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This paper proposes Markovian Generative Adversarial Networks (MGANs), a method for training generative neural networks for efficient texture synthesis.
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Wei, L.Y., Levoy, M.: Fast texture synthesis using tree-structured vector quantization. In: Siggraph. pp. 479–488 (2000)
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Efros, A.A., Freeman, W.T.: Image quilting for texture synthesis and transfer. In: Siggraph. pp. 341–346 (2001)
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Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B., Salesin, D.H.: Image analogies. In: Siggraph. pp. 327–340 (2001)
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Kwatra, V., Schödl, A., Essa, I., Turk, G., Bobick, A.: Graphcut textures: Image and video synthesis using graph cuts. ACM Trans. Graph. 22(3), 277–286 (Jul 2003)
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Kwatra, V., Essa, I., Bobick, A., Kwatra, N.: Texture optimization for example-based synthesis. Siggraph 24(3), 795–802 (2005)
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Barnes, C., Shechtman, E., Finkelstein, A., Goldman, D.B.: Patchmatch: A randomized correspondence algorithm for structural image editing. Siggrah pp. 24:1–24:11 (2009)
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Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: NIPS. pp. 2672–2680 (2014)
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Zeiler, M.D., Fergus, R.: Visualizing and understanding convolutional networks. In: ECCV. pp. 818–833 (2014)
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Chintala, S.: Easy benchmarking of all publicly accessible implementations of convnets. https://github.com/soumith/convnet-benchmarks (2015)
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Denton, E.L., Fergus, R., Szlam, A., Chintala, S.: Deep generative image models using a laplacian pyramid of adversarial networks. In: NIPS (2015)
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Cited alongside, same era.
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Cited alongside, same era.
Gauthier, J.: Conditional generative adversarial nets for convolutional face generation. http://www.foldl.me/2015/conditional-gans-face-generation/ (2015)
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Springenberg, J., Dosovitskiy, A., Brox, T., Riedmiller, M.: Striving for simplicity: The all convolutional net (2015), http://lmb.informatik.uni-freiburg.de/Publications/2015/DB15a
2015
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Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: ICCV (2015)
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Mahendran, A., Vedaldi, A.: Understanding deep image representations by inverting them. In: CVPR (2015)
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Mordvintsev, A., Olah, C., Tyka, M.: Inceptionism: Going deeper into neural networks. http://googleresearch.blogspot.com/2015/06/inceptionism-going-deeper-into-neural.html (2015)
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