ArtFID: Quantitative Evaluation of Neural Style Transfer-Reference-Cited by-同舟云学术

ArtFID: Quantitative Evaluation of Neural Style Transfer

Published:2022 Issue: Volume: Page:560-576
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
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Author:

Wright Matthias,Ommer Björn

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-16788-1_34

Reference88 articles.

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4. Chan, C., Ginosar, S., Zhou, T., Efros, A.A.: Everybody dance now. In: International Conference on Computer Vision (ICCV) (2019)

5. Chandran, P., Zoss, G., Gotardo, P., Gross, M., Bradley, D.: Adaptive convolutions for structure-aware style transfer. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2021)

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