGG-16 is the best choice according to its least iteration and shortest running time among the four networks. In addition, ReLu and LeakyReLu are better than Tanh and Sigmoid when choosing activation functions for their better handling texture ability. LBFGS is better than Adam, SGD and RMSprop when choosing optimizer for its smaller number of iterations. Finally, we obtain an optimized image style transfer model based on VGG-16 network.

Citation Download Citation

Huiyan Ni and Zhiqing Su "Image style transferring method based on VGG-16 network", Proc. SPIE 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022), 1224702 (29 April 2022); https://doi.org/10.1117/12.2636926

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KEYWORDS

Image processing

Feature extraction

Convolution

Image fusion

Convolutional neural networks

Photography

Performance modeling

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