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Classification has been the focal point of research on adversarial attacks, but only a few works investigate methods suited to denser prediction tasks, such as semantic segmentation.
Splitting algorithms for the sum of two nonlinear operators
Pierre-Louis Lions and Bertrand Mercier · 1979
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Signal recovery by proximal forward-backward splitting
Patrick L Combettes and Valérie R Wajs · 2005
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Dualization of signal recovery problems
Patrick L Combettes, Đinh Dũng, and B · 2010
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Convex analysis and monotone operator theory in Hilbert spaces
Heinz H Bauschke, Patrick L Combettes, et al · 2011
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Proximal splitting methods in signal processing
Patrick L Combettes and Jean-Christophe Pesquet · 2011
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Optimization with sparsity-inducing penalties
Francis Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, et al · 2012
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A quasi-newton proximal splitting method
Stephen Becker and Jalal Fadili · 2012
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The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2012
Earlier work this paper cites.
Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized gauss–seidel methods
Hedy Attouch, Jérôme Bolte, and Benar Fux Svaiter · 2013
Earlier work this paper cites.
Practical augmented Lagrangian methods for constrained optimization
Ernesto G Birgin and José Mario Martínez · 2014
Earlier work this paper cites.
Variable metric forward–backward algorithm for minimizing the sum of a differentiable function and a convex function
Emilie Chouzenoux, Jean-Christophe Pesquet, and Audrey Repetti · 2014
Earlier work this paper cites.
Variable metric forward–backward splitting with applications to monotone inclusions in duality
Patrick L Combettes and Băng C Vũ · 2014
Earlier work this paper cites.
On the convergence of the iterates of the “fast iterative shrinkage/thresholding algorithm”
Antonin Chambolle and Charles H Dossal · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Deepfool: A simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard · 2016
Cited alongside, same era.
Towards evaluating the robustness of neural networks
Nicholas Carlini and David Wagner · 2017
Cited alongside, same era.
Houdini: Fooling deep structured visual and speech recognition models with adversarial examples
Moustapha M Cisse, Yossi Adi, Natalia Neverova, and Joseph Keshet · 2017
Cited alongside, same era.
Adversarial examples for semantic image segmentation
Volker Fischer, Mummadi Chaithanya Kumar, Jan Hendrik Metzen, and Thomas Brox · 2017
Cited alongside, same era.
Adversarial machine learning at scale
Alexey Kurakin, Ian J. Goodfellow, and Samy Bengio · 2017
Cited alongside, same era.
Adversarial examples for semantic segmentation and object detection
Cihang Xie, Jianyu Wang, Zhishuai Zhang, Yuyin Zhou, Lingxi Xie, and Alan Yuille · 2017
Decoupling direction and norm for efficient gradient-based l2 adversarial attacks and defenses
Jérôme Rony, Luiz G Hafemann, Luiz S Oliveira, Ismail Ben Ayed, Robert Sabourin, and Eric Granger · 2019
Later among the works it cites.
Trust region based adversarial attack on neural networks
Zhewei Yao, Amir Gholami, Peng Xu, Kurt Keutzer, and Michael W Mahoney · 2019
Later among the works it cites.
What if adversarial samples were digital images?
Benoît Bonnet, Teddy Furon, and Patrick Bas · 2020
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MMSegmentation: Openmmlab semantic segmentation toolbox and benchmark
MMSegmentation Contributors · 2020
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Minimally distorted adversarial examples with a fast adaptive boundary attack
Francesco Croce and Matthias Hein · 2020
Later among the works it cites.
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
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Cited alongside, same era.
On the robustness of semantic segmentation models to adversarial attacks
Anurag Arnab, Ondrej Miksik, and Philip HS Torr · 2018
Cited alongside, same era.
Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
Cited alongside, same era.
Boosting adversarial attacks with momentum
Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Hang Su, Jun Zhu, Xiaolin Hu, and Jianguo Li · 2018
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
Cited alongside, same era.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
Cited alongside, same era.
Accurate, reliable and fast robustness evaluation
Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, and Matthias Bethge · 2019
Cited alongside, same era.
Francesco Croce and Matthias Hein · 2020
Later among the works it cites.
Adversarial attacks for image segmentation on multiple lightweight models
Xu Kang, Bin Song, Xiaojiang Du, and Mohsen Guizani · 2020
Later among the works it cites.
Deep high-resolution representation learning for visual recognition
Jingdong Wang, Ke Sun, Tianheng Cheng, Borui Jiang, Chaorui Deng, Yang Zhao, Dong Liu, Yadong Mu, Mingkui Tan, Xinggang Wang, et al · 2020
Later among the works it cites.
Pdpgd: Primal-dual proximal gradient descent adversarial attack
Alexander Matyasko and Lap-Pui Chau · 2021
Later among the works it cites.
Fast minimum-norm adversarial attacks through adaptive norm constraints
Maura Pintor, Fabio Roli, Wieland Brendel, and Battista Biggio · 2021
Later among the works it cites.
Augmented lagrangian adversarial attacks
Jérôme Rony, Eric Granger, Marco Pedersoli, and Ismail Ben Ayed · 2021
Later among the works it cites.
Segformer: Simple and efficient design for semantic segmentation with transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M Alvarez, and Ping Luo · 2021
Later among the works it cites.
Dynamic divide-and-conquer adversarial training for robust semantic segmentation
Xiaogang Xu, Hengshuang Zhao, and Jiaya Jia · 2021
Later among the works it cites.
Unmatched preconditioning of the proximal gradient algorithm
Marion Savanier, Emilie Chouzenoux, Jean-Christophe Pesquet, and Cyril Riddell · 2022
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