Journal of Shandong University(Engineering Science) ›› 2023, Vol. 53 ›› Issue (6): 1-7.doi: 10.6040/j.issn.1672-3961.0.2023.132
• Machine Learning & Data Mining • Next Articles
Jiachun LI(),Bowen LI,Jianbo CHANG
CLC Number:
1 |
PATEL K , HAN H , JAIN A K . Secure face unlock: spoof detection on smartphones[J]. IEEE Transactions on Information Forensics and Security, 2016, 11 (10): 2268- 2283.
doi: 10.1109/TIFS.2016.2578288 |
2 | KOMULAINEN J, HADID A, PIETIKÄINEN M. Context based face anti-spoofing[C]//Proceedings of the 2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS). Arlington, USA: IEEE, 2013: 6712690. |
3 | YANG J, LEI Z, LI S Z. Learn convolutional neural network for face anti-spoofing[EB/OL]. (2014-08-26)[2023-02-21]. https://arxiv.org/abs/1408.5601. |
4 | XU Z, LI S, DENG W. Learning temporal features using LSTM-CNN architecture for face anti-spoofing[C]//Proceedings of the 2015 3rd IAPR Asian Conference on Pattern Recognition(ACPR). Kuala Lumpur, Malaysia: IEEE, 2015: 141-145. |
5 | WANG Z, YU Z, ZHAO C, et al. Deep spatial gradient and temporal depth learning for face anti-spoofing[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, USA: IEEE, 2020: 5042-5051. |
6 | ZHANG S, WANG X, LIU A, et al. A dataset and benchmark for large-scale multi-modal face anti-spoofing[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Long Beach, USA: IEEE, 2019: 919-928. |
7 |
WANG Z , WANG Q , DENG W , et al. Learning multi-granularity temporal characteristics for face anti-spoofing[J]. IEEE Transactions on Information Forensics and Security, 2022, 17, 1254- 1269.
doi: 10.1109/TIFS.2022.3158062 |
8 | ATOUM Y, LIU Y, JOURABLOO A, et al. Face anti-spoofing using patch and depth-based CNNs[C]//Proceedings of the 2017 IEEE International Joint Conference on Biometrics (IJCB). Denver, USA: IEEE, 2017: 319-328. |
9 | KIM T, KIM Y H, KIM I, et al. BASN: enriching feature representation using bipartite auxiliary supervisions for face anti-spoofing[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops. Seoul, Korea: IEEE, 2019: 494-503. |
10 | GEORGE A, MARCEL S. Deep pixel-wise binary supervision for face presentation attack detection[C]// Proceedings of the 2019 International Conference on Biometrics (ICB). Crete, Greece: IEEE, 2019: 19352833. |
11 | RONNEBERGER O, FISCHER P, BROX T. U-Net: convolutional networks for biomedical image segmentation[C]//Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention. Munich, Germany: Springer, 2015: 234-241. |
12 | SANDLER M, HOWARD A, ZHU M, et al. MobileNetV2: inverted residuals and linear bottlenecks[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Salt Lake City, USA: IEEE, 2018: 4510-4520. |
13 | VISIN F, KASTNER K, CHO K, et al. ReNet: a recurrent neural network based alternative to convolutional networks[EB/OL]. (2015-07-23)[2023-02-21]. https://arxiv.org/abs/1505.00393. |
14 | BOULKENAFET Z, KOMULAINEN J, LI L, et al. OULU-NPU: a mobile face presentation attack database with real-world variations[C]//Proceedings of the 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017). Washington, USA: IEEE, 2017: 612-618. |
15 | CHINGOVSKA I, ANJOS A, MARCEL S. On the effectiveness of local binary patterns in face anti-spoofing[C]//2012 BIOSIG-Proceedings of the International Conference of Biometrics Special Interest Group (BIOSIG). Darmstadt, Germany: IEEE, 2012: 13029854. |
16 | ZHANG Z, YAN J, LIU S, et al. A face anti-spoofing database with diverse attacks[C]//Proceedings of the 2012 5th IAPR International Conference on Biometrics (ICB). New Delhi, India: IEEE, 2012: 26-31. |
