Artistic Neural Style Transfer Algorithms with Activation Smoothing
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866912116419592192 |
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| author | Li, Xiangtian Cao, Han Zhang, Zhaoyang Hu, Jiacheng Jin, Yuhui Zhao, Zihao |
| author_facet | Li, Xiangtian Cao, Han Zhang, Zhaoyang Hu, Jiacheng Jin, Yuhui Zhao, Zihao |
| contents | The works of Gatys et al. demonstrated the capability of Convolutional Neural Networks (CNNs) in creating artistic style images. This process of transferring content images in different styles is called Neural Style Transfer (NST). In this paper, we re-implement image-based NST, fast NST, and arbitrary NST. We also explore to utilize ResNet with activation smoothing in NST. Extensive experimental results demonstrate that smoothing transformation can greatly improve the quality of stylization results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_08014 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Artistic Neural Style Transfer Algorithms with Activation Smoothing Li, Xiangtian Cao, Han Zhang, Zhaoyang Hu, Jiacheng Jin, Yuhui Zhao, Zihao Computer Vision and Pattern Recognition Image and Video Processing The works of Gatys et al. demonstrated the capability of Convolutional Neural Networks (CNNs) in creating artistic style images. This process of transferring content images in different styles is called Neural Style Transfer (NST). In this paper, we re-implement image-based NST, fast NST, and arbitrary NST. We also explore to utilize ResNet with activation smoothing in NST. Extensive experimental results demonstrate that smoothing transformation can greatly improve the quality of stylization results. |
| title | Artistic Neural Style Transfer Algorithms with Activation Smoothing |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2411.08014 |