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Unpaired image-to-image translation is the problem of mapping an image in the source domain to one in the target domain, without requiring corresponding image pairs.
Unsupervised image translation
R. Rosales, K. Achan, and B. J. Frey · 2003
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Unsupervised visual domain adaptation using subspace alignment
B. Fernando, A. Habrard, M. Sebban, and T. Tuytelaars · 2013
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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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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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Microsoft COCO: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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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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Unsupervised domain adaptation by backpropagation
Y. Ganin and V. Lempitsky · 2015
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Activitynet: A large-scale video benchmark for human activity understanding
F. C. Heilbron, V. Escorcia, B. Ghanem, and J. C. Niebles · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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Visual domain adaptation: A survey of recent advances
V. M. Patel, R. Gopalan, R. Li, and R. Chellappa · 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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L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2016
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The cityscapes dataset for semantic urban scene understanding
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele · 2016
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Generating images with perceptual similarity metrics based on deep networks
A. Dosovitskiy and T. Brox · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 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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Photo-realistic single image super-resolution using a generative adversarial network
C. Ledig, L. Theis, F. Huszár, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, et al · 2016
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Coupled generative adversarial networks
M.-Y. Liu and O. Tuzel · 2016
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Context encoders: Feature learning by inpainting
D. Pathak, P. Krahenbuhl, J. Donahue, T. Darrell, and A. A. Efros · 2016
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Generative adversarial text to image synthesis
S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele, and H. Lee · 2016
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Playing for data: Ground truth from computer games
S. R. Richter, V. Vineet, S. Roth, and V. Koltun · 2016
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The SYNTHIA dataset: A large collection of synthetic images for semantic segmentation of urban scenes
G. Ros, L. Sellart, J. Materzynska, D. Vazquez, and A. M. Lopez · 2016
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Improved techniques for training gans
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
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Label efficient learning of transferable representations acrosss domains and tasks
Z. Luo, Y. Zou, J. Hoffman, and L. F. Fei-Fei · 2017
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Least squares generative adversarial networks
X. Mao, Q. Li, H. Xie, R. Y. Lau, Z. Wang, and S. P. Smolley · 2017
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Automatic differentiation in pytorch
A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang, Z. DeVito, Z. Lin, A. Desmaison, L. Antiga, and A. Lerer · 2017
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Playing for benchmarks
S. R. Richter, Z. Hayder, and V. Koltun · 2017
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Xgan: Unsupervised image-to-image translation for many-to-many mappings
A. Royer, K. Bousmalis, S. Gouws, F. Bertsch, I. Moressi, F. Cole, and K. Murphy · 2017
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From source to target and back: symmetric bi-directional adaptive gan
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Y. Taigman, A. Polyak, and L. Wolf · 2016
Cited alongside, same era.
Generative image modeling using style and structure adversarial networks
X. Wang and A. Gupta · 2016
Cited alongside, same era.
Generative visual manipulation on the natural image manifold
J.-Y. Zhu, P. Krähenbühl, E. Shechtman, and A. A. Efros · 2016
Cited alongside, same era.
M. Arjovsky, S. Chintala, and L. Bottou · 2017
Cited alongside, same era.
One-sided unsupervised domain mapping
S. Benaim and L. Wolf · 2017
Cited alongside, same era.
Unsupervised pixel-level domain adaptation with generative adversarial networks
K. Bousmalis, N. Silberman, D. Dohan, D. Erhan, and D. Krishnan · 2017
Cited alongside, same era.
Quo vadis, action recognition? a new model and the kinetics dataset
J. Carreira and A. Zisserman · 2017
Cited alongside, same era.
P. Russo, F. M. Carlucci, T. Tommasi, and B. Caputo · 2017
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Scribbler: Controlling deep image synthesis with sketch and color
P. Sangkloy, J. Lu, C. Fang, F. Yu, and J. Hays · 2017
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Unsupervised domain adaptation for semantic segmentation with gans
S. Sankaranarayanan, Y. Balaji, A. Jain, S. N. Lim, and R. Chellappa · 2017
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Learning from simulated and unsupervised images through adversarial training
A. Shrivastava, T. Pfister, O. Tuzel, J. Susskind, W. Wang, and R. Webb · 2017
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The role of minimal complexity functions in unsupervised learning of semantic mappings
T. G. TAU, L. Wolf, and S. B. TAU · 2017
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High-resolution image synthesis and semantic manipulation with conditional gans
T.-C. Wang, M.-Y. Liu, J.-Y. Zhu, A. Tao, J. Kautz, and B. Catanzaro · 2017
Later among the works it cites.
Dualgan: Unsupervised dual learning for image-to-image translation
Z. Yi, H. Zhang, P. Tan, and M. Gong · 2017
Later among the works it cites.
Pyramid scene parsing network
H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia · 2017
Later among the works it cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros · 2017
Later among the works it cites.
Semantic-aware grad-gan for virtual-to-real urban scene adaption
P. Li, X. Liang, D. Jia, and E. P. Xing · 2018
Closest in time.
Da-gan: Instance-level image translation by deep attention generative adversarial networks
S. Ma, J. Fu, C. W. Chen, and T. Mei · 2018
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Deep visual domain adaptation: A survey
M. Wang and W. Deng · 2018
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Generating instance segmentation annotation by geometry-guided gan
W. Xu, Y. Li, and C. Lu · 2018
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