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Diffusion models (DMs) have demonstrated advantageous potential on generative tasks.
Blackmarks: Blackbox multibit watermarking for deep neural networks
Huili Chen, Bita Darvish Rouhani, and Farinaz Koushanfar · 1904
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Persistent and unforgeable watermarks for deep neural networks
Huiying Li, Emily Willson, Haitao Zheng, and Ben Y Zhao · 1910
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Digital watermarking: algorithms and applications
Christine I Podilchuk and Edward J Delp · 2001
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Digital watermarking
Ingemar Cox, Matthew Miller, Jeffrey Bloom, and Chris Honsinger · 2002
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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, 2009
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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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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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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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
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Embedding watermarks into deep neural networks
Yusuke Uchida, Yuki Nagai, Shigeyuki Sakazawa, and Shin’ichi Satoh · 2017
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Turning your weakness into a strength: Watermarking deep neural networks by backdooring
Yossi Adi, Carsten Baum, Moustapha Cisse, Benny Pinkas, and Joseph Keshet · 2018
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Watermarking deep neural networks for embedded systems
Jia Guo and Miodrag Potkonjak · 2018
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Protecting intellectual property of deep neural networks with watermarking
Jialong Zhang, Zhongshu Gu, Jiyong Jang, Hui Wu, Marc Ph Stoecklin, Heqing Huang, and Ian Molloy · 2018
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Deepsigns: An end-to-end watermarking framework for ownership protection of deep neural networks
Bita Darvish Rouhani, Huili Chen, and Farinaz Koushanfar · 2019
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Rethinking deep neural network ownership verification: Embedding passports to defeat ambiguity attacks
Lixin Fan, Kam Woh Ng, and Chee Seng Chan · 2019
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Evolutionary trigger set generation for dnn black-box watermarking
Jia Guo and Miodrag Potkonjak · 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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Quantifying the carbon emissions of machine learning
Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, and Thomas Dandres · 2019
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Deep neural network fingerprinting by conferrable adversarial examples
Nils Lukas, Yuxuan Zhang, and Florian Kerschbaum · 2019
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Robust watermarking of neural network with exponential weighting
Ryota Namba and Jun Sakuma · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Robust and undetectable white-box watermarks for deep neural networks
Tianhao Wang and Florian Kerschbaum · 2019
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A novel method for identifying the deep neural network model with the serial number
Xiangrui Xu, Yaqin Li, and Cao Yuan · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Cited alongside, same era.
Stargan v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
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Waffle: Watermarking in federated learning
Buse GA Tekgul, Yuxi Xia, Samuel Marchal, and N Asokan · 2021
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One-shot generative domain adaptation
Ceyuan Yang, Yujun Shen, Zhiyi Zhang, Yinghao Xu, Jiapeng Zhu, Zhirong Wu, and Bolei Zhou · 2021
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Artificial fingerprinting for generative models: Rooting deepfake attribution in training data
Ning Yu, Vladislav Skripniuk, Sahar Abdelnabi, and Mario Fritz · 2021
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Watermarking graph neural networks by random graphs
Xiangyu Zhao, Hanzhou Wu, and Xinpeng Zhang · 2021
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Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models
Fan Bao, Chongxuan Li, Jun Zhu, and Bo Zhang · 2022
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Adam and the ants: On the influence of the optimization algorithm on the detectability of dnn watermarks
Betty Cortiñas-Lorenzo and Fernando Pérez-González · 2020
Cited alongside, same era.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Training generative adversarial networks with limited data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2020
Cited alongside, same era.
Adversarial frontier stitching for remote neural network watermarking
Erwan Le Merrer, Patrick Perez, and Gilles Trédan · 2020
Cited alongside, same era.
Countering language drift with seeded iterated learning
Yuchen Lu, Soumye Singhal, Florian Strub, Aaron Courville, and Olivier Pietquin · 2020
Cited alongside, same era.
Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
Cited alongside, same era.
Jianwei Fei, Zhihua Xia, Benedetta Tondi, and Mauro Barni · 2022
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An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Blindnet backdoor: Attack on deep neural network using blind watermark
Hyun Kwon and Yongchul Kim · 2022
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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
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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
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 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 W Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa R Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, and Jenia Jitsev · 2022
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Invisible watermarking for audio generation diffusion models
Xirong Cao, Xiang Li, Divyesh Jadav, Yanzhao Wu, Zhehui Chen, Chen Zeng, and Wenqi Wei · 2023
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Hey that’s mine imperceptible watermarks are preserved in diffusion generated outputs
Luke Ditria and Tom Drummond · 2023
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The stable signature: Rooting watermarks in latent diffusion models
Pierre Fernandez, Guillaume Couairon, Hervé Jégou, Matthijs Douze, and Teddy Furon · 2023
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A watermark for large language models
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein · 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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Text-to-image diffusion models can be easily backdoored through multimodal data poisoning
Shengfang Zhai, Yinpeng Dong, Qingni Shen, Shi Pu, Yuejian Fang, and Hang Su · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
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