Arbitrary style transfer method with attentional feature distribution matching
Author:
Funder
Natural Science Foundation of Anhui Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00530-024-01300-4.pdf
Reference40 articles.
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3. Ulyanov, D., Vedaldi, A., Lempitsky, V.:. Improved texture networks: Maximizing quality and diversity in feed-forward stylization and texture synthesis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6924–6932, (2017)
4. Kotovenko, D., Sanakoyeu, A., Lang, S., Ommer, B.: Content and style disentanglement for artistic style transfer. In: Proceedings of the IEEE/CVF international conference on computer vision, pp. 4422–4431 (2019)
5. Chen H, Zhao L, Zhang H, et al. Diverse image style transfer via invertible cross-space mapping[C]//2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE Computer Society, 2021: 14860–14869.
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