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Generative adversarial networks (GANs) have shown outstanding performance on a wide range of problems in computer vision, graphics, and machine learning, but often require numerous training data and heavy computational resources.
Caltech-256 object category dataset
G. Griffin, A. Holub, and P. Perona · 2007
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Automated flower classification over a large number of classes
M.-E. Nilsback and A. Zisserman · 2008
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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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Learning hybrid image templates (hit) by information projection
Z. Si and S.-C. Zhu · 2011
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The caltech-ucsd birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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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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Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2014
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How transferable are features in deep neural networks?
J. Yosinski, J. Clune, Y. Bengio, and H. Lipson · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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Fitnets: Hints for thin deep nets
A. Romero, N. Ballas, S. E. Kahou, A. Chassang, C. Gatta, and Y. Bengio · 2015
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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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Deligan: Generative adversarial networks for diverse and limited data
S. Gurumurthy, R. Kiran Sarvadevabhatla, and R. Venkatesh Babu · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
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Discriminator rejection sampling
S. Azadi, C. Olsson, T. Darrell, I. Goodfellow, and A. Odena · 2018
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Recycle-gan: Unsupervised video retargeting
A. Bansal, S. Ma, D. Ramanan, and Y. Sheikh · 2018
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Optimizing the latent space of generative networks
P. Bojanowski, A. Joulin, D. Lopez-Pas, and A. Szlam · 2018
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Explicit inductive bias for transfer learning with convolutional networks
X. Li, Y. Grandvalet, and F. Davoine · 2018
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Are gans created equal? a large-scale study
M. Lucic, K. Kurach, M. Michalski, S. Gelly, and O. Bousquet · 2018
Cited alongside, same era.
cgans with projection discriminator
T. Miyato and M. Koyama · 2018
Cited alongside, same era.
Animeface character dataset, 2018
C. Nagadomi · 2018
Cited alongside, same era.
Metropolis-hastings generative adversarial networks
R. Turner, J. Hung, E. Frank, Y. Saatci, and J. Yosinski · 2018
Cited alongside, same era.
Video-to-video synthesis
T.-C. Wang, M.-Y. Liu, J.-Y. Zhu, G. Liu, A. Tao, J. Kautz, and B. Catanzaro · 2018
Cited alongside, same era.
Transferring gans: generating images from limited data
Y. Wang, C. Wu, L. Herranz, J. van de Weijer, A. Gonzalez-Garcia, and B. Raducanu · 2018
Cited alongside, same era.
A large-scale study on regularization and normalization in gans
K. Kurach, M. Lučić, X. Zhai, M. Michalski, and S. Gelly · 2019
Later among the works it cites.
Few-shot unsupervised image-to-image translation
M.-Y. Liu, X. Huang, A. Mallya, T. Karras, T. Aila, J. Lehtinen, and J. Kautz · 2019
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High-fidelity image generation with fewer labels
M. Lucic, M. Tschannen, M. Ritter, X. Zhai, O. Bachem, and S. Gelly · 2019
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Instagan: Instance-aware image-to-image translation
S. Mo, M. Cho, and J. Shin · 2019
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Mining gold samples for conditional gans
S. Mo, C. Kim, S. Kim, M. Cho, and J. Shin · 2019
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Image generation from small datasets via batch statistics adaptation
A. Noguchi and T. Harada · 2019
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S. Ahn, S. X. Hu, A. Damianou, N. D. Lawrence, and Z. Dai · 2019
Cited alongside, same era.
Large scale GAN training for high fidelity natural image synthesis
A. Brock, J. Donahue, and K. Simonyan · 2019
Cited alongside, same era.
Everybody dance now
C. Chan, S. Ginosar, T. Zhou, and A. A. Efros · 2019
Cited alongside, same era.
Self-supervised gans via auxiliary rotation loss
T. Chen, X. Zhai, M. Ritter, M. Lucic, and N. Houlsby · 2019
Cited alongside, same era.
Stargan v2: Diverse image synthesis for multiple domains
Y. Choi, Y. Uh, J. Yoo, and J.-W. Ha · 2019
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2019
Cited alongside, same era.
Semantic image synthesis with spatially-adaptive normalization
T. Park, M.-Y. Liu, T.-C. Wang, and J.-Y. Zhu · 2019
Later among the works it cites.
Relational knowledge distillation
W. Park, D. Kim, Y. Lu, and M. Cho · 2019
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Small-gan: Speeding up gan training using core-sets
S. Sinha, H. Zhang, A. Goyal, Y. Bengio, H. Larochelle, and A. Odena · 2019
Later among the works it cites.
Discriminator optimal transport
A. Tanaka · 2019
Later among the works it cites.
Cnn-generated images are surprisingly easy to spot… for now
S.-Y. Wang, O. Wang, R. Zhang, A. Owens, and A. A. Efros · 2019
Later among the works it cites.
Few-shot video-to-video synthesis
T.-C. Wang, M.-Y. Liu, A. Tao, G. Liu, B. Catanzaro, and J. Kautz · 2019
Later among the works it cites.
Minegan: effective knowledge transfer from gans to target domains with few images
Y. Wang, A. Gonzalez-Garcia, D. Berga, L. Herranz, F. S. Khan, and J. van de Weijer · 2019
Later among the works it cites.
Few-shot adversarial learning of realistic neural talking head models
E. Zakharov, A. Shysheya, E. Burkov, and V. Lempitsky · 2019
Later among the works it cites.
Consistency regularization for generative adversarial networks
H. Zhang, Z. Zhang, A. Odena, and H. Lee · 2020
Closest in time.
Improved consistency regularization for gans
Z. Zhao, S. Singh, H. Lee, Z. Zhang, A. Odena, and H. Zhang · 2020
Closest in time.