9 citations · 12 across the 7 of their papers we have counts for
7 papers
Improving the Transferability of Adversarial Attacks on Face Recognition with Diverse Parameters Augmentation
Fengfan Zhou, Bangjie Yin, Hefei Ling +2
Face Recognition (FR) models are vulnerable to adversarial examples that subtly manipulate benign face images, underscoring the urgent need to improve the transferability of advers…
ARLON: Boosting Diffusion Transformers with Autoregressive Models for Long Video Generation
Zongyi Li, Shujie Hu, Shujie Liu +7
Text-to-video models have recently undergone rapid and substantial advancements. Nevertheless, due to limitations in data and computational resources, achieving efficient generatio…
Adversarial Attacks on Both Face Recognition and Face Anti-spoofing Models
Fengfan Zhou, Qianyu Zhou, Hefei Ling +1
Adversarial attacks on Face Recognition (FR) systems have demonstrated significant effectiveness against standalone FR models. However, their practicality diminishes in complete FR…
Detecting Adversarial Data using Perturbation Forgery
Qian Wang, Chen Li, Yuchen Luo +4
As a defense strategy against adversarial attacks, adversarial detection aims to identify and filter out adversarial data from the data flow based on discrepancies in distribution…
Improving the JPEG-resistance of Adversarial Attacks on Face Recognition by Interpolation Smoothing
Kefu Guo, Fengfan Zhou, Hefei Ling +2
JPEG compression can significantly impair the performance of adversarial face examples, which previous adversarial attacks on face recognition (FR) have not adequately addressed. C…
Rethinking Impersonation and Dodging Attacks on Face Recognition Systems
Fengfan Zhou, Qianyu Zhou, Bangjie Yin +4
Face Recognition (FR) systems can be easily deceived by adversarial examples that manipulate benign face images through imperceptible perturbations. Adversarial attacks on FR encom…
Continual Adversarial Defense
Qian Wang, Hefei Ling, Yingwei Li +3
In response to the rapidly evolving nature of adversarial attacks against visual classifiers, numerous defenses have been proposed to generalize against as many known attacks as po…