ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2012.00558
  4. Cited By
Robustness Out of the Box: Compositional Representations Naturally
  Defend Against Black-Box Patch Attacks

Robustness Out of the Box: Compositional Representations Naturally Defend Against Black-Box Patch Attacks

1 December 2020
Christian Cosgrove
Adam Kortylewski
Chenglin Yang
Alan Yuille
    AAML
ArXiv (abs)PDFHTML

Papers citing "Robustness Out of the Box: Compositional Representations Naturally Defend Against Black-Box Patch Attacks"

3 / 3 papers shown
PatchCURE: Improving Certifiable Robustness, Model Utility, and
  Computation Efficiency of Adversarial Patch Defenses
PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses
Chong Xiang
Tong Wu
Sihui Dai
Jonathan Petit
Suman Jana
Prateek Mittal
468
12
0
19 Oct 2023
Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey
Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey
Abhijith Sharma
Yijun Bian
Phil Munz
Apurva Narayan
VLMAAML
360
33
0
16 Jun 2022
PatchCleanser: Certifiably Robust Defense against Adversarial Patches
  for Any Image Classifier
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier
Chong Xiang
Saeed Mahloujifar
Prateek Mittal
VLMAAML
320
102
0
20 Aug 2021
1
Page 1 of 1