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The recent development of generative models unleashes the potential of generating hyper-realistic fake images.
Fakespotter: A simple baseline for spotting ai-synthesized fake faces. arxiv 2019
R Wang, L Ma, F Juefei-Xu, X Xie, J Wang, and Y Liu · 1909
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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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Rich models for steganalysis of digital images
Jessica Fridrich and Jan Kodovsky · 2012
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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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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger 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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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu et al · 2017
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock et al · 2018
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Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi et al · 2018
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Forensictransfer: Weakly-supervised domain adaptation for forgery detection
Davide Cozzolino, Justus Thies, Andreas Rössler, Christian Riess, Matthias Nießner, and Luisa Verdoliva · 2018
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras et al · 2018
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Large scale adversarial representation learning
Jeff Donahue and Karen Simonyan · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras et al · 2019
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Stgan: A unified selective transfer network for arbitrary image attribute editing
Ming Liu et al · 2019
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Detecting gan generated fake images using co-occurrence matrices
Lakshmanan Nataraj, Tajuddin Manhar Mohammed, Shivkumar Chandrasekaran, Arjuna Flenner, Jawadul H Bappy, Amit K Roy-Chowdhury, and BS Manjunath · 2019
Cited alongside, same era.
Semantic image synthesis with spatially-adaptive normalization
Taesung Park et al · 2019
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Detecting and simulating artifacts in gan fake images
Xu Zhang, Svebor Karaman, and Shih-Fu Chang · 2019
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What makes fake images detectable? understanding properties that generalize
Lucy Chai, David Bau, Ser-Nam Lim, and Phillip Isola · 2020
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Watch your up-convolution: Cnn based generative deep neural networks are failing to reproduce spectral distributions
Ricard Durall, Margret Keuper, and Janis Keuper · 2020
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Ost: Improving generalization of deepfake detection via one-shot test-time training
Liang Chen, Yong Zhang, Yibing Song, Jue Wang, and Lingqiao Liu · 2022
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Vector quantized diffusion model for text-to-image synthesis
Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, and Baining Guo · 2022
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Leveraging frequency analysis for deep fake image recognition
Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Global texture enhancement for fake face detection in the wild
Zhengzhe Liu, Xiaojuan Qi, and Philip HS Torr · 2020
Cited alongside, same era.
Thinking in frequency: Face forgery detection by mining frequency-aware clues
Yuyang Qian, Guojun Yin, Lu Sheng, Zixuan Chen, and Jing Shao · 2020
Cited alongside, same era.
Cnn-generated images are surprisingly easy to spot… for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, and Alexei A Efros · 2020
Cited alongside, same era.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Cited alongside, same era.
Luping Liu, Yi Ren, Zhijie Lin, and Zhou Zhao · 2022
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Towards the detection of diffusion model deepfakes
Jonas Ricker, Simon Damm, Thorsten Holz, and Asja Fischer · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Towards universal fake image detectors that generalize across generative models
Utkarsh Ojha, Yuheng Li, and Yong Jae Lee · 2023
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Learning on gradients: Generalized artifacts representation for gan-generated images detection
Chuangchuang Tan, Yao Zhao, Shikui Wei, Guanghua Gu, and Yunchao Wei · 2023
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Dire for diffusion-generated image detection
Zhendong Wang, Jianmin Bao, Wengang Zhou, Weilun Wang, Hezhen Hu, Hong Chen, and Houqiang Li · 2023
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Patchcraft: Exploring texture patch for efficient ai-generated image detection
Nan Zhong, Yiran Xu, Zhenxing Qian, and Xinpeng Zhang · 2023
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Rethinking the up-sampling operations in cnn-based generative network for generalizable deepfake detection
Chuangchuang Tan, Yao Zhao, Shikui Wei, Guanghua Gu, Ping Liu, and Yunchao Wei · 2024
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