ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1801.02610
  4. Cited By
Generating Adversarial Examples with Adversarial Networks

Generating Adversarial Examples with Adversarial Networks

8 January 2018
Chaowei Xiao
Bo Li
Jun-Yan Zhu
Warren He
M. Liu
D. Song
    GAN
    AAML
ArXivPDFHTML

Papers citing "Generating Adversarial Examples with Adversarial Networks"

30 / 380 papers shown
Title
AutoGAN: Robust Classifier Against Adversarial Attacks
AutoGAN: Robust Classifier Against Adversarial Attacks
Blerta Lindqvist
Shridatt Sugrim
R. Izmailov
AAML
29
7
0
08 Dec 2018
Universal Perturbation Attack Against Image Retrieval
Universal Perturbation Attack Against Image Retrieval
Jie Li
Rongrong Ji
Hong Liu
Xiaopeng Hong
Yue Gao
Q. Tian
AAML
29
98
0
03 Dec 2018
Transferable Adversarial Attacks for Image and Video Object Detection
Transferable Adversarial Attacks for Image and Video Object Detection
Xingxing Wei
Siyuan Liang
Ning Chen
Xiaochun Cao
AAML
77
222
0
30 Nov 2018
Attacks on State-of-the-Art Face Recognition using Attentional
  Adversarial Attack Generative Network
Attacks on State-of-the-Art Face Recognition using Attentional Adversarial Attack Generative Network
Q. Song
Yingqi Wu
Lu Yang
AAML
CVBM
GAN
24
96
0
29 Nov 2018
Universal Adversarial Training
Universal Adversarial Training
A. Mendrik
Mahyar Najibi
Zheng Xu
John P. Dickerson
L. Davis
Tom Goldstein
AAML
OOD
24
189
0
27 Nov 2018
Learning Robust Representations for Automatic Target Recognition
Learning Robust Representations for Automatic Target Recognition
Justin A. Goodwin
Olivia M. Brown
Taylor W. Killian
Sung-Hyun Son
9
1
0
26 Nov 2018
Stackelberg GAN: Towards Provable Minimax Equilibrium via
  Multi-Generator Architectures
Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures
Hongyang R. Zhang
Susu Xu
Jiantao Jiao
P. Xie
Ruslan Salakhutdinov
Eric Xing
18
22
0
19 Nov 2018
An Orchestrated Empirical Study on Deep Learning Frameworks and
  Platforms
An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms
Qianyu Guo
Xiaofei Xie
Lei Ma
Q. Hu
Ruitao Feng
Li Li
Yang Liu
Jianjun Zhao
Xiaohong Li
22
5
0
13 Nov 2018
Adversarial Gain
Adversarial Gain
Peter Henderson
Koustuv Sinha
Nan Rosemary Ke
Joelle Pineau
AAML
30
0
0
04 Nov 2018
Learning to Defend by Learning to Attack
Learning to Defend by Learning to Attack
Haoming Jiang
Zhehui Chen
Yuyang Shi
Bo Dai
T. Zhao
21
22
0
03 Nov 2018
Data Poisoning Attack against Unsupervised Node Embedding Methods
Data Poisoning Attack against Unsupervised Node Embedding Methods
Mingjie Sun
Jian Tang
Huichen Li
Bo Li
Chaowei Xiao
Yao-Liang Chen
D. Song
GNN
AAML
14
67
0
30 Oct 2018
MeshAdv: Adversarial Meshes for Visual Recognition
MeshAdv: Adversarial Meshes for Visual Recognition
Chaowei Xiao
Dawei Yang
Bo Li
Jia Deng
M. Liu
AAML
32
25
0
11 Oct 2018
Characterizing Adversarial Examples Based on Spatial Consistency
  Information for Semantic Segmentation
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
Chaowei Xiao
Ruizhi Deng
Bo Li
Feng Yu
M. Liu
D. Song
AAML
19
99
0
11 Oct 2018
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep
  Convolutional Networks
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks
Kenneth T. Co
Luis Muñoz-González
Sixte de Maupeou
Emil C. Lupu
AAML
22
67
0
30 Sep 2018
Generating 3D Adversarial Point Clouds
