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In light of recent advancements in generative AI models, it has become essential to distinguish genuine content from AI-generated one to prevent the malicious usage of fake materials as authentic ones and vice versa.
Fakecatcher: Detection of synthetic portrait videos using biological signals
Umur Aybars Ciftci and Ilke Demir · 1901
Earlier work this paper cites.
Steganogan: High capacity image steganography with gans
Kevin Alex Zhang, Alfredo Cuesta-Infante, Lei Xu, and Kalyan Veeramachaneni · 1901
Earlier work this paper cites.
Robust invisible video watermarking with attention
Kevin Alex Zhang, Lei Xu, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni · 1909
Earlier work this paper cites.
Robust invisible video watermarking with attention
Kevin Alex Zhang, Lei Xu, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni · 1909
Earlier work this paper cites.
Watermarking digital images for copyright protection
FRANCIS MORGAN Boland, Joseph JK O’Ruanaidh, and C Dautzenberg · 1995
Earlier work this paper cites.
Secure spread spectrum watermarking for images, audio and video
Ingemar J Cox, Joe Kilian, Tom Leighton, and Talal Shamoon · 1996
Earlier work this paper cites.
A watermark for digital images
Raymond B Wolfgang and Edward J Delp · 1996
Earlier work this paper cites.
Rotation, scale and translation invariant digital image watermarking
Joseph JK O’Ruanaidh and Thierry Pun · 1997
Earlier work this paper cites.
Multimedia data-embedding and watermarking technologies
M.D. Swanson, M. Kobayashi, and A.H. Tewfik · 1998
Earlier work this paper cites.
Digital watermarking
Chris Honsinger · 2002
Earlier work this paper cites.
A robust image fingerprinting system using the radon transform
Jin S Seo, Jaap Haitsma, Ton Kalker, and Chang D Yoo · 2004
Earlier work this paper cites.
Svd-based digital image watermarking scheme
Chin-Chen Chang, Piyu Tsai, and Chia-Chen Lin · 2005
Earlier work this paper cites.
A survey of digital image watermarking techniques
V.M. Potdar, S. Han, and E. Chang · 2005
Earlier work this paper cites.
Digital Watermarking and Steganography
Ingemar Cox, Matthew Miller, Jeffrey Bloom, Jessica Fridrich, and Ton Kalker · 2007
Earlier work this paper cites.
Using high-dimensional image models to perform highly undetectable steganography
Tomáš Pevnỳ, Tomáš Filler, and Patrick Bas · 2010
Earlier work this paper cites.
Lsb++: An improvement to lsb+ steganography
Kazem Ghazanfari, Shahrokh Ghaemmaghami, and Saeed R Khosravi · 2011
Earlier work this paper cites.
Designing steganographic distortion using directional filters
Vojtěch Holub and Jessica Fridrich · 2012
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Deep residual learning for image recognition. corr abs/1512.03385 (2015), 2015
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Cited alongside, same era.
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
Cited alongside, same era.
A deep learning approach to universal image manipulation detection using a new convolutional layer
Belhassen Bayar and Matthew C Stamm · 2016
Cited alongside, same era.
” xception: Deep learning with depthwise separable convolutions”, arxiv preprint
François Chollet · 2016
Cited alongside, same era.
Recasting residual-based local descriptors as convolutional neural networks: an application to image forgery detection
Davide Cozzolino, Giovanni Poggi, and Luisa Verdoliva · 2017
Dynamic texture analysis for detecting fake faces in video sequences
Mattia Bonomi, Cecilia Pasquini, and Giulia Boato · 2021
Later among the works it cites.
Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
Later among the works it cites.
Lips don’t lie: A generalisable and robust approach to face forgery detection
Alexandros Haliassos, Konstantinos Vougioukas, Stavros Petridis, and Maja Pantic · 2021
Later among the works it cites.
Mbrs: Enhancing robustness of dnn-based watermarking by mini-batch of real and simulated jpeg compression
Zhaoyang Jia, Han Fang, and Weiming Zhang · 2021
Later among the works it cites.
Laion-400m: Open dataset of clip-filtered 400 million image-text pairs, 2021
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
Later among the works it cites.
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
Cited alongside, same era.
Distinguishing computer graphics from natural images using convolution neural networks
Nicolas Rahmouni, Vincent Nozick, Junichi Yamagishi, and Isao Echizen · 2017
Cited alongside, same era.
Transferable deep-cnn features for detecting digital and print-scanned morphed face images
Kiran Raja, Sushma Venkatesh, RB Christoph Busch, et al · 2017
Cited alongside, same era.
Two-stream neural networks for tampered face detection
Peng Zhou, Xintong Han, Vlad I Morariu, and Larry S Davis · 2017
Cited alongside, same era.
Towards deepfake detection that actually works
Dessa · 2019
Cited alongside, same era.
Defamatory political deepfakes and the first amendment
Jessica L. Ice · 2019
Cited alongside, same era.
Exploiting visual artifacts to expose deepfakes and face manipulations
Falko Matern, Christian Riess, and Marc Stamminger · 2019
Cited alongside, same era.
Artificial intelligence crime: An overview of malicious use and abuse of ai
Taís Fernanda Blauth, Oskar Josef Gstrein, and Andrej Zwitter · 2022
Later among the works it cites.
Deepfakes and the new disinformation war: The coming age of post-truth geopolitics
Robert Chesney and Danielle Citron · 2022
Later among the works it cites.
Artificial Intelligence, Deepfakes, and Disinformation: A Primer
Todd C. Helmus · 2022
Later among the works it cites.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation, 2022
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
Later among the works it cites.
Understanding diffusion models: A unified perspective
Calvin Luo · 2022
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Diffusion models for adversarial purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, and Anima Anandkumar · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
Rd-iwan: Residual dense based imperceptible watermark attack network
Chunpeng Wang, Qixian Hao, Shujiang Xu, Bin Ma, Zhiqiu Xia, Qi Li, Jian Li, and Yun-Qing Shi · 2022
Later among the works it cites.
Diffusionshield: A watermark for copyright protection against generative diffusion models
Yingqian Cui, Jie Ren, Han Xu, Pengfei He, Hui Liu, Lichao Sun, and Jiliang Tang · 2023
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Improving synthetically generated image detection in cross-concept settings
Pantelis Dogoulis, Giorgos Kordopatis-Zilos, Ioannis Kompatsiaris, and Symeon Papadopoulos · 2023
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Image denoising: The deep learning revolution and beyond—a survey paper
Michael Elad, Bahjat Kawar, and Gregory Vaksman · 2023
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Evading watermark based detection of ai-generated content
Zhengyuan Jiang, Jinghuai Zhang, and Neil Zhenqiang Gong · 2023
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Tree-ring watermarks: Fingerprints for diffusion images that are invisible and robust
Yuxin Wen, John Kirchenbauer, Jonas Geiping, and Tom Goldstein · 2023
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