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Neural style transfer (NST) generates new images by combining the style of one image with the content of another.
Contrast masking in human vision
G. E. Legge and J. M. Foley · 1980
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M. S. Livingstone · 1988
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Statistics of cone responses to natural images: implications for visual coding
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Inner vision: An exploration of art and the brain
S. Zeki · 2000
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Image quality assessment: from error visibility to structural similarity
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli · 2004
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2014
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Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2015
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
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Painter by numbers, 2016
N. Kiri and W. Kan · 2016
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Towards evaluating the robustness of neural networks
N. Carlini and D. Wagner · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
X. Huang and S. Belongie · 2017
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Universal style transfer via feature transforms
Y. Li, C. Fang, J. Yang, Z. Wang, X. Lu, and M.-H. Yang · 2017
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Deep photo style transfer
F. Luan, S. Paris, E. Shechtman, and K. Bala · 2017
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Universal adversarial perturbations
S.-M. Moosavi-Dezfooli, A. Fawzi, O. Fawzi, and P. Frossard · 2017
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Stable and controllable neural texture synthesis and style transfer using histogram losses
E. Risser, P. Wilmot, and C. Barnes · 2017
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Boosting adversarial attacks with momentum
Y. Dong, F. Liao, T. Pang, H. Su, J. Zhu, X. Hu, and J. Li · 2018
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Sliced-wasserstein autoencoder: An embarrassingly simple generative model
In the light of feature distributions: Moment matching for neural style transfer
N. Kalischek, J. D. Wegner, and K. Schindler · 2021
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Exploring frequency adversarial attacks for face forgery detection
S. Jia, C. Ma, T. Yao, B. Yin, S. Ding, and X. Yang · 2022
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Segment and complete: Defending object detectors against adversarial patch attacks with robust patch detection
J. Liu, A. Levine, C. P. Lau, R. Chellappa, and S. Feizi · 2022
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Exact feature distribution matching for arbitrary style transfer and domain generalization
Y. Zhang, M. Li, R. Li, K. Jia, and L. Zhang · 2022
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Restricted black-box adversarial attack against deepfake face swapping
J. Dong, Y. Wang, J. Lai, and X. Xie · 2023
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S. Kolouri, P. E. Pope, C. E. Martin, and G. K. Rohde · 2018
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Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2018
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Pieapp: Perceptual image-error assessment through pairwise preference
E. Prashnani, H. Cai, Y. Mostofi, and P. Sen · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
R. Zhang, P. Isola, A. A. Efros, E. Shechtman, and O. Wang · 2018
Cited alongside, same era.
Fda: Feature disruptive attack
A. Ganeshan, V. B.S., and R. V. Babu · 2019
Cited alongside, same era.
A closed-form solution to universal style transfer
M. Lu, H. Zhao, A. Yao, Y. Chen, F. Xu, and L. Zhang · 2019
Cited alongside, same era.
Arbitrary style transfer with style-attentional networks
D. Y. Park and K. H. Lee · 2019
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M. Garg, J. S. Ubhi, and A. K. Aggarwal · 2023
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Z. Guo, W. Li, Y. Qian, O. Arandjelović, and L. Fang · 2023
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Unifying the harmonic analysis of adversarial attacks and robustness
S. R. Maiya, M. Ehrlich, V. Agarwal, S.-N. Lim, T. Goldstein, and A. Shrivastava · 2023
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Ai image creator faces uk and us legal challenges
C. Vallance · 2023
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Lfaa: Crafting transferable targeted adversarial examples with low-frequency perturbations
K. Wang, J. Shi, and W. Wang · 2023
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Prompt as triggers for backdoor attack: Examining the vulnerability in language models
S. Zhao, J. Wen, A. Luu, J. Zhao, and J. Fu · 2023
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Semi-supervised counting via pixel-by-pixel density distribution modelling
H. Lin, Z. Ma, R. Ji, Y. Wang, Z. Su, X. Hong, and D. Meng · 2024
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Exploring clean label backdoor attacks and defense in language models
S. Zhao, L. A. Tuan, J. Fu, J. Wen, and W. Luo · 2024
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