Fetching the paper…
Reading the bibliography…
Invisible watermarks safeguard images' copyrights by embedding hidden messages only detectable by owners.
Nonlinear total variation based noise removal algorithms
Leonid I Rudin, Stanley Osher, and Emad Fatemi · 1992
Earlier work this paper cites.
A watermark for digital images
Raymond B Wolfgang and Edward J Delp · 1996
Earlier work this paper cites.
Bilateral filtering for gray and color images
Carlo Tomasi and Roberto Manduchi · 1998
Earlier work this paper cites.
Informed embedding: exploiting image and detector information during watermark insertion
Matthew L Miller, Ingemar J Cox, and Jeffrey A Bloom · 2000
Earlier work this paper cites.
The first 50 years of electronic watermarking
Ingemar J Cox and Matt L Miller · 2002
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli · 2004
Earlier work this paper cites.
A non-local algorithm for image denoising
Antoni Buades, Bartomeu Coll, and J-M Morel · 2005
Earlier work this paper cites.
Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
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.
Image denoising by sparse 3-d transform-domain collaborative filtering
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
Earlier work this paper cites.
Broken arrows
Teddy Furon and Patrick Bas · 2008
Earlier work this paper cites.
Dwt-dct-svd based watermarking
KA Navas, Mathews Cheriyan Ajay, M Lekshmi, Tampy S Archana, and M Sasikumar · 2008
Earlier work this paper cites.
Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
Earlier work this paper cites.
Ssim image quality metric for denoised images
Peter Ndajah, Hisakazu Kikuchi, Masahiro Yukawa, Hidenori Watanabe, and Shogo Muramatsu · 2010
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.
Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol, and Léon Bottou · 2010
Earlier work this paper cites.
A statistical framework for differential privacy
Larry Wasserman and Shuheng Zhou · 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.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
Earlier work this paper cites.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
Earlier work this paper cites.
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
Earlier work this paper cites.
The composition theorem for differential privacy
Peter Kairouz, Sewoong Oh, and Pramod Viswanath · 2015
Cited alongside, same era.
Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
Cited alongside, same era.
Optimal rates for total variation denoising
Jan-Christian Hütter and Philippe Rigollet · 2016
Cited alongside, same era.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Cited alongside, same era.
Rényi differential privacy
Ilya Mironov · 2017
Cited alongside, same era.
Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
Cited alongside, same era.
Wdnet: Watermark-decomposition network for visible watermark removal
Yang Liu, Zhen Zhu, and Xiang Bai · 2021
Later among the works it cites.
Artificial fingerprinting for generative models: Rooting deepfake attribution in training data
Ning Yu, Vladislav Skripniuk, Sahar Abdelnabi, and Mario Fritz · 2021
Later among the works it cites.
Plug-and-play image restoration with deep denoiser prior
Kai Zhang, Yawei Li, Wangmeng Zuo, Lei Zhang, Luc Van Gool, and Radu Timofte · 2021
Later among the works it cites.
Gaussian differential privacy
Jinshuo Dong, Aaron Roth, and Weijie J Su · 2022
Later among the works it cites.
Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
Later among the works it cites.
Diffusion models for adversarial purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, and Animashree Anandkumar · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2017
Cited alongside, same era.
Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising
Borja Balle and Yu-Xiang Wang · 2018
Cited alongside, same era.
Variational image compression with a scale hyperprior
Johannes Ballé, David Minnen, Saurabh Singh, Sung Jin Hwang, and Nick Johnston · 2018
Cited alongside, same era.
Blind visual motif removal from a single image
Amir Hertz, Sharon Fogel, Rana Hanocka, Raja Giryes, and Daniel Cohen-Or · 2019
Cited alongside, same era.
Attacking image watermarking and steganography-a survey
Osama Hosam · 2019
Cited alongside, same era.
Steganogan: High capacity image steganography with gans
Kevin Alex Zhang, Alfredo Cuesta-Infante, Lei Xu, and Kalyan Veeramachaneni · 2019
Cited alongside, same era.
Later among the works it cites.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 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.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
Later among the works it cites.
Openai, google, others pledge to watermark ai content for safety, white house says, Jul 2023
Diane Bartz and Krystal Hu · 2023
Closest in time.
The stable signature: Rooting watermarks in latent diffusion models
Pierre Fernandez, Guillaume Couairon, Hervé Jégou, Matthijs Douze, and Teddy Furon · 2023
Closest in time.
Google keynote (google i/o 23)
Google · 2023
Closest in time.
President biden issues executive order on safe, secure, and trustworthy artificial intelligence, 2023
The White House · 2023
Closest in time.
Chuck schumer calls on congress to pick up the pace on ai regulation, Jun 2023
Makena Kelly · 2023
Closest in time.
White house rolls out plan to promote ethical ai, May 2023
Makena Kelly · 2023
Closest in time.
Diffwa: Diffusion models for watermark attack
Xinyu Li · 2023
Closest in time.
Leveraging optimization for adaptive attacks on image watermarks
Nils Lukas, Abdulrahman Diaa, Lucas Fenaux, and Florian Kerschbaum · 2023
Closest in time.
Ptw: Pivotal tuning watermarking for pre-trained image generators
Nils Lukas and Florian Kerschbaum · 2023
Closest in time.
Robustness of ai-image detectors: Fundamental limits and practical attacks
Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei, Aounon Kumar, Atoosa Malemir Chegini, Wenxiao Wang, and Soheil Feizi · 2023
Closest in time.
Tree-ring watermarks: Fingerprints for diffusion images that are invisible and robust
Yuxin Wen, John Kirchenbauer, Jonas Geiping, and Tom Goldstein · 2023
Closest in time.
Microsoft pledges to watermark ai-generated images and videos
Kyle Wiggers · 2023
Closest in time.
Benchmarking the robustness of image watermarks
Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, et al · 2024
Closest in time.