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IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR), pp.63-69, IEEE, 2021. https:\/\/ieeexplore.ieee.org\/abstract\/document\/9565534.","DOI":"10.1109\/MIPR51284.2021.00017"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] P. Isola, J.-Y. Zhu, T. Zhou, and A.A. Efros, \u201cImage-to-image translation with conditional adversarial networks,\u201d Proc. IEEE Computer Vision and Pattern Recognition, pp.1125-1134, 2017.","DOI":"10.1109\/CVPR.2017.632"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] J.-Y. Zhu, T. Park, P. Isola, and A.A. Efros, \u201cUnpaired image-to-image translation using cycle-consistent adversarial networks,\u201d Proc. IEEE International Conference on Computer Vision, pp.2223-2232, 2017.","DOI":"10.1109\/ICCV.2017.244"},{"key":"7","unstructured":"[7] J.Y. Zhu, R. Zhang, D. Pathak, T. Darrell, A.A. Efros, O. Wang, and E. Shechtman, \u201cToward multimodal image-to-image translation,\u201d Advances in Neural Information Processing Systems, pp.465-476, 2017."},{"key":"8","unstructured":"[8] M.Y. Liu, T. Breuel, and J. Kautz, \u201cUnsupervised image-to-image translation networks,\u201d Advances in Neural Information Processing Systems, pp.700-708, 2017."},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] X. Huang, M.Y. Liu, S. Belongie, and J. Kautz, \u201cMultimodal unsupervised image-to-image translation,\u201d Proc. European Conference on Computer Vision, pp.172-189, 2018.","DOI":"10.1007\/978-3-030-01219-9_11"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] Y. Choi, M. Choi, M. Kim, J.-W. Ha, S. Kim, and J. Choo, \u201cStargan: Unified generative adversarial networks for multi-domain image-to-image translation,\u201d Proc. IEEE Computer Vision and Pattern Recognition, pp.8789-8797, 2018.","DOI":"10.1109\/CVPR.2018.00916"},{"key":"11","unstructured":"[11] M. Mirza and S. Osindero, \u201cConditional generative adversarial nets,\u201d arXiv preprint arXiv:1411.1784, 2014."},{"key":"12","unstructured":"[12] I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, \u201cGenerative adversarial nets,\u201d Advances in Neural Information Processing Systems, pp.2672-2680, 2014."},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] L.A. Gatys, A.S. Ecker, and M. Bethge, \u201cImage style transfer using convolutional neural networks,\u201d Proc. IEEE Computer Vision and Pattern Recognition, pp.2414-2423, 2016.","DOI":"10.1109\/CVPR.2016.265"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] J. Johnson, A. Alahi, and L. Fei-Fei, \u201cPerceptual losses for real-time style transfer and super-resolution,\u201d Proc. European Conference on Computer Vision, pp.694-711, 2016.","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] X. Huang and S. Belongie, \u201cArbitrary style transfer in real-time with adaptive instance normalization,\u201d Proc. IEEE Computer Vision and Pattern Recognition, pp.1501-1510, 2017.","DOI":"10.1109\/ICCV.2017.167"},{"key":"16","unstructured":"[16] T. Park, J.Y. Zhu, O. Wang, J. Lu, E. Shechtman, A.A. Efros, and R. Zhang, \u201cSwapping autoencoder for deep image manipulation,\u201d arXiv preprint arXiv:2007.00653, 2020."},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] T. Karras, S. Laine, and T. Aila, \u201cA style-based generator architecture for generative adversarial networks,\u201d Proc. IEEE Computer Vision and Pattern Recognition, pp.4401-4410, 2019.","DOI":"10.1109\/CVPR.2019.00453"},{"key":"18","doi-asserted-by":"crossref","unstructured":"[18] Y. Deng, F. Tang, X. Pan, W. Dong, C. Ma, and C. 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IEEE Computer Vision and Pattern Recognition, pp.7564-7573, 2018.","DOI":"10.1109\/CVPR.2018.00789"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] W. Wang, J. Liu, S. Yang, and Z. Guo, \u201cTypography with Decor: Intelligent text style transfer,\u201d Proc. IEEE Computer Vision and Pattern Recognition, pp.5889-5897, 2019.","DOI":"10.1109\/CVPR.2019.00604"},{"key":"29","unstructured":"[29] Y. Song and Y. Zhang, \u201cCLIPFont: Text guided vector wordart generation,\u201d Proc. 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