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

Xiangyu Zhang

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

4 / 4 papers shown

Title
Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics Taowen Wang Dongfang Liu James Liang Wenhao Yang Qifan Wang Cheng Han Jiebo Luo Ruixiang Tang Ruixiang Tang AAML 79 3 0 18 Nov 2024
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 Kaichen Zhou Lanqing Hong Changhao Chen Hang Xu Chao Ye Qingyong Hu Zhenguo Li MDE 92 31 0 14 Sep 2022
Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation Rui Peng Ronggang Wang Yawen Lai Luyang Tang Yangang Cai MDE 67 72 0 26 Sep 2021