38 citations
- Northwestern Polytechnical UniversityCN5 papers
- Institute of AutomationCN3 papers
- University of OuluFI3 papers
- Chinese Academy of SciencesCN2 papers
- University of Chinese Academy of SciencesCN2 papers
- Aibee (China)1 paper
- Hefei University of TechnologyCN1 paper
- University of South AustraliaAU1 paper
- Westlake UniversityCN1 paper
5 papers · 2 filters
Layer-Wise Adaptive Updating for Few-Shot Image Classification
Yunxiao Qin, Weiguo Zhang, Zezheng Wang +2
Few-shot image classification (FSIC), which requires a model to recognize new categories via learning from few images of these categories, has attracted lots of attention. Recently…
Multi-Modal Face Anti-Spoofing Based on Central Difference Networks
Zitong Yu, Yunxiao Qin, Xiaobai Li +4
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from presentation attacks. Existing multi-modal FAS methods rely on stacked vanilla convolutions, w…
Learning Meta Face Recognition in Unseen Domains
Jianzhu Guo, Xiangyu Zhu, Chenxu Zhao +3
Face recognition systems are usually faced with unseen domains in real-world applications and show unsatisfactory performance due to their poor generalization. For example, a well-…
Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
Zezheng Wang, Zitong Yu, Chenxu Zhao +5
Face anti-spoofing is critical to the security of face recognition systems. Depth supervised learning has been proven as one of the most effective methods for face anti-spoofing. D…
Searching Central Difference Convolutional Networks for Face Anti-Spoofing
Zitong Yu, Chenxu Zhao, Zezheng Wang +5
Face anti-spoofing (FAS) plays a vital role in face recognition systems. Most state-of-the-art FAS methods 1) rely on stacked convolutions and expert-designed network, which is wea…