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Fooling Vision and Language Models Despite Localization and Attention
  Mechanism
v1v2 (latest)

Fooling Vision and Language Models Despite Localization and Attention Mechanism

25 September 2017
Xiaojun Xu
Xinyun Chen
Chang-rui Liu
Anna Rohrbach
Trevor Darrell
Basel Alomair
    AAML
ArXiv (abs)PDFHTML

Papers citing "Fooling Vision and Language Models Despite Localization and Attention Mechanism"

22 / 22 papers shown
Title
Instruct2Attack: Language-Guided Semantic Adversarial Attacks
Instruct2Attack: Language-Guided Semantic Adversarial Attacks
Jiang-Long Liu
Chen Wei
Yuxiang Guo
Heng Yu
Yaoyao Liu
Soheil Feizi
Chun Pong Lau
Rama Chellappa
DiffMAAML
176
11
0
27 Nov 2023
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness
  and Controllability
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and ControllabilityNeural Information Processing Systems (NeurIPS), 2023
Haotian Xue
Alexandre Araujo
Bin Hu
Yongxin Chen
DiffM
407
79
0
25 May 2023
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps
Trace and Detect Adversarial Attacks on CNNs using Feature Response MapsIAPR International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), 2018
Mohammadreza Amirian
Friedhelm Schwenker
Thilo Stadelmann
AAML
119
17
0
24 Aug 2022
Multimodal Research in Vision and Language: A Review of Current and
  Emerging Trends
Multimodal Research in Vision and Language: A Review of Current and Emerging Trends
Shagun Uppal
Sarthak Bhagat
Devamanyu Hazarika
Navonil Majumdar
Soujanya Poria
Roger Zimmermann
Amir Zadeh
245
6
0
19 Oct 2020
Appending Adversarial Frames for Universal Video Attack
Appending Adversarial Frames for Universal Video AttackIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2019
Zhikai Chen
Lingxi Xie
Zehao Wu
Yong He
Qi Tian
AAML
150
38
0
10 Dec 2019
Adversarial Learning of Deepfakes in Accounting
Adversarial Learning of Deepfakes in Accounting
Marco Schreyer
Timur Sattarov
Bernd Reimer
Damian Borth
AAML
139
26
0
09 Oct 2019
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous
  Driving
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous DrivingConference on Computer and Communications Security (CCS), 2019
Yulong Cao
Chaowei Xiao
Benjamin Cyr
Yimeng Zhou
Wonseok Park
Sara Rampazzi
Qi Alfred Chen
Kevin Fu
Z. Morley Mao
AAML
167
594
0
16 Jul 2019
Improving the Robustness of Deep Neural Networks via Adversarial
  Training with Triplet Loss
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet LossInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
Pengcheng Li
Jinfeng Yi
Bowen Zhou
Lijun Zhang
AAML
160
37
0
28 May 2019
Body Shape Privacy in Images: Understanding Privacy and Preventing
  Automatic Shape Extraction
Body Shape Privacy in Images: Understanding Privacy and Preventing Automatic Shape Extraction
Hosnieh Sattar
Katharina Krombholz
Gerard Pons-Moll
Mario Fritz
3DH
185
3
0
27 May 2019
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks
Jinghui Chen
Dongruo Zhou
Jinfeng Yi
Quanquan Gu
AAML
239
75
0
27 Nov 2018
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural
  Network Robustness against Adversarial Attack
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial AttackComputer Vision and Pattern Recognition (CVPR), 2018
Adnan Siraj Rakin
Zhezhi He
Deliang Fan
AAML
143
306
0
22 Nov 2018
Attack Graph Convolutional Networks by Adding Fake Nodes
Attack Graph Convolutional Networks by Adding Fake Nodes
Xiaoyun Wang
Minhao Cheng
Joe Eaton
Cho-Jui Hsieh
S. F. Wu
AAMLGNN
283
83
0
25 Oct 2018
Understand, Compose and Respond - Answering Visual Questions by a
  Composition of Abstract Procedures
Understand, Compose and Respond - Answering Visual Questions by a Composition of Abstract Procedures
B. Vatashsky
S. Ullman
CoGe
122
2
0
25 Oct 2018
Query-Efficient Black-Box Attack by Active Learning
Query-Efficient Black-Box Attack by Active Learning
Pengcheng Li
Jinfeng Yi
Lijun Zhang
AAMLMLAU
125
58
0
13 Sep 2018
Defend Deep Neural Networks Against Adversarial Examples via Fixed and
  Dynamic Quantized Activation Functions
Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions
Adnan Siraj Rakin
Jinfeng Yi
Boqing Gong
Deliang Fan
AAMLMQ
151
51
0
18 Jul 2018
Modularity Matters: Learning Invariant Relational Reasoning Tasks
Modularity Matters: Learning Invariant Relational Reasoning Tasks
Jason Jo
Vikas Verma
Yoshua Bengio
OOD
123
8
0
18 Jun 2018
Adversarially Robust Generalization Requires More Data
Adversarially Robust Generalization Requires More Data
Ludwig Schmidt
Shibani Santurkar
Dimitris Tsipras
Kunal Talwar
Aleksander Madry
OODAAML
401
837
0
30 Apr 2018
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with
  Adversarial Examples
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples
Minhao Cheng
Jinfeng Yi
Pin-Yu Chen
Huan Zhang
Cho-Jui Hsieh
SILMAAML
376
254
0
03 Mar 2018
Fooling OCR Systems with Adversarial Text Images
Fooling OCR Systems with Adversarial Text Images
Congzheng Song
Vitaly Shmatikov
AAML
95
53
0
15 Feb 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A
  Survey
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Naveed Akhtar
Lin Wang
AAML
429
1,976
0
02 Jan 2018
On the Robustness of Semantic Segmentation Models to Adversarial Attacks
On the Robustness of Semantic Segmentation Models to Adversarial Attacks
Anurag Arnab
O. Mikšík
Juil Sock
AAML
322
325
0
27 Nov 2017
Adversarial Attacks Beyond the Image Space
Adversarial Attacks Beyond the Image Space
Fangyin Wei
Chenxi Liu
Yu-Siang Wang
Weichao Qiu
Lingxi Xie
Yu-Wing Tai
Chi-Keung Tang
Alan Yuille
AAML
370
158
0
20 Nov 2017
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