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Neural networks are known to be susceptible to adversarial samples: small variations of natural examples crafted to deliberately mislead the models.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2014
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Image style transfer using convolutional neural networks
L. A. Gatys, A. S. Ecker, and M. Bethge · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Wide residual networks
S. Zagoruyko and N. Komodakis · 2016
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T. B. Brown, D. Mané, A. Roy, M. Abadi, and J. Gilmer · 2017
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Towards evaluating the robustness of neural networks
N. Carlini and D. Wagner · 2017
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A rotation and a translation suffice: Fooling cnns with simple transformations
L. Engstrom, B. Tran, D. Tsipras, L. Schmidt, and A. Madry · 2017
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Can you fool ai with adversarial examples on a visual turing test
X. Xu, X. Chen, C. Liu, A. Rohrbach, T. Darell, and D. Song · 2017
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Synthesizing robust adversarial examples
A. Athalye, L. Engstrom, A. Ilyas, and K. Kwok · 2018
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Robust physical-world attacks on deep learning visual classification
K. Eykholt, I. Evtimov, E. Fernandes, B. Li, A. Rahmati, C. Xiao, A. Prakash, T. Kohno, and D. Song · 2018
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Semantic adversarial examples
H. Hosseini and R. Poovendran · 2018
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Adversarial examples in the physical world
A. Kurakin, I. J. Goodfellow, and S. Bengio · 2018
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Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2018
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Generating natural adversarial examples
Z. Zhao, D. Dua, and S. Singh · 2018
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Beyond pixel norm-balls: Parametric adversaries using an analytically differentiable renderer
H.-T. D. Liu, M. Tao, C.-L. Li, D. Nowrouzezahrai, and A. Jacobson · 2019
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Adversarial attacks beyond the image space
X. Zeng, C. Liu, Y.-S. Wang, W. Qiu, L. Xie, Y.-W. Tai, C.-K. Tang, and A. L. Yuille · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, et al · 2020
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Adversarial camouflage: Hiding physical-world attacks with natural styles
R. Duan, X. Ma, Y. Wang, J. Bailey, A. K. Qin, and Y. Yang · 2020
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Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
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Do adversarially robust imagenet models transfer better?
H. Salman, A. Ilyas, L. Engstrom, A. Kapoor, and A. Madry · 2020
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Score-based generative modeling through stochastic differential equations
Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, and B. Poole · 2020
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Adversarial t-shirt! evading person detectors in a physical world
K. Xu, G. Zhang, S. Liu, Q. Fan, M. Sun, H. Chen, P.-Y. Chen, Y. Wang, and X. Lin · 2020
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Diffusion models beat gans on image synthesis
Synthesizing coherent story with auto-regressive latent diffusion models
X. Pan, P. Qin, Y. Li, H. Xue, and W. Chen · 2022
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High-resolution image synthesis with latent diffusion models
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
C. Saharia, W. Chan, S. Saxena, L. Li, J. Whang, E. L. Denton, K. Ghasemipour, R. Gontijo Lopes, B. Karagol Ayan, T. Salimans, et al · 2022
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Guided diffusion model for adversarial purification
J. Wang, Z. Lyu, D. Lin, B. Dai, and H. Fu · 2022
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Guided diffusion model for adversarial purification from random noise
Q. Wu, H. Ye, and Y. Gu · 2022
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P. Dhariwal and A. Nichol · 2021
Cited alongside, same era.
Naturalistic physical adversarial patch for object detectors
Y.-C.-T. Hu, B.-H. Kung, D. S. Tan, J.-C. Chen, K.-L. Hua, and W.-H. Cheng · 2021
Cited alongside, same era.
Sdedit: Guided image synthesis and editing with stochastic differential equations
C. Meng, Y. He, Y. Song, J. Song, J. Wu, J.-Y. Zhu, and S. Ermon · 2021
Cited alongside, same era.
Denoising diffusion implicit models
J. Song, C. Meng, and S. Ermon · 2021
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Adversarial purification with score-based generative models
J. Yoon, S. J. Hwang, and J. Lee · 2021
Cited alongside, same era.
ediffi: Text-to-image diffusion models with an ensemble of expert denoisers
Y. Balaji, S. Nah, X. Huang, A. Vahdat, J. Song, K. Kreis, M. Aittala, T. Aila, S. Laine, B. Catanzaro, et al · 2022
Cited alongside, same era.
BEit: BERT pre-training of image transformers
H. Bao, L. Dong, S. Piao, and F. Wei · 2022
Cited alongside, same era.
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Ada3diff: Defending against 3d adversarial point clouds via adaptive diffusion
K. Zhang, H. Zhou, J. Zhang, Q. Huang, W. Zhang, and N. Yu · 2022
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Fast sampling of diffusion models with exponential integrator
Q. Zhang and Y. Chen · 2022
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(certified!!) adversarial robustness for free!
N. Carlini, F. Tramer, K. D. Dvijotham, L. Rice, M. Sun, and J. Z. Kolter · 2023
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Content-based unrestricted adversarial attack
Z. Chen, B. Li, S. Wu, K. Jiang, S. Ding, and W. Zhang · 2023
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Advart: Adversarial art for camouflaged object detection attacks
A. Guesmi, I. M. Bilasco, M. Shafique, and I. Alouani · 2023
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Patch of invisibility: Naturalistic black-box adversarial attacks on object detectors
R. Lapid and M. Sipper · 2023
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Robust evaluation of diffusion-based adversarial purification
M. Lee and D. Kim · 2023
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Dreamfusion: Text-to-3d using 2d diffusion
B. Poole, A. Jain, J. T. Barron, and B. Mildenhall · 2023
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High-resolution image reconstruction with latent diffusion models from human brain activity
Y. Takagi and S. Nishimoto · 2023
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Y. Wang, Z. Wu, C. Li, and A. Wu · 2023
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Densepure: Understanding diffusion models for adversarial robustness
C. Xiao, Z. Chen, K. Jin, J. Wang, W. Nie, M. Liu, A. Anandkumar, B. Li, and D. Song · 2023
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Toward effective protection against diffusion based mimicry through score distillation
H. Xue, C. Liang, X. Wu, and Y. Chen · 2023
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