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Feed-forward CNNs trained for image transformation problems rely on loss functions that measure the similarity between the generated image and a target image.
Image analogies
Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B., Salesin, D.H.: · 2001
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Real-time texture synthesis by patch-based sampling
Liang, L., Liu, C., Xu, Y.Q., Guo, B., Shum, H.Y.: · 2001
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Data-driven hallucination of different times of day from a single outdoor photo
Shih, Y., Paris, S., Durand, F., Freeman, W.T.: · 2013
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Deep convolutional neural network for image deconvolution
Xu, L., Ren, J.S., Liu, C., Jia, J.: · 2014
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: · 2014
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Style transfer for headshot portraits
Shih, Y., Paris, S., Barnes, C., Freeman, W.T., Durand, F.: · 2014
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Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2014
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Adam: A method for stochastic optimization
Kingma, D., Ba, J.: · 2014
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Deep learning face attributes in the wild
Liu, Z., Luo, P., Wang, X., Tang, X.: · 2015
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Image style transfer using convolutional neural networks
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Combining markov random fields and convolutional neural networks for image synthesis
Li, C., Wand, M.: · 2016
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Perceptual losses for real-time style transfer and super-resolution
Johnson, J., Alahi, A., Fei-Fei, L.: · 2016
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Split and match: example-based adaptive patch sampling for unsupervised style transfer
Frigo, O., Sabater, N., Delon, J., Hellier, P.: · 2016
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Fast patch-based style transfer of arbitrary style
Chen, T.Q., Schmidt, M.: · 2016
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Instance normalization: The missing ingredient for fast stylization
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems
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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., Catanzaro, B.: · 2017
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Learning to discover cross-domain relations with generative adversarial networks
Kim, T., Cha, M., Kim, H., Lee, J., Kim, J.: · 2017
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Dualgan: Unsupervised dual learning for image-to-image translation
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Style transfer via texture synthesis
Elad, M., Milanfar, P.: · 2017
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A learned representation for artistic style
Dumoulin, V., Shlens, J., Kudlur, M.: · 2017
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Stable and controllable neural texture synthesis and style transfer using histogram losses
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Template matching with deformable diversity similarity
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