TY - GEN
T1 - CNN-Based Anomaly Detection for Face Presentation Attack Detection with Multi-Channel Images
AU - Zhang, Yuge
AU - Zhao, Min
AU - Yan, Longbin
AU - Gao, Tiande
AU - Chen, Jie
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/1
Y1 - 2020/12/1
N2 - Recently, face recognition systems have received significant attention, and there have been many works focused on presentation attacks (PAs). However, the generalization capacity of PAs is still challenging in real scenarios, as the attack samples in the training database may not cover all possible PAs. In this paper, we propose to perform the face presentation attack detection (PAD) with multi-channel images using the convolutional neural network based anomaly detection. Multi-channel images endow us with rich information to distinguish between different mode of attacks, and the anomaly detection based technique ensures the generalization performance. We evaluate the performance of our methods using the wide multi-channel presentation attack (WMCA) dataset.
AB - Recently, face recognition systems have received significant attention, and there have been many works focused on presentation attacks (PAs). However, the generalization capacity of PAs is still challenging in real scenarios, as the attack samples in the training database may not cover all possible PAs. In this paper, we propose to perform the face presentation attack detection (PAD) with multi-channel images using the convolutional neural network based anomaly detection. Multi-channel images endow us with rich information to distinguish between different mode of attacks, and the anomaly detection based technique ensures the generalization performance. We evaluate the performance of our methods using the wide multi-channel presentation attack (WMCA) dataset.
KW - Face presentation attack detection
KW - anomaly detection
KW - multi-channel CNN
UR - https://www.scopus.com/pages/publications/85099456638
U2 - 10.1109/VCIP49819.2020.9301818
DO - 10.1109/VCIP49819.2020.9301818
M3 - 会议稿件
AN - SCOPUS:85099456638
T3 - 2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020
SP - 189
EP - 192
BT - 2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020
Y2 - 1 December 2020 through 4 December 2020
ER -