activity
20182023
most citedAdv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition

23 citations · 57 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2023

Contrastive Pseudo Learning for Open-World DeepFake Attribution

Zhimin Sun, Shen Chen, Taiping Yao +4

The challenge in sourcing attribution for forgery faces has gained widespread attention due to the rapid development of generative techniques. While many recent works have taken es…

cs.CV2023★ 2 cited

Sibling-Attack: Rethinking Transferable Adversarial Attacks against Face Recognition

Zexin Li, Bangjie Yin, Taiping Yao +4

A hard challenge in developing practical face recognition (FR) attacks is due to the black-box nature of the target FR model, i.e., inaccessible gradient and parameter information…

cs.CV2022★ 23 cited

Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition

Shuai Jia, Bangjie Yin, Taiping Yao +4

Deep learning models have shown their vulnerability when dealing with adversarial attacks. Existing attacks almost perform on low-level instances, such as pixels and super-pixels,…

cs.CV2022★ 5 cited

Exploring Frequency Adversarial Attacks for Face Forgery Detection

Shuai Jia, Chao Ma, Taiping Yao +3

Various facial manipulation techniques have drawn serious public concerns in morality, security, and privacy. Although existing face forgery classifiers achieve promising performan…

cs.CV2021★ 4 cited

Structure Destruction and Content Combination for Face Anti-Spoofing

Ke-Yue Zhang, Taiping Yao, Jian Zhang +4

In pursuit of consolidating the face verification systems, prior face anti-spoofing studies excavate the hidden cues in original images to discriminate real persons and diverse att…

cs.CV2021★ 13 cited

Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition

Bangjie Yin, Wenxuan Wang, Taiping Yao +5

Deep neural networks, particularly face recognition models, have been shown to be vulnerable to both digital and physical adversarial examples. However, existing adversarial exampl…

cs.CV2021★ 3 cited

Delving into Data: Effectively Substitute Training for Black-box Attack

Wenxuan Wang, Bangjie Yin, Taiping Yao +6

Deep models have shown their vulnerability when processing adversarial samples. As for the black-box attack, without access to the architecture and weights of the attacked model, t…

cs.CR2018

The Untold Secrets of Operational Wi-Fi Calling Services: Vulnerabilities, Attacks, and Countermeasures

Tian Xie, Guan-Hua Tu, Bangjie Yin +5

Since 2016, all of four major U.S. operators have rolled out nationwide Wi-Fi calling services. They are projected to surpass VoLTE (Voice over LTE) and other VoIP services in term…

cs.CV2018★ 7 cited

Towards Interpretable Face Recognition

Bangjie Yin, Luan Tran, Haoxiang Li +2

Deep CNNs have been pushing the frontier of visual recognition over past years. Besides recognition accuracy, strong demands in understanding deep CNNs in the research community mo…