Fetching the paper…
Reading the bibliography…
Image style transfer has attracted widespread attention in the past few years.
N. Chinchor, “Muc-4 evaluation metrics,” in Proceedings of the 4th Conference on Message Understanding , USA, 1992. [Online]. Available: https://doi.org/10.3115/1072064.1072067
1992
Earlier work this paper cites.
S.-J. Kim, A. Magnani, and S. P. Boyd, “Robust fisher discriminant analysis,” in NeurIPS , 2005
2005
Earlier work this paper cites.
2014
Earlier work this paper cites.
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick, “Microsoft coco: Common objects in context,” in Proc. ECCV , 2014
2014
Earlier work this paper cites.
K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,” in Proc. ICLR , 2015
2015
Earlier work this paper cites.
L. A. Gatys, A. S. Ecker, and M. Bethge, “Image style transfer using convolutional neural networks,” in Proc. CVPR Workshops , 2016
2016
Earlier work this paper cites.
D. Ulyanov, V. Lebedev, A. Vedaldi, and V. Lempitsky, “Texture networks: Feed-forward synthesis of textures and stylized images,” in Proc. ICML , 2016
2016
Earlier work this paper cites.
T. Q. Chen and M. Schmidt, “Fast patch-based style transfer of arbitrary style,” 2016
2016
Earlier work this paper cites.
X. Chen, Y. Duan, R. Houthooft, J. Schulman, I. Sutskever, and P. Abbeel, “Infogan: Interpretable representation learning by information maximizing generative adversarial nets,” in NeurIPS , 2016
2016
Earlier work this paper cites.
“K. nichol. painter by numbers, wikiart,” https://www.kaggle.com/c/painter-by-numbers , 2016
2016
Earlier work this paper cites.
J. Johnson, A. Alahi, and L. Fei-Fei, “Perceptual losses for real-time style transfer and super-resolution,” in Proc. ECCV , 2016
2016
Earlier work this paper cites.
Y. Li, C. Fang, J. Yang, Z. Wang, X. Lu, and M.-H. Yang, “Universal style transfer via feature transforms,” NeurIPS , 2017
2017
Earlier work this paper cites.
X. Huang and S. Belongie, “Arbitrary style transfer in real-time with adaptive instance normalization,” in Proc. ICCV , 2017
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. u. Kaiser, and I. Polosukhin, “Attention is all you need,” in NeurIPS , 2017
2017
Earlier work this paper cites.
A. van den Oord, O. Vinyals, and k. kavukcuoglu, “Neural discrete representation learning,” in NeurIPS , 2017
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
A. Sanakoyeu, D. Kotovenko, S. Lang, and B. Ommer, “A style-aware content loss for real-time hd style transfer,” in Proc. ECCV , 2018
2018
Earlier work this paper cites.
L. Sheng, Z. Lin, J. Shao, and X. Wang, “Avatar-net: Multi-scale zero-shot style transfer by feature decoration,” in Proc. CVPR Workshops , 2018
2018
Earlier work this paper cites.
A. Sanakoyeu, D. Kotovenko, S. Lang, and B. Ommer, “A style-aware content loss for real-time hd style transfer,” in Proc. ECCV , 2018
2018
Earlier work this paper cites.
X. Huang, M.-Y. Liu, S. Belongie, and J. Kautz, “Multimodal unsupervised image-to-image translation,” in Proc. ECCV , 2018
2018
Earlier work this paper cites.
H.-Y. Lee, H.-Y. Tseng, J.-B. Huang, M. K. Singh, and M.-H. Yang, “Diverse image-to-image translation via disentangled representations,” in Proc. ECCV , 2018
2018
Cited alongside, same era.
X. Wang, R. Girshick, A. Gupta, and K. He, “Non-local neural networks,” in Proc. CVPR Workshops , 2018
2018
Cited alongside, same era.
X. Li, S. Liu, J. Kautz, and M.-H. Yang, “Learning linear transformations for fast arbitrary style transfer,” in Proc. CVPR Workshops , 2019
2019
Cited alongside, same era.
