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We present a simple nearest-neighbor (NN) approach that synthesizes high-frequency photorealistic images from an "incomplete" signal such as a low-resolution image, a surface normal map, or edges.
Texture synthesis by non-parametric sampling
A. A. Efros and T. K. Leung · 1999
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Image analogies
A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D. H. Salesin · 2001
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Example-based super-resolution
W. T. Freeman, T. R. Jones, and E. C. Pasztor · 2002
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Learning a similarity metric discriminatively, with application to face verification
S. Chopra, R. Hadsell, and Y. LeCun · 2005
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A data-driven approach to quantifying natural human motion
L. Ren, A. Patrick, A. A. Efros, J. K. Hodgins, and J. M. Rehg · 2005
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Similarity by composition
O. Boiman and M. Irani · 2006
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Detecting irregularities in images and in video
O. Boiman and M. Irani · 2007
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Scene completion using millions of photographs
J. Hays and A. A. Efros · 2007
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Face hallucination: Theory and practice
C. Liu, H. Shum, and W. T. Freeman · 2007
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Cg2real: Improving the realism of computer generated images using a large collection of photographs
M. K. Johnson, K. Dale, S. Avidan, H. Pfister, W. T. Freeman, and W. Matusik · 2011
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Sift flow: Dense correspondence across scenes and its applications
C. Liu, J. Yuen, and A. Torralba · 2011
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Data-driven visual similarity for cross-domain image matching
A. Shrivastava, T. Malisiewicz, A. Gupta, and A. A. Efros · 2011
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Cats and dogs
O. M. Parkhi, A. Vedaldi, A. Zisserman, and C. V. Jawahar · 2012
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Deep learning made easier by linear transformations in perceptrons
T. Raiko, H. Valpola, and Y. LeCun · 2012
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A bayesian approach to alignment-based image hallucination
M. F. Tappen and C. Liu · 2012
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Restoring an image taken through a window covered with dirt or rain
D. Eigen, D. Krishnan, and R. Fergus · 2013
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Data-driven 3D primitives for single image understanding
D. F. Fouhey, A. Gupta, and M. Hebert · 2013
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Pedestrian detection with unsupervised multi-stage feature learning
P. Sermanet, K. Kavukcuoglu, S. Chintala, and Y. LeCun · 2013
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Generative adversarial networks
I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. C. Courville, and Y. Bengio · 2014
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Do convnets learn correspondence?
J. Long, N. Zhang, and T. Darrell · 2014
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The role of context for object detection and semantic segmentation in the wild
R. Mottaghi, X. Chen, X. Liu, N.-G. Cho, S.-W. Lee, S. Fidler, R. Urtasun, and A. Yuille · 2014
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Fine-Grained Visual Comparisons with Local Learning
A. Yu and K. Grauman · 2014
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Learning visual similarity for product design with convolutional neural networks
S. Bell and K. Bala · 2015
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Deep generative image models using a laplacian pyramid of adversarial networks
Convolutional sketch inversion
Y. Gucluturk, U. Guclu, R. van Lier, and M. A. J. van Gerven · 2016
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Stacked generative adversarial networks
X. Huang, Y. Li, O. Poursaeed, J. E. Hopcroft, and S. J. Belongie · 2016
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Image-to-image translation with conditional adversarial networks
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros · 2016
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Perceptual losses for real-time style transfer and super-resolution
J. Johnson, A. Alahi, and L. Fei-Fei · 2016
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Warpnet: Weakly supervised matching for single-view reconstruction
A. Kanazawa, D. W. Jacobs, and M. Chandraker · 2016
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E. L. Denton, S. Chintala, A. Szlam, and R. Fergus · 2015
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Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
D. Eigen and R. Fergus · 2015
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Hypercolumns for object segmentation and fine-grained localization
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 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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Fully convolutional models for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
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Designing deep networks for surface normal estimation
X. Wang, D. Fouhey, and A. Gupta · 2015
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G. Larsson, M. Maire, and G. Shakhnarovich · 2016
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Photo-realistic single image super-resolution using a generative adversarial network
C. Ledig, L. Theis, F. Huszar, J. Caballero, A. P. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi · 2016
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Generative image modeling using style and structure adversarial networks
X. Wang and A. Gupta · 2016
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
J. Wu, C. Zhang, T. Xue, W. T. Freeman, and J. B. Tenenbaum · 2016
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
H. Zhang, T. Xu, H. Li, S. Zhang, X. Huang, X. Wang, and D. N. Metaxas · 2016
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Colorful image colorization
R. Zhang, P. Isola, and A. A. Efros · 2016
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Learning dense correspondence via 3d-guided cycle consistency
T. Zhou, P. Krähenbühl, M. Aubry, Q. Huang, 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
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Pixelnet: Representation of the pixels, by the pixels, and for the pixels
A. Bansal, X. Chen, B. Russell, A. Gupta, and D. Ramanan · 2017
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Photographic image synthesis with cascaded refinement networks
Q. Chen and V. Koltun · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
J. Zhu, T. Park, P. Isola, and A. A. Efros · 2017
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