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MMAD-Purify: A Precision-Optimized Framework for Efficient and Scalable
  Multi-Modal Attacks

MMAD-Purify: A Precision-Optimized Framework for Efficient and Scalable Multi-Modal Attacks

17 October 2024
Xinxin Liu
Zhongliang Guo
Siyuan Huang
Chun Pong Lau
    AAML
    DiffM
ArXivPDFHTML

Papers citing "MMAD-Purify: A Precision-Optimized Framework for Efficient and Scalable Multi-Modal Attacks"

13 / 13 papers shown
Title
Instruct2Attack: Language-Guided Semantic Adversarial Attacks
Instruct2Attack: Language-Guided Semantic Adversarial Attacks
Jiang-Long Liu
Chen Wei
Yuxiang Guo
Heng Yu
Alan Yuille
Soheil Feizi
Chun Pong Lau
Rama Chellappa
DiffM
AAML
63
7
0
27 Nov 2023
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness
  and Controllability
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability
Haotian Xue
Alexandre Araujo
Bin Hu
Yongxin Chen
DiffM
84
46
0
25 May 2023
On Distillation of Guided Diffusion Models
On Distillation of Guided Diffusion Models
Chenlin Meng
Robin Rombach
Ruiqi Gao
Diederik P. Kingma
Stefano Ermon
Jonathan Ho
Tim Salimans
VLM
DiffM
73
521
0
06 Oct 2022
Mutual Adversarial Training: Learning together is better than going
  alone
Mutual Adversarial Training: Learning together is better than going alone
Jiang-Long Liu
Chun Pong Lau
Hossein Souri
Soheil Feizi
Ramalingam Chellappa
OOD
AAML
61
25
0
09 Dec 2021
Segment and Complete: Defending Object Detectors against Adversarial
  Patch Attacks with Robust Patch Detection
Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection
Jiangjiang Liu
Alexander Levine
Chun Pong Lau
Ramalingam Chellappa
Soheil Feizi
AAML
59
78
0
08 Dec 2021
Score-Based Generative Modeling through Stochastic Differential
  Equations
Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song
Jascha Narain Sohl-Dickstein
Diederik P. Kingma
Abhishek Kumar
Stefano Ermon
Ben Poole
DiffM
SyDa
338
6,480
0
26 Nov 2020
Generative Modeling by Estimating Gradients of the Data Distribution
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song
Stefano Ermon
SyDa
DiffM
258
3,916
0
12 Jul 2019
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture
  Design
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
Ningning Ma
Xiangyu Zhang
Haitao Zheng
Jian Sun
177
4,990
0
30 Jul 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler
Andrew G. Howard
Menglong Zhu
A. Zhmoginov
Liang-Chieh Chen
184
19,284
0
13 Jan 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
307
12,069
0
19 Jun 2017
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
772
36,813
0
25 Aug 2016
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
277
19,066
0
20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.6K
100,386
0
04 Sep 2014
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