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Self-supervised Adversarial Training of Monocular Depth Estimation
  against Physical-World Attacks

Self-supervised Adversarial Training of Monocular Depth Estimation against Physical-World Attacks

9 June 2024
Zhiyuan Cheng
Cheng Han
James Liang
Qifan Wang
Xiangyu Zhang
Dongfang Liu
    AAML
ArXivPDFHTML

Papers citing "Self-supervised Adversarial Training of Monocular Depth Estimation against Physical-World Attacks"

3 / 3 papers shown
Title
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
DevNet: Self-supervised Monocular Depth Learning via Density Volume
  Construction
DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction
Kaichen Zhou
Lanqing Hong
Changhao Chen
Hang Xu
Chao Ye
Qingyong Hu
Zhenguo Li
MDE
44
21
0
14 Sep 2022
Excavating the Potential Capacity of Self-Supervised Monocular Depth
  Estimation
Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation
Rui Peng
Ronggang Wang
Yawen Lai
Luyang Tang
Yangang Cai
MDE
53
72
0
26 Sep 2021
1