Generating 3D Adversarial Point Clouds
Chong Xiang
C. Qi
Bo Li
3DPC
24
286
0
19 Sep 2018
Structure-Preserving Transformation: Generating Diverse and Transferable
  Adversarial Examples
Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples
Dan Peng
Zizhan Zheng
Xiaofeng Zhang
AAML
22
5
0
08 Sep 2018
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided
  Fuzzing
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing
Xiaofei Xie
Lei Ma
Felix Juefei Xu
Hongxu Chen
Minhui Xue
Bo Li
Yang Liu
Jianjun Zhao
Jianxiong Yin
Simon See
43
40
0
04 Sep 2018
Adversarial Attack Type I: Cheat Classifiers by Significant Changes
Adversarial Attack Type I: Cheat Classifiers by Significant Changes
Sanli Tang
Xiaolin Huang
Mingjian Chen
Chengjin Sun
J. Yang
AAML
38
2
0
03 Sep 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the
  Robustness of 18 Deep Image Classification Models
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
D. Su
Huan Zhang
Hongge Chen
Jinfeng Yi
Pin-Yu Chen
Yupeng Gao
VLM
40
389
0
05 Aug 2018
Traits & Transferability of Adversarial Examples against Instance
  Segmentation & Object Detection
Traits & Transferability of Adversarial Examples against Instance Segmentation & Object Detection
Raghav Gurbaxani
Shivank Mishra
AAML
11
4
0
04 Aug 2018
Customizing an Adversarial Example Generator with Class-Conditional GANs
Customizing an Adversarial Example Generator with Class-Conditional GANs
Shih-hong Tsai
GAN
AAML
28
4
0
27 Jun 2018
Adversarial Attacks on Face Detectors using Neural Net based Constrained
  Optimization
Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization
A. Bose
P. Aarabi
AAML
19
89
0
31 May 2018
Constructing Unrestricted Adversarial Examples with Generative Models
Constructing Unrestricted Adversarial Examples with Generative Models
Yang Song
Rui Shu
Nate Kushman
Stefano Ermon
GAN
AAML
185
302
0
21 May 2018
Fortified Networks: Improving the Robustness of Deep Networks by
  Modeling the Manifold of Hidden Representations
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations
Alex Lamb
Jonathan Binas
Anirudh Goyal
Dmitriy Serdyuk
Sandeep Subramanian
Ioannis Mitliagkas
Yoshua Bengio
OOD
34
43
0
07 Apr 2018
Certified Robustness to Adversarial Examples with Differential Privacy
Certified Robustness to Adversarial Examples with Differential Privacy
Mathias Lécuyer
Vaggelis Atlidakis
Roxana Geambasu
Daniel J. Hsu
Suman Jana
SILM
AAML
56
926
0
09 Feb 2018
Pros and Cons of GAN Evaluation Measures
Pros and Cons of GAN Evaluation Measures
Ali Borji
ELM
EGVM
37
866
0
09 Feb 2018
A General Framework for Adversarial Examples with Objectives
A General Framework for Adversarial Examples with Objectives
Mahmood Sharif
Sruti Bhagavatula
Lujo Bauer
Michael K. Reiter
AAML
GAN
13
191
0
31 Dec 2017
Towards Robust Neural Networks via Random Self-ensemble
Towards Robust Neural Networks via Random Self-ensemble
Xuanqing Liu
Minhao Cheng
Huan Zhang
Cho-Jui Hsieh
FedML
AAML
58
419
0
02 Dec 2017
Ensemble Adversarial Training: Attacks and Defenses
Ensemble Adversarial Training: Attacks and Defenses
Florian Tramèr
Alexey Kurakin
Nicolas Papernot
Ian Goodfellow
Dan Boneh
Patrick McDaniel
AAML
79
2,701
0
19 May 2017
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
365
5,849
0
08 Jul 2016
Previous
12345678