DeepAI AI Chat
Log In Sign Up

Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack

by   Feixiang He, et al.

Action recognition has been heavily employed in many applications such as autonomous vehicles, surveillance, etc, where its robustness is a primary concern. In this paper, we examine the robustness of state-of-the-art action recognizers against adversarial attack, which has been rarely investigated so far. To this end, we propose a new method to attack action recognizers that rely on 3D skeletal motion. Our method involves an innovative perceptual loss that ensures the imperceptibility of the attack. Empirical studies demonstrate that our method is effective in both white-box and black-box scenarios. Its generalizability is evidenced on a variety of action recognizers and datasets. Its versatility is shown in different attacking strategies. Its deceitfulness is proven in extensive perceptual studies. Our method shows that adversarial attack on 3D skeletal motions, one type of time-series data, is significantly different from traditional adversarial attack problems. Its success raises serious concern on the robustness of action recognizers and provides insights on potential improvements.


SMART: Skeletal Motion Action Recognition aTtack

Adversarial attack has inspired great interest in computer vision, by sh...

BASAR:Black-box Attack on Skeletal Action Recognition

Skeletal motion plays a vital role in human activity recognition as eith...

Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers

The success of deep learning research has catapulted deep models into pr...

Adversarial Attack on Skeleton-based Human Action Recognition

Deep learning models achieve impressive performance for skeleton-based h...

Adversarial Bone Length Attack on Action Recognition

Skeleton-based action recognition models have recently been shown to be ...

Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition

Skeleton-based action recognition has attracted increasing attention due...

Investigating Top-k White-Box and Transferable Black-box Attack

Existing works have identified the limitation of top-1 attack success ra...