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Generative adversarial networks (GANs) have remarkably advanced in diverse domains, especially image generation and editing.
Optimizing classifier performance via an approximation to the Wilcoxon-Mann-Whitney statistic
Yan, L.; Dodier, R. H.; Mozer, M.; and Wolniewicz, R. H. 2003 · 2003
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T-gd: Transferable gan-generated images detection framework
Jeon, H.; Bang, Y.; Kim, J.; and Woo, S. S. 2020 · 2008
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ImageNet Classification with Deep Convolutional Neural Networks
Krizhevsky, A.; Sutskever, I.; and Hinton, G. 2012 · 2012
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Generative Adversarial Nets
Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2014 · 2014
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Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K.; and Zisserman, A. 2014 · 2014
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Deep Learning Face Attributes in the Wild
Liu, Z.; Luo, P.; Wang, X.; and Tang, X. 2015 · 2015
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LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
Yu, F.; Zhang, Y.; Song, S.; Seff, A.; and Xiao, J. 2015 · 2015
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A deep learning approach to universal image manipulation detection using a new convolutional layer
Bayar, B.; and Stamm, M. C. 2016 · 2016
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Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Sgdr: Stochastic gradient descent with warm restarts
Loshchilov, I.; and Hutter, F. 2016 · 2016
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Xception: Deep learning with depthwise separable convolutions
Chollet, F. 2017 · 2017
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Progressive growing of gans for improved quality, stability, and variation
Karras, T.; Aila, T.; Laine, S.; and Lehtinen, J. 2017 · 2017
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Large scale GAN training for high fidelity natural image synthesis
Brock, A.; Donahue, J.; and Simonyan, K. 2018 · 2018
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Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Choi, Y.; Choi, M.; Kim, M.; Ha, J.-W.; Kim, S.; and Choo, J. 2018 · 2018
Cited alongside, same era.
Forensictransfer: Weakly-supervised domain adaptation for forgery detection
Cozzolino, D.; Thies, J.; Rössler, A.; Riess, C.; Nießner, M.; and Verdoliva, L. 2018 · 2018
Cited alongside, same era.
Forensics face detection from GANs using convolutional neural network
Do, N.-T.; Na, I.-S.; and Kim, S.-H. 2018 · 2018
Cited alongside, same era.
Can forensic detectors identify gan generated images?
Li, H.; Chen, H.; Li, B.; and Tan, S. 2018 · 2018
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
Karras, T.; Laine, S.; and Aila, T. 2019 · 2019
Cited alongside, same era.
Rethinking the Hyperparameters for Fine-tuning
Li, H.; Chaudhari, P.; Yang, H.; Lam, M.; Ravichandran, A.; Bhotika, R.; and Soatto, S. 2020 · 2020
Later among the works it cites.
GAN-Generated Image Detection with Self-Attention Mechanism against GAN Generator Defect
Mi, Z.; Jiang, X.; Sun, T.; and Xu, K. 2020 · 2020
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CNN-Generated Images Are Surprisingly Easy to Spot… for Now
Wang, S. Y.; Wang, O.; Zhang, R.; Owens, A.; and Efros, A. A. 2020b · 2020
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The Biggest Deepfake Abuse Site Is Growing in Disturbing Ways
BURGESS, M. 2021 · 2021
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Locally GAN-generated face detection based on an improved Xception
Chen, B.; Ju, X.; Xiao, B.; Ding, W.; Zheng, Y.; and de Albuquerque, V. H. C. 2021 · 2021
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Repvgg: Making vgg-style convnets great again
Ding, X.; Zhang, X.; Ma, N.; Han, J.; Ding, G.; and Sun, J. 2021 · 2021
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Mccloskey, S.; and Albright, M. 2019 · 2019
Cited alongside, same era.
Detecting GAN generated Fake Images using Co-occurrence Matrices
Nataraj, L.; Mohammed, T. M.; Chandrasekaran, S.; Flenner, A.; Bappy, J. H.; Roy-Chowdhury, A. K.; and Manjunath, B. S. 2019 · 2019
Cited alongside, same era.
Semantic image synthesis with spatially-adaptive normalization
Park, T.; Liu, M.-Y.; Wang, T.-C.; and Zhu, J.-Y. 2019 · 2019
Cited alongside, same era.
Efficientnet: Rethinking model scaling for convolutional neural networks
Tan, M.; and Le, Q. 2019 · 2019
Cited alongside, same era.
Exposing deep fakes using inconsistent head poses
Yang, X.; Li, Y.; and Lyu, S. 2019 · 2019
Cited alongside, same era.
Cutmix: Regularization strategy to train strong classifiers with localizable features
Yun, S.; Han, D.; Oh, S. J.; Chun, S.; Choe, J.; and Yoo, Y. 2019 · 2019
Cited alongside, same era.
Identification of deep network generated images using disparities in color components - ScienceDirect
Hla, B.; Bla, B.; Sta, B.; and Jha, B. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
Are GAN generated images easy to detect? A critical analysis of the state-of-the-art
Gragnaniello, D.; Cozzolino, D.; Marra, F.; Poggi, G.; and Verdoliva, L. 2021 · 2021
Later among the works it cites.
Robust knowledge transfer via hybrid forward on the teacher-student model
Song, L.; Wu, J.; Yang, M.; Zhang, Q.; Li, Y.; and Yuan, J. 2021 · 2021
Later among the works it cites.
Eyes tell all: Irregular pupil shapes reveal GAN-generated faces
Guo, H.; Hu, S.; Wang, X.; Chang, M.-C.; and Lyu, S. 2022a · 2022
Later among the works it cites.
FrePGAN: robust deepfake detection using frequency-level perturbations
Jeong, Y.; Kim, D.; Ro, Y.; and Choi, J. 2022 · 2022
Later among the works it cites.
A convnet for the 2020s
Liu, Z.; Mao, H.; Wu, C.-Y.; Feichtenhofer, C.; Darrell, T.; and Xie, S. 2022 · 2022
Later among the works it cites.
Learning on Gradients: Generalized Artifacts Representation for GAN-Generated Images Detection
Tan, C.; Zhao, Y.; Wei, S.; Gu, G.; and Wei, Y. 2023 · 2023
Closest in time.
GAN-generated Faces Detection: A Survey and New Perspectives
Wang, X.; Guo, H.; Hu, S.; Chang, M.-C.; and Lyu, S. 2023 · 2023
Closest in time.