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The extraordinary ability of generative models enabled the generation of images with such high quality that human beings cannot distinguish Artificial Intelligence (AI) generated images from real-life photographs.
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, Geoffrey Hinton, et al · 2009
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Underwater image processing: state of the art of restoration and image enhancement methods
Raimondo Schettini and Silvia Corchs · 2010
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Not all image regions matter: Masked vector quantization for autoregressive image generation
Mengqi Huang, Zhendong Mao, Quan Wang, and Yongdong Zhang · 2011
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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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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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions
Peter Young, Alice Lai, Micah Hodosh, and Julia Hockenmaier · 2014
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Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 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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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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Tutorial on variational autoencoders
Carl Doersch · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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beta-vae: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2016
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Data augmentation generative adversarial networks
Antreas Antoniou, Amos Storkey, and Harrison Edwards · 2017
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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CVAE-GAN: fine-grained image generation through asymmetric training
Jianmin Bao, Dong Chen, Fang Wen, Houqiang Li, and Gang Hua · 2017
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Discordchatexporter, 2017
Oleksii Holub · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Durk P Kingma and Prafulla Dhariwal · 2018
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Detection of gan-generated fake images over social networks
Francesco Marra, Diego Gragnaniello, Davide Cozzolino, and Luisa Verdoliva · 2018
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Image transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Do gans leave artificial fingerprints?
Francesco Marra, Diego Gragnaniello, Luisa Verdoliva, and Giovanni Poggi · 2019
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Generating diverse high-fidelity images with vq-vae-2
Ali Razavi, Aaron Van den Oord, and Oriol Vinyals · 2019
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Detecting photoshopped faces by scripting photoshop
Sheng-Yu Wang, Oliver Wang, Andrew Owens, Richard Zhang, and Alexei A Efros · 2019
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Multi-attribute transfer via disentangled representation
Jianfu Zhang, Yuanyuan Huang, Yaoyi Li, Weijie Zhao, and Liqing Zhang · 2019
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Stylegan-xl: Scaling stylegan to large diverse datasets
Axel Sauer, Katja Schwarz, and Andreas Geiger · 2022
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Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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De-fake: Detection and attribution of fake images generated by text-to-image diffusion models
Zeyang Sha, Zheng Li, Ning Yu, and Yang Zhang · 2022
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Df-gan: A simple and effective baseline for text-to-image synthesis
Ming Tao, Hao Tang, Fei Wu, Xiao-Yuan Jing, Bing-Kun Bao, and Changsheng Xu · 2022
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2022 ieee image and video processing cup synthetic image detection
Luisa Verdoliva, Davide Cozzolino, and Koki Nagano · 2022
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Stargan v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
Leveraging frequency analysis for deep fake image recognition
Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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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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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Cited alongside, same era.
Zijie J Wang, Evan Montoya, David Munechika, Haoyang Yang, Benjamin Hoover, and Duen Horng Chau · 2022
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Interpretable-through-prototypes deepfake detection for diffusion models
Agil Aghasanli, Dmitry Kangin, and Plamen Angelov · 2023
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Styledomain: Efficient and lightweight parameterizations of stylegan for one-shot and few-shot domain adaptation
Aibek Alanov, Vadim Titov, Maksim Nakhodnov, and Dmitry Vetrov · 2023
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Cifake: Image classification and explainable identification of ai-generated synthetic images
Jordan J Bird and Ahmad Lotfi · 2023
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Muse: Text-to-image generation via masked generative transformers
Huiwen Chang, Han Zhang, Jarred Barber, AJ Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Murphy, William T Freeman, Michael Rubinstein, et al · 2023
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On the detection of synthetic images generated by diffusion models
Riccardo Corvi, Davide Cozzolino, Giada Zingarini, Giovanni Poggi, Koki Nagano, and Luisa Verdoliva · 2023
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Hierarchical fine-grained image forgery detection and localization
Xiao Guo, Xiaohong Liu, Zhiyuan Ren, Steven Grosz, Iacopo Masi, and Xiaoming Liu · 2023
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Scaling up gans for text-to-image synthesis
Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, and Taesung Park · 2023
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Mage: Masked generative encoder to unify representation learning and image synthesis
Tianhong Li, Huiwen Chang, Shlok Mishra, Han Zhang, Dina Katabi, and Dilip Krishnan · 2023
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Detecting images generated by deep diffusion models using their local intrinsic dimensionality
Peter Lorenz, Ricard L Durall, and Janis Keuper · 2023
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Dall·e 3 system card, 2023
OpenAI · 2023
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Styleres: Transforming the residuals for real image editing with stylegan
Hamza Pehlivan, Yusuf Dalva, and Aysegul Dundar · 2023
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Md Awsafur Rahman, Bishmoy Paul, Najibul Haque Sarker, Zaber Ibn Abdul Hakim, and Shaikh Anowarul Fattah · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2023
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Galip: Generative adversarial clips for text-to-image synthesis
Ming Tao, Bing-Kun Bao, Hao Tang, and Changsheng Xu · 2023
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p + p+ : Extended textual conditioning in text-to-image generation
Andrey Voynov, Qinghao Chu, Daniel Cohen-Or, and Kfir Aberman · 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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Generalizable synthetic image detection via language-guided contrastive learning
Haiwei Wu, Jiantao Zhou, and Shile Zhang · 2023
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Navigating text-to-image customization: From lycoris fine-tuning to model evaluation
Shin-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao, Bernard BW Yang, Giyeong Oh, and Yanmin Gong · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Genimage: A million-scale benchmark for detecting ai-generated image
Mingjian Zhu, Hanting Chen, Qiangyu Yan, Xudong Huang, Guanyu Lin, Wei Li, Zhijun Tu, Hailin Hu, Jie Hu, and Yunhe Wang · 2023
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