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. 2209.07735
  4. Cited By
Enhance the Visual Representation via Discrete Adversarial Training

Enhance the Visual Representation via Discrete Adversarial Training

16 September 2022
Xiaofeng Mao
YueFeng Chen
Ranjie Duan
Yao Zhu
Gege Qi
Shaokai Ye
Xiaodan Li
Rong Zhang
Hui Xue
ArXivPDFHTML

Papers citing "Enhance the Visual Representation via Discrete Adversarial Training"

14 / 64 papers shown
Title
The Open Images Dataset V4: Unified image classification, object
  detection, and visual relationship detection at scale
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale
Alina Kuznetsova
H. Rom
N. Alldrin
J. Uijlings
Ivan Krasin
...
S. Popov
Matteo Malloci
Alexander Kolesnikov
Tom Duerig
V. Ferrari
ObjD
VLM
85
1,340
0
02 Nov 2018
Robustness May Be at Odds with Accuracy
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
73
1,772
0
30 May 2018
Generating Natural Language Adversarial Examples
Generating Natural Language Adversarial Examples
M. Alzantot
Yash Sharma
Ahmed Elgohary
Bo-Jhang Ho
Mani B. Srivastava
Kai-Wei Chang
AAML
357
921
0
21 Apr 2018
YOLOv3: An Incremental Improvement
YOLOv3: An Incremental Improvement
Joseph Redmon
Ali Farhadi
ObjD
83
21,306
0
08 Apr 2018
Improving the Adversarial Robustness and Interpretability of Deep Neural
  Networks by Regularizing their Input Gradients
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients
A. Ross
Finale Doshi-Velez
AAML
139
679
0
26 Nov 2017
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDL
SSL
OCL
154
4,928
0
02 Nov 2017
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
233
9,687
0
25 Oct 2017
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
219
11,962
0
19 Jun 2017
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.3K
192,638
0
10 Dec 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
290
43,154
0
11 Feb 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
159
18,922
0
20 Dec 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
242
43,290
0
01 May 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
164
14,831
1
21 Dec 2013
Estimating or Propagating Gradients Through Stochastic Neurons for
  Conditional Computation
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Yoshua Bengio
Nicholas Léonard
Aaron Courville
300
3,099
0
15 Aug 2013
Previous
12