most citedSelf-Domain Adaptation for Face Anti-Spoofing

3 citations · 6 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV20221 cited

Multi-Scale Wavelet Transformer for Face Forgery Detection

Jie Liu, Jingjing Wang, Peng Zhang +3

Currently, many face forgery detection methods aggregate spatial and frequency features to enhance the generalization ability and gain promising performance under the cross-dataset…

cs.CV2022

Weakly Supervised Regional and Temporal Learning for Facial Action Unit Recognition

Jingwei Yan, Jingjing Wang, Qiang Li +2

Automatic facial action unit (AU) recognition is a challenging task due to the scarcity of manual annotations. To alleviate this problem, a large amount of efforts has been dedicat…

cs.CV2022

Few-shot One-class Domain Adaptation Based on Frequency for Iris Presentation Attack Detection

Yachun Li, Ying Lian, Jingjing Wang +3

Iris presentation attack detection (PAD) has achieved remarkable success to ensure the reliability and security of iris recognition systems. Most existing methods exploit discrimin…

cs.CV20221 cited

Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression

Qiang Li, Jingjing Wang, Zhaoliang Yao +5

Learning from a label distribution has achieved promising results on ordinal regression tasks such as facial age and head pose estimation wherein, the concept of adaptive label dis…

cs.CV2022

Learning Multiple Explainable and Generalizable Cues for Face Anti-spoofing

Ying Bian, Peng Zhang, Jingjing Wang +2

Although previous CNN based face anti-spoofing methods have achieved promising performance under intra-dataset testing, they suffer from poor generalization under cross-dataset tes…

cs.CV20211 cited

Self-Supervised Regional and Temporal Auxiliary Tasks for Facial Action Unit Recognition

Jingwei Yan, Jingjing Wang, Qiang Li +2

Automatic facial action unit (AU) recognition is a challenging task due to the scarcity of manual annotations. To alleviate this problem, a large amount of efforts has been dedicat…