D. Y. Park and K. H. Lee, “Arbitrary style transfer with style-attentional networks,” in Proc. CVPR Workshops , 2019
2019
Cited alongside, same era.
N. Kolkin, J. Salavon, and G. Shakhnarovich, “Style transfer by relaxed optimal transport and self-similarity,” in Proc. CVPR Workshops , 2019
2019
Cited alongside, same era.
Z.-S. Liu, V. Kalogeiton, and M.-P. Cani, “Multiple style transfer via variational autoencoder,” in Intl. Conf. Image Proc. , 2021
2021
Later among the works it cites.
J. Köhler, A. Krämer, and F. Noé, “Smooth normalizing flows,” in NeurIPS , 2021
2021
Later among the works it cites.
H. Chen, L. Zhao, Z. Wang, H. Zhang, Z. Zuo, A. Li, W. Xing, and D. Lu, “Dualast: Dual style-learning networks for artistic style transfer,” in Proc. CVPR Workshops , 2021
2021
Later among the works it cites.
A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark et al. , “Learning transferable visual models from natural language supervision,” in Proc. ICML , 2021
2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
D. Kotovenko, A. Sanakoyeu, P. Ma, S. Lang, and B. Ommer, “A content transformation block for image style transfer,” Proc. CVPR Workshops , 2019
2019
Cited alongside, same era.
N. Audebert, C. Herold, K. Slimani, and C. Vidal, “Multimodal deep networks for text and image-based document classification,” in Joint European Conference on Machine Learning and Knowledge Discovery in Databases , 2019
2019
Cited alongside, same era.
T. Karras, S. Laine, and T. Aila, “A style-based generator architecture for generative adversarial networks,” in Proc. CVPR Workshops , 2019
2019
Cited alongside, same era.
W. Wang, S. Yang, J. Xu, and J. Liu, “Consistent video style transfer via relaxation and regularization,” IEEE Transactions on Image Processing , 2020
2020
Cited alongside, same era.
H. Wang, Y. Li, Y. Wang, H. Hu, and M.-H. Yang, “Collaborative distillation for ultra-resolution universal style transfer,” in Proc. CVPR Workshops , 2020
2020
Cited alongside, same era.
H.-Y. Lee, H.-Y. Tseng, Q. Mao, J.-B. Huang, Y.-D. Lu, M. K. Singh, and M.-H. Yang, “Drit++: Diverse image-to-image translation viadisentangled representations,” IJCV , 2020
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2021
Later among the works it cites.
A. Ramesh, M. Pavlov, G. Goh, S. Gray, C. Voss, A. Radford, M. Chen, and I. Sutskever, “Zero-shot text-to-image generation,” in Proc. ICML , 2021
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
O. Patashnik, Z. Wu, E. Shechtman, D. Cohen-Or, and D. Lischinski, “Styleclip: Text-driven manipulation of stylegan imagery,” in Proc. ICCV , 2021
2021
Later among the works it cites.
A. Sauer, K. Chitta, J. Müller, and A. Geiger, “Projected GANs Converge Faster,” NeurIPS , 2021
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
S. Schwettmann, E. Hernandez, D. Bau, S. Klein, J. Andreas, and A. Torralba, “Toward a visual concept vocabulary for gan latent space,” in Proc. ICCV , 2021
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
A. Srinivas, T.-Y. Lin, N. Parmar, J. Shlens, P. Abbeel, and A. Vaswani, “Bottleneck transformers for visual recognition,” in Proc. CVPR Workshops , 2021
2021
Later among the works it cites.
K. Hong, S. Jeon, H. Yang, J. Fu, and H. Byun, “Domain-aware universal style transfer,” in Proc. ICCV , 2021
2021
Later among the works it cites.
Y. Deng, F. Tang, W. Dong, C. Ma, X. Pan, L. Wang, and C. Xu, “Stytr ∧ \wedge 2: Image style transfer with transformers,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2022
2022
Closest in time.