Y
Yaojie Liu
Researcher at Michigan State University
Publications - 22
Citations - 1725
Yaojie Liu is an academic researcher from Michigan State University. The author has contributed to research in topics: Spoofing attack & Facial recognition system. The author has an hindex of 11, co-authored 20 publications receiving 1031 citations. Previous affiliations of Yaojie Liu include Ohio State University & University of Electronic Science and Technology of China.
Papers
More filters
Proceedings ArticleDOI
Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision
TL;DR: This paper argues the importance of auxiliary supervision to guide the learning toward discriminative and generalizable cues, and introduces a new face anti-spoofing database that covers a large range of illumination, subject, and pose variations.
Proceedings ArticleDOI
Face anti-spoofing using patch and depth-based CNNs
TL;DR: A novel two-stream CNN-based approach for face anti-spoofing is proposed, by extracting the local features and holistic depth maps from the face images, which facilitate CNN to discriminate the spoof patches independent of the spatial face areas.
Proceedings ArticleDOI
Deep Tree Learning for Zero-Shot Face Anti-Spoofing
TL;DR: Zhang et al. as mentioned in this paper proposed a novel Deep Tree Network (DTN) to tackle the zero-shot face anti-spoofing (ZSFA) problem by partitioning the spoof samples into semantic sub-groups in an unsupervised fashion.
Book ChapterDOI
Face De-Spoofing: Anti-Spoofing via Noise Modeling
TL;DR: A CNN architecture with proper constraints and supervisions is proposed to overcome the problem of having no ground truth for the decomposition of face de-spoofing, and the results show promising improvements due to the spoof noise modeling.
Proceedings ArticleDOI
Dense Face Alignment
TL;DR: Li et al. as mentioned in this paper proposed a CNN to estimate the 3D face shape, which not only aligns limited facial landmarks but also fits face contours and SIFT feature points.