All Papers

Title

Adversarial Robustness of Deep Sensor Fusion Models

v1v2v3 (latest)

Adversarial Robustness of Deep Sensor Fusion Models

IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2025

23 June 2020

Ayan Chakrabarti

Yevgeniy Vorobeychik

ArXiv (abs)PDF HTML

Papers citing "Adversarial Robustness of Deep Sensor Fusion Models"

7 / 7 papers shown

Title
Adversarial Examples in Environment Perception for Automated Driving (Review) Jun Yan Huilin Yin AAML 144 1 0 11 Apr 2025
Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception Luke Chen Junyao Wang Trier Mortlock Pramod P. Khargonekar M. A. Al Faruque UQCV 208 1 0 25 Mar 2025
Module-wise Adaptive Adversarial Training for End-to-end Autonomous Driving Tianyuan Zhang Lu Wang Jiaqi Kang Xinwei Zhang Yaning Tan Yuwei Chen Aishan Liu Xianglong Liu AAML 124 4 0 11 Sep 2024
Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks Yang Zheng Christian Scano Antonio Emanuele Cinà Xiaoyi Feng Zhaoqiang Xia Xiaoyue Jiang Ambra Demontis Battista Biggio Fabio Roli AAML 85 4 0 13 Sep 2023
Unified Adversarial Patch for Visible-Infrared Cross-modal Attacks in the Physical World Xingxing Wei Yao Huang Yitong Sun Jie Yu AAML 109 19 0 27 Jul 2023
Quantifying the robustness of deep multispectral segmentation models against natural perturbations and data poisoning Elise Bishoff Charles Godfrey Myles Mckay E. Byler AAML 89 1 0 18 May 2023
Billion-scale similarity search with GPUs Jeff Johnson Matthijs Douze Edouard Grave 665 4,052 0 28 Feb 2017