FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack

09/15/2021
by   DonghuaWang, et al.
0

Physical adversarial attacks in object detection have attracted increasing attention. However, most previous works focus on hiding the objects from the detector by generating an individual adversarial patch, which only covers the planar part of the vehicle's surface and fails to attack the detector in physical scenarios for multi-view, long-distance and partially occluded objects. To bridge the gap between digital attacks and physical attacks, we exploit the full 3D vehicle surface to propose a robust Full-coverage Camouflage Attack (FCA) to fool detectors. Specifically, we first try rendering the non-planar camouflage texture over the full vehicle surface. To mimic the real-world environment conditions, we then introduce a transformation function to transfer the rendered camouflaged vehicle into a photo-realistic scenario. Finally, we design an efficient loss function to optimize the camouflage texture. Experiments show that the full-coverage camouflage attack can not only outperform state-of-the-art methods under various test cases but also generalize to different environments, vehicles, and object detectors.

READ FULL TEXT

page 1

page 3

page 5

page 7

research
07/31/2020

Physical Adversarial Attack on Vehicle Detector in the Carla Simulator

In this paper, we tackle the issue of physical adversarial examples for ...
research
08/14/2023

ACTIVE: Towards Highly Transferable 3D Physical Camouflage for Universal and Robust Vehicle Evasion

Adversarial camouflage has garnered attention for its ability to attack ...
research
03/18/2022

DTA: Physical Camouflage Attacks using Differentiable Transformation Network

To perform adversarial attacks in the physical world, many studies have ...
research
02/19/2023

X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection

Adversarial attacks are valuable for evaluating the robustness of deep l...
research
09/10/2019

UPC: Learning Universal Physical Camouflage Attacks on Object Detectors

In this paper, we study physical adversarial attacks on object detectors...
research
10/10/2021

Adversarial Attacks in a Multi-view Setting: An Empirical Study of the Adversarial Patches Inter-view Transferability

While machine learning applications are getting mainstream owing to a de...
research
10/17/2022

Differential Evolution based Dual Adversarial Camouflage: Fooling Human Eyes and Object Detectors

Recent studies reveal that deep neural network (DNN) based object detect...

Please sign up or login with your details

Forgot password? Click here to reset