activity
20202026
most citedInstance-Aware Domain Generalization for Face Anti-Spoofing

99 citations · 361 across the 41 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

cs.CR2022

Artificial Intelligence Security Competition (AISC)

Yinpeng Dong, Peng Chen, Senyou Deng +49

The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems. To accelerate the research on AI security, the Artifi…

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★ 64 cited

Adaptive Mixture of Experts Learning for Generalizable Face Anti-Spoofing

Qianyu Zhou, Ke-Yue Zhang, Taiping Yao +3

With various face presentation attacks emerging continually, face anti-spoofing (FAS) approaches based on domain generalization (DG) have drawn growing attention. Existing DG-based…

cs.CV2022★ 67 cited

Generative Domain Adaptation for Face Anti-Spoofing

Qianyu Zhou, Ke-Yue Zhang, Taiping Yao +4

Face anti-spoofing (FAS) approaches based on unsupervised domain adaption (UDA) have drawn growing attention due to promising performances for target scenarios. Most existing UDA F…

cs.CV2022★ 2 cited

Entropy-driven Sampling and Training Scheme for Conditional Diffusion Generation

Shengming Li, Guangcong Zheng, Hui Wang +4

Denoising Diffusion Probabilistic Model (DDPM) is able to make flexible conditional image generation from prior noise to real data, by introducing an independent noise-aware classi…

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…