-
1
-
-
85035363407
-
Wasserstein generative adversarial networks
-
Martin Arjovsky, Soumith Chintala, and Léon Bottou. Wasserstein generative adversarial networks. In ICML, pp. 214–223, 2017.
-
(2017)
ICML
, pp. 214-223
-
-
Arjovsky, M.1
Chintala, S.2
Bottou, L.3
-
2
-
-
85043992858
-
Modulating early visual processing by language
-
Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, and Aaron C Courville. Modulating early visual processing by language. In NIPS, pp. 6576–6586, 2017.
-
(2017)
NIPS
, pp. 6576-6586
-
-
De Vries, H.1
Strub, F.2
Mary, J.3
Larochelle, H.4
Pietquin, O.5
Courville, A.C.6
-
3
-
-
84965143571
-
Deep generative image models using a laplacian pyramid of adversarial networks
-
Emily Denton, Soumith Chintala, Arthur Szlam, and Rob Fergus. Deep generative image models using a laplacian pyramid of adversarial networks. In NIPS, pp. 1486–1494, 2015.
-
(2015)
NIPS
, pp. 1486-1494
-
-
Denton, E.1
Chintala, S.2
Szlam, A.3
Fergus, R.4
-
4
-
-
85041900982
-
Adversarially learned inference
-
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martin Arjovsky, Olivier Mastropietro, and Aaron Courville. Adversarially learned inference. In ICLR, 2017a.
-
(2017)
ICLR
-
-
Dumoulin, V.1
Belghazi, I.2
Poole, B.3
Lamb, A.4
Arjovsky, M.5
Mastropietro, O.6
Courville, A.7
-
5
-
-
85088228106
-
A learned representation for artistic style
-
Vincent Dumoulin, Jonathon Shlens, and Manjunath Kudlur. A learned representation for artistic style. In ICLR, 2017b.
-
(2017)
ICLR
-
-
Dumoulin, V.1
Shlens, J.2
Kudlur, M.3
-
6
-
-
84937849144
-
Generative adversarial nets
-
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. Generative adversarial nets. In NIPS, pp. 2672–2680, 2014.
-
(2014)
NIPS
, pp. 2672-2680
-
-
Goodfellow, I.1
Pouget-Abadie, J.2
Mirza, M.3
Xu, B.4
Warde-Farley, D.5
Ozair, S.6
Courville, A.7
Bengio, Y.8
-
7
-
-
85047004943
-
-
arXiv preprint
-
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville. Improved training of wasserstein GANs. arXiv preprint arXiv:1704.00028, 2017.
-
(2017)
Improved Training of Wasserstein GANs
-
-
Gulrajani, I.1
Ahmed, F.2
Arjovsky, M.3
Dumoulin, V.4
Courville, A.5
-
8
-
-
84986274465
-
Deep residual learning for image recognition
-
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recognition. In CVPR, 2016a.
-
(2016)
CVPR
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
9
-
-
84990050094
-
Identity mappings in deep residual networks
-
Springer
-
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Identity mappings in deep residual networks. In European Conference on Computer Vision, pp. 630–645. Springer, 2016b.
-
(2016)
European Conference on Computer Vision
, pp. 630-645
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
10
-
-
85049562159
-
-
arXiv preprint
-
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, and Sepp Hochreiter. Gans trained by a two time-scale update rule converge to a nash equilibrium. arXiv preprint arXiv:1706.08500, 2017.
-
(2017)
Gans Trained by A Two Time-Scale Update Rule Converge to A Nash Equilibrium
-
-
Heusel, M.1
Ramsauer, H.2
Unterthiner, T.3
Nessler, B.4
Klambauer, G.5
Hochreiter, S.6
-
11
-
-
85046992994
-
Learning to discover cross-domain relations with generative adversarial networks
-
Taeksoo Kim, Moonsu Cha, Hyunsoo Kim, Jungkwon Lee, and Jiwon Kim. Learning to discover cross-domain relations with generative adversarial networks. In ICML, pp. 1857–1865, 2017.
-
(2017)
ICML
, pp. 1857-1865
-
-
Kim, T.1
Cha, M.2
Kim, H.3
Lee, J.4
Kim, J.5
-
12
-
-
85083951076
-
ADaM: A method for stochastic optimization
-
Diederik Kingma and Jimmy Ba. Adam: A method for stochastic optimization. In ICLR, 2015.
-
(2015)
ICLR
-
-
Kingma, D.1
Ba, J.2
-
13
-
-
85035231525
-
Photo-realistic single image super-resolution using a generative adversarial network
-
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, and Wenzhe Shi. Photo-realistic single image super-resolution using a generative adversarial network. In CVPR, 2017.
-
(2017)
CVPR
-
-
Ledig, C.1
Theis, L.2
Huszár, F.3
Caballero, J.4
Cunningham, A.5
Acosta, A.6
Aitken, A.7
Tejani, A.8
Totz, J.9
Wang, Z.10
Shi, W.11
-
16
-
-
85083950959
-
Spectral normalization for generative adversarial networks
-
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida. Spectral normalization for generative adversarial networks. In ICLR, 2018.
-
(2018)
ICLR
-
-
Miyato, T.1
Kataoka, T.2
Koyama, M.3
Yoshida, Y.4
-
17
-
-
85041919547
-
Plug & play generative networks: Conditional iterative generation of images in latent space
-
Anh Nguyen, Jeff Clune, Yoshua Bengio, Alexey Dosovitskiy, and Jason Yosinski. Plug & play generative networks: Conditional iterative generation of images in latent space. In CVPR, 2017.
