211 citations · 279 across the 4 of their papers we have counts for
8 papers
Noise Modeling, Synthesis and Classification for Generic Object Anti-Spoofing
Joel Stehouwer, Amin Jourabloo, Yaojie Liu +1
Using printed photograph and replaying videos of biometric modalities, such as iris, fingerprint and face, are common attacks to fool the recognition systems for granting access as…
Deep Tree Learning for Zero-shot Face Anti-Spoofing
Yaojie Liu, Joel Stehouwer, Amin Jourabloo +1
Face anti-spoofing is designed to keep face recognition systems from recognizing fake faces as the genuine users. While advanced face anti-spoofing methods are developed, new types…
Face De-Spoofing: Anti-Spoofing via Noise Modeling
Amin Jourabloo, Yaojie Liu, Xiaoming Liu
Many prior face anti-spoofing works develop discriminative models for recognizing the subtle differences between live and spoof faces. Those approaches often regard the image as an…
Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision
Yaojie Liu, Amin Jourabloo, Xiaoming Liu
Face anti-spoofing is the crucial step to prevent face recognition systems from a security breach. Previous deep learning approaches formulate face anti-spoofing as a binary classi…
Do Convolutional Neural Networks Learn Class Hierarchy?
Bilal Alsallakh, Amin Jourabloo, Mao Ye +2
Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possib…
Dense Face Alignment
Yaojie Liu, Amin Jourabloo, William Ren +1
Face alignment is a classic problem in the computer vision field. Previous works mostly focus on sparse alignment with a limited number of facial landmark points, i.e., facial land…