all AI news
On the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Driving. (arXiv:2201.01850v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
The existence of real-world adversarial examples (commonly in the form of
patches) poses a serious threat for the use of deep learning models in
safety-critical computer vision tasks such as visual perception in autonomous
driving. This paper presents an extensive evaluation of the robustness of
semantic segmentation models when attacked with different types of adversarial
patches, including digital, simulated, and physical ones. A novel loss function
is proposed to improve the capabilities of attackers in inducing a
misclassification of pixels. …
arxiv autonomous autonomous driving cv real-time segmentation semantic time