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The goal of this paper is to embed controllable factors, i.e., natural language descriptions, into image-to-image translation with generative adversarial networks, which allows text descriptions to determine the visual attributes of synthetic images.
Manigan: Text-guided image manipulation
Li, B., Qi, X., Lukasiewicz, T., and Torr, P · 1912
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Natural language processing with Python: Analyzing
Bird, S., Klein, E., and Loper, E · 2009
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
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Microsoft COCO
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., and Zitnick, C. L · 2014
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Deep generative image models using a Laplacian
Denton, E. L., Chintala, S., Fergus, R., et al · 2015
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Generative adversarial text to image synthesis
Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., and Lee, H · 2016
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Photographic image synthesis with cascaded refinement networks
Chen, Q. and Koltun, V · 2017
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Semantic image synthesis via adversarial learning
Dong, H., Yu, S., Wu, C., and Guo, Y · 2017
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Stacked generative adversarial networks
Huang, X., Li, Y., Poursaeed, O., Hopcroft, J., and Belongie, S · 2017
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Image-to-image translation with conditional adversarial networks
Isola, P., Zhu, J.-Y., Zhou, T., and Efros, A. A · 2017
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StackGAN
Zhang, H., Xu, T., Li, H., Zhang, S., Wang, X., Huang, X., and Metaxas, D. N · 2017
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Inferring semantic layout for hierarchical text-to-image synthesis
Hong, S., Yang, D., Choi, J., and Lee, H · 2018
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Image generation from scene graphs
Johnson, J., Gupta, A., and Fei-Fei, L · 2018
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Instagan: Instance-aware image-to-image translation
Mo, S., Cho, M., and Shin, J · 2018
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StackGAN
Zhang, H., Xu, T., Li, H., Zhang, S., Wang, X., Huang, X., and Metaxas, D. N · 2018
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Specifying object attributes and relations in interactive scene generation
Ashual, O. and Wolf, L · 2019
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Semantic image synthesis with spatially-adaptive normalization
Park, T., Liu, M.-Y., Wang, T.-C., and Zhu, J.-Y · 2019
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Controlling style and semantics in weakly-supervised image generation
Pavllo, D., Lucchi, A., and Hofmann, T · 2019
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Singan: Learning a generative model from a single natural image
Shaham, T. R., Dekel, T., and Michaeli, T · 2019
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Text-adaptive generative adversarial networks: manipulating images with natural language
Nam, S., Kim, Y., and Kim, S. J · 2018
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Semi-parametric image synthesis
Qi, X., Chen, Q., Jia, J., and Koltun, V · 2018
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High-resolution image synthesis and semantic manipulation with conditional gans
Wang, T.-C., Liu, M.-Y., Zhu, J.-Y., Tao, A., Kautz, J., and Catanzaro, B · 2018
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Object-driven text-to-image synthesis via adversarial training
Li, W., Zhang, P., Zhang, L., Huang, Q., He, X., Lyu, S., and Gao, J
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Tang, H., Xu, D., Yan, Y., Torr, P. H., and Sebe, N · 2019
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Image generation from layout
Zhao, B., Meng, L., Yin, W., and Sigal, L · 2019
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Controllable text-to-image generation
Li, B., Qi, X., Lukasiewicz, T., and Torr, P · 2073
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