activity
20192022
most citedNAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofing

270 citations · 515 across the 22 of their papers we have counts for

collaborators

28 papers

cs.CV2022

Face Presentation Attack Detection

Zitong Yu, Chenxu Zhao, Zhen Lei

Face recognition technology has been widely used in daily interactive applications such as checking-in and mobile payment due to its convenience and high accuracy. However, its vul…

cs.CV20221 cited

Learning Motion-Robust Remote Photoplethysmography through Arbitrary Resolution Videos

Jianwei Li, Zitong Yu, Jingang Shi

Remote photoplethysmography (rPPG) enables non-contact heart rate (HR) estimation from facial videos which gives significant convenience compared with traditional contact-based mea…

eess.IV2022

Boosting Binary Neural Networks via Dynamic Thresholds Learning

Jiehua Zhang, Xueyang Zhang, Zhuo Su +5

Developing lightweight Deep Convolutional Neural Networks (DCNNs) and Vision Transformers (ViTs) has become one of the focuses in vision research since the low computational cost i…

cs.CV2022

Forensicability Assessment of Questioned Images in Recapturing Detection

Changsheng Chen, Lin Zhao, Rizhao Cai +3

Recapture detection of face and document images is an important forensic task. With deep learning, the performances of face anti-spoofing (FAS) and recaptured document detection ha…

cs.CV202213 cited

Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofing

Zhuo Wang, Zezheng Wang, Zitong Yu +4

With diverse presentation attacks emerging continually, generalizable face anti-spoofing (FAS) has drawn growing attention. Most existing methods implement domain generalization (D…

cs.CV20221 cited

ViTransPAD: Video Transformer using convolution and self-attention for Face Presentation Attack Detection

Zuheng Ming, Zitong Yu, Musab Al-Ghadi +3

Face Presentation Attack Detection (PAD) is an important measure to prevent spoof attacks for face biometric systems. Many works based on Convolution Neural Networks (CNNs) for fac…