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Detecting fake images is becoming a major goal of computer vision.
Spatial frequency analysis of the visual environment: anisotropy and the carpentered environment hypothesis
E. Switkes, M.J. Mayer, and J.A. Sloan · 1978
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Color and spatial structure in natural scenes
G.J. Burton and I.R. Moorhead · 1987
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The amplitude spectra of natural images
D.J. Tolhurst, Y. Tadmor, and C. Tang · 1992
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Statistics of natural image categories
A. Torralba and A. Oliva · 2003
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Digital camera identification from sensor pattern noise
J. Lukàš, J. Fridrich, and M. Goljan · 2006
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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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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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Deep unsupervised learning using nonequilibrium thermodynamics
J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, and S. Ganguli · 2015
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Neural discrete representation learning
A. Van Den Oord, O. Vinyals, and K. Kavukcuoglu · 2017
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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
K. Zhang, W. Zuo, Y. Chen, D. Meng, and L. Zhang · 2017
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Unpaired image-toimage translation using cycle-consistent adversarial networks
J.-Y. Zhu, T. Park, P. Isola, and A. Efros · 2017
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Large Scale GAN Training for High Fidelity Natural Image Synthesis
A. Brock, J. Donahue, and K. Simonyan · 2018
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Progressive Growing of GANs for Improved Quality, Stability, and Variation
T. Karras, T. Aila, S. Laine, and J. Lehtinen · 2018
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Detection of GAN-generated fake images over social networks
F. Marra, D. Gragnaniello, D. Cozzolino, and L. Verdoliva · 2018
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A style-based generator architecture for generative adversarial networks
T. Karras, S. Laine, and T. Aila · 2019
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Do GANs Leave Artificial Fingerprints?
F. Marra, D. Gragnaniello, L. Verdoliva, and G. Poggi · 2019
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Exploiting visual artifacts to expose deepfakes and face manipulations
F. Matern, C. Riess, , and M. Stamminger · 2019
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Detecting GAN-Generated Imagery using Saturation Cues
S. McCloskey and M. Albright · 2019
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Generative modeling by estimating gradients of the data distribution
Y. Song and S. Ermon · 2019
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Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints
N. Yu, L. Davis, and M. Fritz · 2019
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Detecting and Simulating Artifacts in GAN Fake Images
X. Zhang, S. Karaman, and S.-F. Chang · 2019
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Generative pretraining from pixels
M. Chen, A. Radford, R. Child, J. Wu, H. Jun, D. Luan, and I. Sutskever · 2020
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Noiseprint: A CNN-based camera model fingerprint
D. Cozzolino and L. Verdoliva · 2020
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Watch your up-convolution: CNN based Generative Deep Neural Networks are failing to reproduce spectral distributions
R. Durall, M. Keuper, and J. Keuper · 2020
Cited alongside, same era.
Fourier spectrum discrepancies in deep network generated images
T. Dzanic, K. Shah, and F. D. Witherden · 2020
Cited alongside, same era.
Leveraging Frequency Analysis for Deep Fake Image Recognition
J. Frank, T. Eisenhofer, L. Schönherr, A. Fischer, D. Kolossa, and T. Holz · 2020
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
Y. Balaji, S. Nah, X. Huang, A. Vahdat, J. Song, K. Kreis, M. Aittala, T. Aila, S. Laine, B. Catanzaro, T. Karras, and M.Y. Liu · 2022
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Lighting (in)consistency of paint by text
H. Farid · 2022
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Perspective (in)consistency of paint by text
H. Farid · 2022
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Eyes tell all: Irregular pupil shapes reveal GAN-generated faces
H. Guo, S. Hu, X. Wang, M.C. Chang, and S. Lyu · 2022
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Elucidating the design space of diffusion-based generative models
T. Karras, M. Aittala, T. Aila, and S. Laine · 2022
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Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
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Analyzing and improving the image quality of StyleGAN
T. Karras, S. Laine, M. Aittala, J. Hellsten, J. Lehtinen, and T. Aila · 2020
Cited alongside, same era.
Reverse engineering of generative models: Inferring model hyperparameters from generated images
V. Asnani, X. Yin, T. Hassner, and X. Liu · 2021
Cited alongside, same era.
A Closer Look at Fourier Spectrum Discrepancies for CNN-generated Images Detection
K. Chandrasegaran, N.-T. Tran, and N.-M. Cheung · 2021
Cited alongside, same era.
DALL-E Mini
B. Dayma, S. Patil, P. Cuenca, K. Saifullah, T. Abraham, P. Lê Khàc, L. Melas, and R. Ghosh · 2021
Cited alongside, same era.
Diffusion models beat GANs on image synthesis
P. Dhariwal and A. Nichol · 2021
Cited alongside, same era.
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
A. Q. Nichol, P. Dhariwal, A. Ramesh, P. Shyam, P. Mishkin, B. Mcgrew, I. Sutskever, and M. Chen · 2022
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AI-synthesized faces are indistinguishable from real faces and more trustworthy
S. J. Nightingale and H. Farid · 2022
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Towards universal fake image detectors that generalize across generative models
U. Ojha, Y. Li, and Y. Jae Lee · 2022
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Scalable diffusion models with transformers
W. Peebles and S. Xie · 2022
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Hierarchical text-conditional image generation with clip latents
A. Ramesh, P. Dhariwal, A. Nichol, C. Chu, and M. Chen · 2022
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Towards the detection of diffusion model deepfakes
J. Ricker, S. Damm, T. Holz, and A. Fischer · 2022
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High-resolution image synthesis with latent diffusion models
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
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Stable diffusion
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
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DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Diffusion Models
Z. Sha, Z. Li, N. Yu, and Y. Zhang · 2022
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Diffusion probabilistic model made slim
X. Yang, D. Zhou, J. Feng, and X. Wang · 2022
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On the detection of synthetic images generated by diffusion models
R. Corvi, D. Cozzolino, G. Zingarini, G. Poggi, K. Nagano, and L. Verdoliva · 2023
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Scaling up GANs for Text-to-Image Synthesis
M. Kang, J.-Y. Zhu, R. Zhang, J. Park, E. Shechtman, S. Paris, and T. Park · 2023
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StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis
A. Sauer, T. Karras, S. Laine, A. Geiger, and T. Aila · 2023
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GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis
M. Tao, B.-K. Bao, H. Tang, and C. Xu · 2023
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