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Photos serve as a way for humans to record what they experience in their daily lives, and they are often regarded as trustworthy sources of information.
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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Generative adversarial networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2014
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Splicebuster: A new blind image splicing detector
Davide Cozzolino, Giovanni Poggi, and Luisa Verdoliva · 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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Development of photo forensics algorithm by detecting photoshop manipulation using error level analysis
Teddy Surya Gunawan, Siti Amalina Mohammad Hanafiah, Mira Kartiwi, Nanang Ismail, Nor Farahidah Za’bah, and Anis Nurashikin Nordin · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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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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Detection of gan-generated fake images over social networks
Francesco Marra, Diego Gragnaniello, Davide Cozzolino, and Luisa Verdoliva · 2018
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Piyush Sharma, Nan Ding, Sebastian Goodman, and Radu Soricut · 2018
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Small is beautiful: In defense of the small-n design
Philip L Smith and Daniel R Little · 2018
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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Deep fakes: A looming challenge for privacy, democracy, and national security
Bobby Chesney and Danielle Citron · 2019
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Survey on deep learning with class imbalance
Justin M. Johnson and Taghi M. Khoshgoftaar · 2019
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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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Detecting GAN generated fake images using co-occurrence matrices
Lakshmanan Nataraj, Tajuddin Manhar Mohammed, B. S. Manjunath, Shivkumar Chandrasekaran, Arjuna Flenner, Jawadul H. Bappy, and Amit K. Roy-Chowdhury · 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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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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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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Stargan v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
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On the detection of digital face manipulation
Hao Dang, Feng Liu, Joel Stehouwer, Xiaoming Liu, and Anil K. Jain · 2020
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Leveraging frequency analysis for deep fake image recognition
Joel Frank, Thorsten Eisenhofer, Lea Schonherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz · 2020
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Adversarial perturbations fool deepfake detectors
Apurva Gandhi and Shomik Jain · 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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Maskgan: Towards diverse and interactive facial image manipulation
Cheng-Han Lee, Ziwei Liu, Lingyun Wu, and Ping Luo · 2020
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Global texture enhancement for fake face detection in the wild
Zhengzhe Liu, Xiaojuan Qi, and Philip H. S. Torr · 2020
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Thinking in frequency: Face forgery detection by mining frequency-aware clues
Yuyang Qian, Guojun Yin, Lu Sheng, Zixuan Chen, and Jing Shao · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
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Bringing old photos back to life
Ziyu Wan, Bo Zhang, Dongdong Chen, Pan Zhang, Dong Chen, Jing Liao, and Fang Wen · 2020
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Fakespotter: A simple yet robust baseline for spotting ai-synthesized fake faces
Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, and Yang Liu · 2020
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Cnn-generated images are surprisingly easy to spot… for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, and Alexei A. Efros · 2020
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Cogview: Mastering text-to-image generation via transformers
Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, and Jie Tang · 2021
A survey on bias and fairness in machine learning
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan · 2022
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The creation and detection of deepfakes: A survey
Yisroel Mirsky and Wenke Lee · 2022
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2022
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Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 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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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
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Cited alongside, same era.
Partial success in closing the gap between human and machine vision
Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Tizian Thieringer, Matthias Bethge, Felix A. Wichmann, and Wieland Brendel · 2021
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Forgerynet: A versatile benchmark for comprehensive forgery analysis
Yinan He, Bei Gan, Siyu Chen, Yichun Zhou, Guojun Yin, Luchuan Song, Lu Sheng, Jing Shao, and Ziwei Liu · 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
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
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
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, Gretchen Krueger, and Ilya Sutskever · 2021
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Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J. Fleet, and Mohammad Norouzi · 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, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, and Jenia Jitsev · 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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Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, and Yonghui Wu · 2022
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https://500px.com/
500px · 2023
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https://www.bbc.com/news/technology-62788725
bbc news: "art is dead dude" - the rise of the ai artists stirs debate · 2023
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https://www.bbc.com/news/world-us-canada-65069316
bbc news: Fake trump arrest photos: How to spot an ai-generated image · 2023
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https://www.bbc.com/news/entertainment-arts-65296763
bbc news: Sony world photography award 2023: Winner refuses award after revealing ai creation · 2023
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https://github.com/deep-floyd/IF
Deepfloyd. if · 2023
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https://images.google.com/
Google images · 2023
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https://www.midjourney.com/
Midjourney · 2023
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https://photutorial.com/
photutorial: Number of photos (2023): Statistics, facts, & predictions · 2023
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Rembrandt’s the night watch painting restored by ai · 2023
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Stable diffusion v1.5. realistic vision v2.0 · 2023
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Cifake: Image classification and explainable identification of ai-generated synthetic images
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Structure and content-guided video synthesis with diffusion models
Patrick Esser, Johnathan Chiu, Parmida Atighehchian, Jonathan Granskog, and Anastasis Germanidis · 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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Hierarchical diffusion autoencoders and disentangled image manipulation
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Towards universal fake image detectors that generalize across generative models
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Benchmarking deepart detection
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Adding conditional control to text-to-image diffusion models
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