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. 2404.00924
  4. Cited By
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise
  Regression Tasks

BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks

1 April 2024
Zhiyuan Cheng
Zhaoyi Liu
Tengda Guo
Shiwei Feng
Dongfang Liu
Mingjie Tang
Xiangyu Zhang
    AAML
ArXivPDFHTML

Papers citing "BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks"

5 / 5 papers shown
Title
Self-supervised Adversarial Training of Monocular Depth Estimation
  against Physical-World Attacks
Self-supervised Adversarial Training of Monocular Depth Estimation against Physical-World Attacks
Zhiyuan Cheng
Cheng Han
James Liang
Qifan Wang
Xiangyu Zhang
Dongfang Liu
AAML
19
4
0
09 Jun 2024
CLUSTSEG: Clustering for Universal Segmentation
CLUSTSEG: Clustering for Universal Segmentation
James Liang
Tianfei Zhou
Dongfang Liu
Wenguan Wang
VLM
59
47
0
03 May 2023
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D
  Object Detection
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection
Zhiyuan Cheng
Hongjun Choi
James Liang
Shiwei Feng
Guanhong Tao
Dongfang Liu
Michael Zuzak
Xiangyu Zhang
AAML
17
11
0
28 Apr 2023
EvoBA: An Evolution Strategy as a Strong Baseline forBlack-Box
  Adversarial Attacks
EvoBA: An Evolution Strategy as a Strong Baseline forBlack-Box Adversarial Attacks
Andrei-Șerban Ilie
Marius Popescu
Alin Stefanescu
AAML
18
6
0
12 Jul 2021
SentiNet: Detecting Localized Universal Attacks Against Deep Learning
  Systems
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems
Edward Chou
Florian Tramèr
Giancarlo Pellegrino
AAML
148
284
0
02 Dec 2018
1