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Recently, there have been several promising methods to generate realistic imagery from deep convolutional networks.
Plenoptic modeling: An image-based rendering system
L. McMillan and G. Bishop · 1995
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Texture synthesis by non-parametric sampling
A. A. Efros and T. K. Leung · 1999
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Colorization using optimization
A. Levin, D. Lischinski, and Y. Weiss · 2004
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Manga colorization
Y. Qu, T.-T. Wong, and P.-A. Heng · 2006
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Scene completion using millions of photographs
J. Hays and A. A. Efros · 2007
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Patchmatch: a randomized correspondence algorithm for structural image editing
C. Barnes, E. Shechtman, A. Finkelstein, and D. Goldman · 2009
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Sketch2photo: internet image montage
T. Chen, M.-M. Cheng, P. Tan, A. Shamir, and S.-M. Hu · 2009
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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
H. Lee, R. Grosse, R. Ranganath, and A. Y. Ng · 2009
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Deep Boltzmann machines
R. Salakhutdinov and G. Hinton · 2009
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Lazybrush: Flexible painting tool for hand-drawn cartoons
D. Sỳkora, J. Dingliana, and S. Collins · 2009
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Face photo-sketch synthesis and recognition
X. Wang and X. Tang · 2009
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https://www.youtube.com/watch?v=Gyu2yPwiQvA , 2012
Convert photo to line drawing · 2012
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How do humans sketch objects?
M. Eitz, J. Hays, and M. Alexa · 2012
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Xdog: an extended difference-of-gaussians compendium including advanced image stylization
H. WinnemöLler, J. E. Kyprianidis, and S. C. Olsen · 2012
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2014
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Learning to generate chairs with convolutional neural networks
A. Dosovitskiy, J. Tobias Springenberg, and T. Brox · 2015
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Draw: A recurrent neural network for image generation
K. Gregor, I. Danihelka, A. Graves, D. J. Rezende, and D. Wierstra · 2015
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Deep learning face attributes in the wild
Z. Liu, P. Luo, X. Wang, and X. Tang · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
Cited alongside, same era.
U-Net: Convolutional Networks for Biomedical Image Segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
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LSUN: construction of a large-scale image dataset using deep learning with humans in the loop
F. Yu, Y. Zhang, S. Song, A. Seff, and J. Xiao · 2015
Cited alongside, same era.
https://www.youtube.com/watch?v=QNmniB_5Nz0/ , 2016
Create filter gallery photocopy effect with single step in photoshop · 2016
Cited alongside, same era.
Scribblesup: Scribble-supervised convolutional networks for semantic segmentation
D. Lin, J. Dai, J. Jia, K. He, and J. Sun · 2016
Closest in time.
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
A. Nguyen, A. Dosovitskiy, J. Yosinski, T. Brox, and J. Clune · 2016
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Plug & play generative networks: Conditional iterative generation of images in latent space
A. Nguyen, J. Yosinski, Y. Bengio, A. Dosovitskiy, and J. Clune · 2016
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Deconvolution and checkerboard artifacts
A. Odena, V. Dumoulin, and C. Olah · 2016
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Pixel recurrent neural networks
A. v. d. Oord, N. Kalchbrenner, and K. Kavukcuoglu · 2016
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Context encoders: Feature learning by inpainting
D. Pathak, P. Krähenbühl, J. Donahue, T. Darrell, and A. Efros · 2016
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Neural Photo Editing with Introspective Adversarial Networks
A. Brock, T. Lim, J. M. Ritchie, and N. Weston · 2016
Cited alongside, same era.
Semantic style transfer and turning two-bit doodles into fine artworks
A. J. Champandard · 2016
Cited alongside, same era.
Generating images with perceptual similarity metrics based on deep networks
A. Dosovitskiy and T. Brox · 2016
Cited alongside, same era.
Image style transfer using convolutional neural networks
L. A. Gatys, A. S. Ecker, and M. Bethge · 2016
Cited alongside, same era.
Convolutional sketch inversion
Y. Güçlütürk, U. Güçlü, R. van Lier, and M. A. van Gerven · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification
S. Iizuka, E. Simo-Serra, and H. Ishikawa · 2016
Cited alongside, same era.
Closest in time.
Learning what and where to draw
S. Reed, Z. Akata, S. Mohan, S. Tenka, B. Schiele, and H. Lee · 2016
Closest in time.
Generative adversarial text-to-image synthesis
S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele, and H. Lee · 2016
Closest in time.
The sketchy database: Learning to retrieve badly drawn bunnies
P. Sangkloy, N. Burnell, C. Ham, and J. Hays · 2016
Closest in time.
Learning to Simplify: Fully Convolutional Networks for Rough Sketch Cleanup
E. Simo-Serra, S. Iizuka, K. Sasaki, and H. Ishikawa · 2016
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Conditional image generation with pixelcnn decoders
A. van den Oord, N. Kalchbrenner, L. Espeholt, O. Vinyals, A. Graves, et al · 2016
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Generative image modeling using style and structure adversarial networks
X. Wang and A. Gupta · 2016
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Attribute2image: Conditional image generation from visual attributes
X. Yan, J. Yang, K. Sohn, and H. Lee · 2016
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Semantic image inpainting with perceptual and contextual losses
R. Yeh, C. Chen, T. Y. Lim, M. Hasegawa-Johnson, and M. N. Do · 2016
Closest in time.
Pixel-level domain transfer
D. Yoo, N. Kim, S. Park, A. S. Paek, and I. S. Kweon · 2016
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Colorful image colorization
R. Zhang, P. Isola, and A. A. Efros · 2016
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View synthesis by appearance flow
T. Zhou, S. Tulsiani, W. Sun, J. Malik, and A. A. Efros · 2016
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Generative visual manipulation on the natural image manifold
J.-Y. Zhu, P. Krähenbühl, E. Shechtman, and A. A. Efros · 2016
Closest in time.