-
(2017)
CVPR
-
-
Nguyen, A.1
Clune, J.2
Bengio, Y.3
Dosovitskiy, A.4
Yosinski, J.5
-
18
-
-
85018914753
-
F-GaN: Training generative neural samplers using variational divergence minimization
-
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka. f-GAN: Training generative neural samplers using variational divergence minimization. In NIPS, pp. 271–279, 2016.
-
(2016)
NIPS
, pp. 271-279
-
-
Nowozin, S.1
Cseke, B.2
Tomioka, R.3
-
19
-
-
85019040819
-
Conditional image synthesis with auxiliary classifier GANs
-
Augustus Odena, Christopher Olah, and Jonathon Shlens. Conditional image synthesis with auxiliary classifier GANs. In ICML, pp. 2642–2651, 2017.
-
(2017)
ICML
, pp. 2642-2651
-
-
Odena, A.1
Olah, C.2
Shlens, J.3
-
21
-
-
85083950271
-
Unsupervised representation learning with deep convolutional generative adversarial networks
-
Alec Radford, Luke Metz, and Soumith Chintala. Unsupervised representation learning with deep convolutional generative adversarial networks. In ICLR, 2016.
-
(2016)
ICLR
-
-
Radford, A.1
Metz, L.2
Chintala, S.3
-
22
-
-
85006947809
-
Generative adversarial text to image synthesis
-
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee. Generative adversarial text to image synthesis. In ICML, pp. 1060–1069, 2016.
-
(2016)
ICML
, pp. 1060-1069
-
-
Reed, S.1
Akata, Z.2
Yan, X.3
Logeswaran, L.4
Schiele, B.5
Lee, H.6
-
23
-
-
84947041871
-
ImageNet large scale visual recognition challenge
-
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei. ImageNet Large Scale Visual Recognition Challenge. International Journal of Computer Vision (IJCV), 115(3):211–252, 2015. doi: 10.1007/s11263-015-0816-y.
-
(2015)
International Journal of Computer Vision (IJCV)
, vol.115
, Issue.3
, pp. 211-252
-
-
Russakovsky, O.1
Deng, J.2
Su, H.3
Krause, J.4
Satheesh, S.5
Ma, S.6
Huang, Z.7
Karpathy, A.8
Khosla, A.9
Bernstein, M.10
Berg, A.C.11
Fei-Fei, L.12
-
24
-
-
85039461633
-
Temporal generative adversarial nets with singular value clipping
-
Masaki Saito, Eiichi Matsumoto, and Shunta Saito. Temporal generative adversarial nets with singular value clipping. In ICCV, 2017.
-
(2017)
ICCV
-
-
Saito, M.1
Matsumoto, E.2
Saito, S.3
-
25
-
-
85018875486
-
Improved techniques for training GANs
-
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen. Improved techniques for training GANs. In NIPS, pp. 2226–2234, 2016.
-
(2016)
NIPS
, pp. 2226-2234
-
-
Salimans, T.1
Goodfellow, I.2
Zaremba, W.3
Cheung, V.4
Radford, A.5
Chen, X.6
-
26
-
-
85040624643
-
-
arXiv preprint
-
Kumar Sricharan, Raja Bala, Matthew Shreve, Hui Ding, Kumar Saketh, and Jin Sun. Semi-supervised conditional GANs. arXiv preprint arXiv:1708.05789, 2017.
-
(2017)
Semi-Supervised Conditional GANs
-
-
Sricharan, K.1
Bala, R.2
Shreve, M.3
Ding, H.4
Saketh, K.5
Sun, J.6
-
27
-
-
84937522268
-
Going deeper with convolutions
-
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. Going deeper with convolutions. In CVPR, pp. 1–9, 2015.
-
(2015)
CVPR
, pp. 1-9
-
-
Szegedy, C.1
Liu, W.2
Jia, Y.3
Sermanet, P.4
Reed, S.5
Anguelov, D.6
Erhan, D.7
Vanhoucke, V.8
Rabinovich, A.9
-
29
-
-
54749092170
-
80 million tiny images: A large data set for nonparametric object and scene recognition
-
Antonio Torralba, Rob Fergus, and William T Freeman. 80 million tiny images: A large data set for nonparametric object and scene recognition. IEEE transactions on pattern analysis and machine intelligence, 30 (11):1958–1970, 2008.
-
(2008)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.30
, Issue.11
, pp. 1958-1970
-
-
Torralba, A.1
Fergus, R.2
Freeman, W.T.3
-
31
-
-
4143089652
-
Multiscale structural similarity for image quality assessment
-
Zhou Wang, Eero P Simoncelli, and Alan C Bovik. Multiscale structural similarity for image quality assessment. In Asilomar Conference on Signals, Systems and Computers, pp. 1398–1402, 2003.
-
(2003)
Asilomar Conference on Signals, Systems and Computers
, pp. 1398-1402
-
-
Wang, Z.1
Simoncelli, E.P.2
Bovik, A.C.3
-
32
-
-
85040306596
-
Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
-
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaolei Huang, Xiaogang Wang, and Dimitris Metaxas. Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks. In ICCV, 2017.
-
(2017)
ICCV
-
-
Zhang, H.1
Xu, T.2
Li, H.3
Zhang, S.4
Huang, X.5
Wang, X.6
Metaxas, D.7
-
33
-
-
85041892358
-
Unpaired image-to-image translation using cycle-consistent adversarial networks
-
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros. Unpaired image-to-image translation using cycle-consistent adversarial networks. In ICCV, 2017.
-
(2017)
ICCV
-
-
Zhu, J.-Y.1
Park, T.2
Isola, P.3
Efros, A.A.4
|