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Yunxiao Qin
Researcher at Northwestern Polytechnical University
Publications - 37
Citations - 1014
Yunxiao Qin is an academic researcher from Northwestern Polytechnical University. The author has contributed to research in topics: Spoofing attack & Facial recognition system. The author has an hindex of 9, co-authored 34 publications receiving 361 citations. Previous affiliations of Yunxiao Qin include Chinese Academy of Sciences & Communication University of China.
Papers
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Proceedings ArticleDOI
Searching Central Difference Convolutional Networks for Face Anti-Spoofing
TL;DR: Yu et al. as discussed by the authors proposed a frame level FAS method based on Central Difference Convolution (CDC), which is able to capture intrinsic detailed patterns via aggregating both intensity and gradient information.
Proceedings ArticleDOI
Deep Spatial Gradient and Temporal Depth Learning for Face Anti-Spoofing
TL;DR: A new approach to detect presentation attacks from multiple frames based on two insights, able to capture discriminative details via Residual Spatial Gradient Block (RSGB) and encode spatio-temporal information from Spatio-Temporal Propagation Module (STPM) efficiently.
Journal ArticleDOI
NAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofing
TL;DR: This work proposes the first FAS method based on neural architecture search (NAS), called NAS-FAS, to discover the well-suited task-aware networks, and develops a novel search space consisting of central difference convolution and pooling operators.
Journal ArticleDOI
Learning meta model for zero- and few-shot face anti-spoofing
Yunxiao Qin,Chenxu Zhao,Xiangyu Zhu,Zezheng Wang,Zitong Yu,Tianyu Fu,Feng Zhou,Jingping Shi,Zhen Lei +8 more
TL;DR: A novel Adaptive Inner-update Meta Face Anti-Spoofing (AIM-FAS) method, which trains a meta-learner focusing on the task of detecting unseen spoofing types by learning from predefined living and spoofing faces and a few examples of new attacks.
Posted Content
Exploiting temporal and depth information for multi-frame face anti-spoofing.
TL;DR: A new method to estimate depth information from multiple RGB frames is developed and a depth-supervised architecture which can efficiently encodes spatiotemporal information for presentation attack detection is proposed.