Have a personal or library account? Click to login
Style Transfer Based on VGG Network Cover

References

  1. Krizhevsky A, Sutskever I, Hinton G E. Imagenet classification with deep convolutional neural networks. In: Proceedings of the 2012 Advances in Neural Information Processing Systems (NIPS). Lake Tahoe, USA: MIT Press, 2012. 1097–1105.
  2. GATYS L, ECKER A, BETHGE M.A Neural Algorithm of Artistic Style [J]. Journal of Vision, 2016, 16(12): 326.
  3. SIMONYAN K, ZISSERMAN A. Very deep convolutional networks for large-scale image recognition [J]. ArXiv preprint ar Xiv, 2014(9):1–14.
  4. JOHNSON J, ALAHI A, FEI-FEI L. Perceptual losses for real-time style transfer and super-resolution [C]//European Conference on Computer Vision, 2016:694–711.
  5. LI Y J, FANG C, YANG J M, et al. Universal style transfer via feature transforms[C]//In Advances in Neural Information Processing Systems. California: NIPS, 2017: 386–396.
  6. Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets[C]//Advances in Neural Information Processing Systems, 2014: 2672–2680.
  7. Radford A, Metz L, Chintala S. Unsupervised representation learning with deep convolutional generative adversarial networks [J]. arXiv: 1511.06434, 2015.
  8. Zhu J Y Park T, Isola P, et al. Unpaired image-to-image translation using cycle-consistent adversarial networks [C] //IEEE International Conference on Computer Vision, 2017: 2223–2232.
  9. Szegedy, Christian, et al. Going deeper with convolutions. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
  10. He, Kaiming, et al. Deep residual learning for image recognition. arXiv preprint arXiv:1512.03385(2015).
  11. He, Kaiming, and Jian Sun. Convolutional neural networks at constrained time cost. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
  12. HUANG X, BELONGIE S. Arbitrary style transfer in real-time with adaptive instance normalization[C]//2017 IEEE International Conference on Computer Vision (ICCV). New York: IEEE Press, 2017:1510–1519.
  13. ULYANOV D, VEDALDI A, LEMPITSKY V. Improved texture networks: Maximizing quality and diversity in feed-forward stylization and texture synthesis [C] //Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017:6924–6932.
  14. Krizhevsky A, Sutskever I, Hinton G E.Imagenet classification with deep convolutional neural networks. In: Proceedings of the 2012 Advances in Neural Information Processing Systems (NIPS). Lake Tahoe, USA: MIT Press, 2012. 1097‒1105.
  15. GATYS L, ECKER A, BETHGE M.A Neural Algorithm of Artistic Style [J]. Journal of Vision, 2016, 16(12): 326.
  16. SIMONYAN K, ZISSERMAN A. Very deep convolutional networks for large-scale image recognition [J]. ArXiv preprint arXiv, 2014(9):1–14.
  17. JOHNSON J, ALAHI A, FEI-FEI L. Perceptual losses for real-time style transfer and super-resolution[C]//European Conference on Computer Vision, 2016:694–711.
  18. LI Y J, FANG C, YANG J M, et al. Universal style transfer via feature transforms[C]//In Advances in Neural Information Processing Systems. California: NIPS, 2017: 386–396.
  19. Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets[C]//Advances in Neural Information Processing Systems, 2014: 2672–2680.
  20. Radford A, Metz L, Chintala S. Unsupervised representation learning with deep convolutional generative adversarial networks [J]. arXiv:1511.06434, 2015.
  21. Zhu J Y Park T, Isola P, et al. Unpaired image-to-image translation using cycle-consistent adversarial networks[C]//IEEE International Conference on Computer Vision, 2017: 2223–2232.
  22. Szegedy, Christian, et al. Going deeper with convolutions. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
  23. He, Kaiming, et al. Deep residual learning for image recognition. arXiv preprint arXiv:1512.03385(2015).
  24. He, Kaiming, and Jian Sun. Convolutional neural networks at constrained time cost. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
  25. HUANG X, BELONGIE S. Arbitrary style transferin real-time with adaptive instance normalization[C]//2017 IEEE International Conference on Computer Vision (ICCV). New York: IEEE Press, 2017:1510–1519.
  26. ULYANOV D, VEDALDI A, LEMPITSKY V. Improved texture networks: Maximizing quality and diversity in feed-forward stylization and texture synthesis[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017:6924–6932.
Language: English
Page range: 54 - 72
Published on: May 28, 2023
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Zhe Zhao, Shifang Zhang, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.