17 | LIU Y, JOURABLOO A, LIU X. Learning deep models for face anti-spoofing: binary or auxiliary supervision[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Salt Lake City, USA: IEEE, 2018: 389-398. |
18 | BOULKENAFET Z, KOMULAINEN J, AKHTAR Z, et al. A competition on generalized software-based face presentation attack detection in mobile scenarios[C]//Proceedings of the 2017 IEEE International Joint Conference on Biometrics (IJCB). Denver, USA: IEEE, 2017: 688-696. |
19 | JOURABLOO A, LIU Y, LIU X. Face de-spoofing: anti-spoofing via noise modeling[C]//Proceedings of the European Conference on Computer Vision (ECCV). Munich, Germany: IEEE, 2018: 290-306. |
20 | LIU Y, STEHOUWER J, LIU X. On disentangling spoof trace for generic face anti-spoofing[C]//Proceedings of the European Conference on Computer Vision. Glasgow, England: Springer, 2020: 406-422. |
[1] | Yue YUAN,Yanli WANG,Kan LIU. Named entity recognition model based on dilated convolutional block architecture [J]. Journal of Shandong University(Engineering Science), 2022, 52(6): 105-114. |
[2] | Tongyu JIANG, Fan CHEN, Hongjie HE. Lightweight face super-resolution network based on asymmetric U-pyramid reconstruction [J]. Journal of Shandong University(Engineering Science), 2022, 52(1): 1-8. |
[3] | Jianqing WU,Xiuguang SONG. Review on development of simultaneous localization and mapping technology [J]. Journal of Shandong University(Engineering Science), 2021, 51(5): 16-31. |
[4] | Qingfa CHAI,Shoujing SUN,Jifu QIU,Ming CHEN,Zhen WEI,Wei CONG. Prediction method of power grid emergency supplies under meteorological disasters [J]. Journal of Shandong University(Engineering Science), 2021, 51(3): 76-83. |
[5] | YANG Xiuyuan, PENG Tao, YANG Liang, LIN Hongfei. Adaptive multi-domain sentiment analysis based on knowledge distillation [J]. Journal of Shandong University(Engineering Science), 2021, 51(3): 15-21. |
[6] | LIAO Jinping, MO Yuchang, YAN Ke. Model and application of short-term electricity consumption forecast based on C-LSTM [J]. Journal of Shandong University(Engineering Science), 2021, 51(2): 90-97. |
[7] | LIU Shuai, WANG Lei, DING Xutao. Emotional EEG recognition based on Bi-LSTM [J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 35-39. |
[8] | Guoyong CAI,Xinhao HE,Yangyang CHU. Visual sentiment analysis based on spatial attention mechanism and convolutional neural network [J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 8-13. |
[9] | Chunyang LI,Nan LI,Tao FENG,Zhuhe WANG,Jingkai MA. Abnormal sound detection of washing machines based on deep learning [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 108-117. |
[10] | Delei CHEN, Cheng WANG, Jianwei CHEN, Yiyin WU. GRU-based collaborative filtering recommendation algorithm with active learning [J]. Journal of Shandong University(Engineering Science), 2020, 50(1): 21-27. |
[11] | Ji ZHANG,Cui JIN,Hongyuan WANG,Shoubing CHEN. Pedestrian recognition based on singular value decomposition pedestrian alignment network [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 91-97. |
[12] | Peng WAN. Object detection of 3D point clouds based on F-PointNet [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 98-104. |
[13] | Zhixiang LIANG,Xiaoming LIU,Ying MU,Yutian LIU. Prediction method of wind power and PV ramp event based on deep learning [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 24-28. |
[14] | Yutian LIU, Runjia SUN, Hongtao WANG, Xueping GU. Review on application of artificial intelligence in power system restoration [J]. Journal of Shandong University(Engineering Science), 2019, 49(5): 1-8. |
[15] | Lizhao LI, Guoyong CAI, Jiao PAN. A microblog rumor events detection method based on C-GRU [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 102-106. |
|