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Due to the outstanding capability for data generation, Generative Adversarial Networks (GANs) have attracted considerable attention in unsupervised learning.
A possibility for implementing curiosity and boredom in model-building neural controllers
Jürgen Schmidhuber · 1991
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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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, et al · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Parseval networks: Improving robustness to adversarial examples
Moustapha Cisse, Piotr Bojanowski, Edouard Grave, Yann Dauphin, and Nicolas Usunier · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 2017
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Least squares generative adversarial networks
Xudong Mao, Qing Li, Haoran Xie, Raymond YK Lau, Zhen Wang, and Stephen Paul Smolley · 2017
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Amortised map inference for image super-resolution
Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, and Ferenc Huszár · 2017
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2017
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Energy-based generative adversarial network
Junbo Zhao, Michael Mathieu, and Yann LeCun · 2017
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Deep anomaly detection with outlier exposure
Dan Hendrycks, Mantas Mazeika, and Thomas Dietterich · 2018
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin · 2018
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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and Rayadurgam Srikant · 2018
Cited alongside, same era.
Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Puzzle mix: Exploiting saliency and local statistics for optimal mixup
Jang-Hyun Kim, Wonho Choo, and Hyun Oh Song · 2020
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Transformation consistency regularization–a semi-supervised paradigm for image-to-image translation
Aamir Mustafa and Rafał K Mantiuk · 2020
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Generative adversarial networks are special cases of artificial curiosity (1990) and also closely related to predictability minimization (1991)
Jürgen Schmidhuber · 2020
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Real or not real, that is the question
Yuanbo Xiangli, Yubin Deng, Bo Dai, Chen Change Loy, and Dahua Lin · 2020
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Consistency regularization for generative adversarial networks
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Cited alongside, same era.
Open set learning with counterfactual images
Lawrence Neal, Matthew Olson, Xiaoli Fern, Weng-Keen Wong, and Fuxin Li · 2018
Cited alongside, same era.
Esrgan: Enhanced super-resolution generative adversarial networks
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy · 2018
Cited alongside, same era.
Mixup as locally linear out-of-manifold regularization
Hongyu Guo, Yongyi Mao, and Richong Zhang · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Cited alongside, same era.
A large-scale study on regularization and normalization in gans
Karol Kurach, Mario Lučić, Xiaohua Zhai, Marcin Michalski, and Sylvain Gelly · 2019
Cited alongside, same era.
Large-scale long-tailed recognition in an open world
Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, and Stella X Yu · 2019
Cited alongside, same era.
Han Zhang, Zizhao Zhang, Augustus Odena, and Honglak Lee · 2020
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Improving the speed and quality of gan by adversarial training
Jiachen Zhong, Xuanqing Liu, and Cho-Jui Hsieh · 2020
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Stylemix: Separating content and style for enhanced data augmentation
Minui Hong, Jinwoo Choi, and Gunhee Kim · 2021
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Mos: Towards scaling out-of-distribution detection for large semantic space
Rui Huang and Yixuan Li · 2021
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Deceive d: Adaptive pseudo augmentation for gan training with limited data
Liming Jiang, Bo Dai, Wayne Wu, and Chen Change Loy · 2021
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Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
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Anigan: Style-guided generative adversarial networks for unsupervised anime face generation
Bing Li, Yuanlue Zhu, Yitong Wang, Chia-Wen Lin, Bernard Ghanem, and Linlin Shen · 2021
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Group-wise inhibition based feature regularization for robust classification
Haozhe Liu, Haoqian Wu, Weicheng Xie, Feng Liu, and Linlin Shen · 2021
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Regularizing generative adversarial networks under limited data
Hung-Yu Tseng, Lu Jiang, Ce Liu, Ming-Hsuan Yang, and Weilong Yang · 2021
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Semantically coherent out-of-distribution detection
Jingkang Yang, Haoqi Wang, Litong Feng, Xiaopeng Yan, Huabin Zheng, Wayne Zhang, and Ziwei Liu · 2021
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Out-of-distribution detection using union of 1-dimensional subspaces
Alireza Zaeemzadeh, Niccolò Bisagno, Zeno Sambugaro, Nicola Conci, Nazanin Rahnavard, and Mubarak Shah · 2021
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Kaleido-bert: Vision-language pre-training on fashion domain
Mingchen Zhuge, Dehong Gao, Deng-Ping Fan, Linbo Jin, Ben Chen, Haoming Zhou, Minghui Qiu, and Ling Shao · 2021
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Combating mode collapse in gans via manifold entropy estimation
Haozhe Liu, Bing Li, Haoqian Wu, Hanbang Liang, Yawen Huang, Yuexiang Li, Bernard Ghanem, and Yefeng Zheng · 2022
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Decoupled mixup for out-of-distribution visual recognition
Haozhe Liu, Wentian Zhang, Jinheng Xie, Haoqian Wu, Bing Li, Ziqi Zhang, Yuexiang Li, Yawen Huang, Bernard Ghanem, and Yefeng Zheng · 2023
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